法国专利FR3034191A1 DETERMINATION OF TRAINING PRESSURE

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The invention relates to a method, an apparatus and a program product for determining a formation pressure for a reservoir. Measurement data for a preliminary test of a formation of the reservoir are received (400). The measurement data is analyzed to determine (404) a last read event and a corresponding last read last. Derived data for flow regime identification is determined (406) at least in part according to the measurement data. The derived data is analyzed to determine (408) a pressure derived response, and a formation pressure is determined (410) at least in part as a function of the last read event, the last read pressure, and the derived pressure response.
公开号:FR3034191A1
申请号:FR1552355
申请日:2015-03-23
公开日:2016-09-30
发明作者:Keith Pinto；Olivier Marche
申请人:Services Petroliers Schlumberger SA；
IPC主号:

专利说明:

[0001] 1 DETERMINATION OF TRAINING PRESSURE Background [0001] Generally, in oil and gas reservoirs, formation pressure for a well in a reservoir is directly associated with well performance. As is known, the formation pressure generally corresponds to the flow of fluids for a well, such fluids may include hydrocarbons. Therefore, formation pressure is an important attribute for determining the performance of a well, as well as for determining suitable recovery strategies to exploit the well. Generally, data acquisition tools (eg, downhole sensors, measuring tools, etc.) can be used to collect measurement data for a well, such measurement data being analytically available to determine various properties of the tank; well, and / or formations thereof. [0002] Computerized systems and methods are increasingly used to facilitate the analysis of the properties of tanks and wells. However, conventional systems and processes typically rely on the input and analysis of oil and gas professionals, and such conventional systems and processes generally provide limited reservoir characteristics, which must then be interpreted by these professionals. oil and gas facilities. Therefore, there is still a need in the art for improved computerized systems and processes for modeling, management and analysis of oil and gas reservoirs. Embodiments described herein relate to systems, methods, and computer program products that determine the formation pressures associated with an oil and gas reservoir. Measurement data for a preliminary test is received from a data acquisition tool, the measurement data being collected during a preliminary test of a formation of the reservoir. The measurement data is analyzed to determine an event last and a corresponding last read pressure for the preliminary test. Derived data for flow regime identification is determined from the measurement data, and the derived data is analyzed to determine a pressure derivative response. A formation pressure is determined for the formation at least in part as a function of the last read event, the last read pressure, and the pressure derivative response. [0004] These and other advantages and features are set forth in the claims appended hereto and which constitute another part of the invention. However, for a better understanding of the object described in the invention, and the advantages and objectives achieved by its use, reference will be made to the drawings and the description which accompanies them, in which embodiments of the invention are described. examples. This summary is simply provided to present a selection of concepts which are described in further detail later in the detailed description, and is not intended to identify key or essential features of the claimed object, nor intended to be used as an aid to limit the scope of the claimed object. Brief Description of the Drawings [0005] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate various embodiments and, together with the general description given above and the detailed description of certain embodiments thereof, below, serve to explain some embodiments. [0006] Fig. 1 is a block diagram of an exemplary hardware and software environment for a data processing system in accordance with the implementations of various technologies and techniques described herein. [0007] FIGS. 2A-2D illustrate simplified schematic views of an oilfield having subsurface formations containing reservoirs in accordance with the implementations of various technologies and techniques described herein. [0008] FIG. 3 illustrates a schematic view, partially in cross-section, of an oilfield having a plurality of data acquisition tools positioned at various locations along the oilfield to collect data from underground formations. in accordance with the implementations of various technologies and techniques described herein. [0009] Figure 4 illustrates a production system for performing one or more oil field operations in accordance with the implementations of various technologies and techniques described herein. Figure 5 shows a block diagram that illustrates a sequence of operations that can be performed by the data processing system of Figure 1 to determine a formation pressure. Fig. 6 shows a schematic illustration of a data acquisition tool positioned in a wellbore associated with a reservoir and configured to collect measurement data from a reservoir formation for Analysis by the data processing system of Fig. 1. [0012] Fig. 7A shows an example graph which illustrates measurement data that can be received by the data processing system of Fig. 1. [0013 Fig. 7B shows an example graph which illustrates the measurement data of Fig. 7A and includes various events which can be determined by analysis of the measurement data by the data processing system of Fig. 1. [0014] Figures 8A-8C show schematic illustrations of flow regimes for fluids that can be revealed in measurement data analyzed by the data processing system of the system. Fig. 9 shows a block diagram which illustrates a sequence of operations that may be performed by the data processing system of Fig. 1 to determine a formation pressure. Fig. 10A shows an example graph which illustrates derived data and a pressure derivative response which can be determined from the measurement data by the data processing system of Fig. 1. [0017] Fig. 10B shows an example graph which illustrates derived data which can be determined by the data processing system of FIG. 1. FIG. 10C shows an example graph which illustrates pressure data as a function of a spherical time function which can be analyzed by the data processing system of FIG. 1. FIG. 10D shows an example graph which illustrates pressure data as a function of a radial time function which can to be analyzed by the data processing system of FIG. 1. FIG. 10E shows an example graph which illustrates a draw-off mobility which can be determined by FIG. Figure 11A and 11B show schematic illustrations of sample data acquisition tools, measurement data collected by the data acquisition tools. , and derived data that can be determined from the measurement data by the data processing system of Fig. 1. Figs. 12-17, 18A, 18B, 18C, 19A, and 19B show user interfaces Example graphs that can be generated by the data processing system of FIG. 1. FIGS. 20A-H show graphs of examples which illustrate various pressure derived responses that can be determined. by the data processing system of Figure 1 from derived data analyzed by it. Detailed Description [0024] The embodiments described herein relate to methods, systems, and computer program products that determine the formation pressures associated with an oil and gas reservoir. In some embodiments, a data processing system may receive measurement data from a data acquisition tool that collects measurement data for reservoir formation. As will be understood, although reference is made to a single data acquisition tool, the embodiments are not limited thereto. In some embodiments, one or more of the data acquisition tools, such as downhole sensors, downhole measurement tools, training testers, cable forming tools, probes. , etc., can collect measurement data for the tank that can be received and analyzed by the data processing system to determine one or more formation pressures associated with the tank. For example, data acquisition tools may be positioned at different depths (also referred to as stations) in a wellbore associated with the reservoir so that measurement data can be collected at each station for training. associated with the tank. In this example, forming pressure for formation can be determined at each station according to embodiments described herein. As will be understood, the formation pressure at each station can be analyzed to determine a formation pressure gradient for formation, the formation pressure gradient indicating the formation pressure at various depths (i.e. at different stations). Additional features of the formation and / or the reservoir can be determined at least in part according to the determined formation pressures. Therefore, an accurate determination of formation pressure (or formation pressures at the different stations) is valuable information when analyzing an oil and gas reservoir. Generally, a data acquisition tool can perform one or more tests of a formation of a reservoir to collect measurement data over time. Some tests conducted for training are short-term and may be called "preliminary tests". 3034191 29469 / 290FRI 5 For a preliminary test, a small volume of fluid can be removed from the formation with a data acquisition tool (eg, a probe), and time-based measurement data that includes data Pressure drop and pressure rise are collected for each preliminary test. A preliminary test typically includes a small pressure drop and a resulting pressure rise that ends with a last reading pressure. As will also be understood, preliminary tests may be performed sequentially by a data acquisition tool so that time measurement data may be collected for each preliminary test, and measurement data of one or more Preliminary tests can be analyzed to determine the formation pressure. On the basis of the measurement data, preliminary test pressure events such as: mud before, start of fall, start of ascent, read last, and / or mud after can be identified. The identification of the most recently read preliminary test pressure event can be used to determine the formation pressure for the well. Generally, a pressure measured at the time of the last read event identified (referred to as the last read pressure) may correspond to the formation pressure. However, depending on the various characteristics of the formation, the positioning of the data acquisition tool, and / or other factors of this type, the pressure read last may not be an accurate measure of pressure. training. [0027] Therefore, in some embodiments, collected measurement data can be analyzed to determine if the last read pressure is accurate to determine the formation pressure. Specifically, a data processing system can analyze measurement data to determine derived data for flow regime identification, and a pressure derived response for the well can be determined from the derived data. The pressure derivative response can be analyzed to determine if the last read pressure is accurate to determine the formation pressure. If it is determined that the last read pressure is not accurate to determine the formation pressure, embodiments may adjust the last read pressure and / or determine the formation pressure at least in part depending on the derived data. and / or the pressure derivative response. Other variations and modifications will occur to a person normally skilled in the art.
[0002] Hardware and Software Environment [0029] Now consider the drawings, in which like numerals designate similar parts in all the views, where Figure 1 illustrates an exemplary data processing system 10 in which the various technologies and techniques described herein can be implemented. The system 10 is illustrated as having one or more computers 12, e.g. client computers, each having a CPU 14 having at least one core processor 16. The CPU 14 is coupled to a memory 18, which may represent the RAM devices including the main storage. of a computer 12, as well as any additional levels of memory, e.g. caches, non-volatile or backup memories (eg, programmable memories or flash), read-only memories, etc. In addition, memory 18 may be considered to include memory storage physically located elsewhere in a computer 12, e.g. any cache memory in a microprocessor or processing core, as well as any storage capacity used as virtual memory, e.g. stored on a mass storage device 10 or another computer coupled to a computer 12. Each computer 12 also generally receives a number of inputs and outputs for communicating information with the outside. To interact with a user or operator, a computer 12 generally includes a user interface 22 incorporating one or more user input / output devices, e.g. a keyboard, a pointing device, a screen, a printer, etc. Otherwise, a user input may be received, eg on a network interface 24 coupled to a network 26, from one or more external computers, e.g. one or more servers 28 or other computers 12. A computer 12 may also be in communication with one or more mass storage devices 20, which may be, for example, internal hard disk storage devices, external hard disk storage, storage networks, etc. In addition, a computer 12 may be in communication with one or more data acquisition tools, sensors, surface production network components, and / or other devices of this type that may be implemented in operations. oil and gas recovery and / or exploration. [0031] A computer 12 generally operates under the control of an operating system 30 and executes or otherwise depends on a variety of software applications, components, programs, objects, modules, data structures, etc. For example, a petrotechnical module or component 32 running within a reservoir and / or well analysis platform (also referred to in the present well analysis platforms) can be used to access to, process, generate, modify or otherwise utilize petrotechnical data, e.g. as stored locally in a database 36 and / or accessed remotely from a collaboration platform 38. The collaboration platform 38 may be implemented using multiple servers 28 in certain implementations, and it will be understood that each server 28 can integrate a CPU, a memory, and other hardware components similar to a computer 12. In a non-limiting embodiment, for example, the platform well analysis 34 may be implemented in the form of and / or in communication with one or more of the following: the MAXWELL acquisition software platform, the INSITU Pro software platform, the platform PD-PLOT software, the TECHLOG software platform, the GEOFRAME software platform, and the AVOCET software platform, while the collaboration platform 38 can be implemented in the form of the platform. OCEAN and the p STUDIO E & P KNOWLEDGE ENVIRONMENT, which are available from Schlumberger Ltd. and its subsidiaries. However, it will be appreciated that the techniques discussed herein may be used in conjunction with other platforms and environments, and the embodiments are not limited to the particular software platforms and environments discussed herein. In general, the routines executed to implement the embodiments described herein, whether they are implemented as part of an operating system or an application, a component, of a specific program, object, module or sequence of instructions, or even a subset thereof, will be referred to herein as "computer program code", or simply "program code". The program code generally comprises one or more instructions that are resident at different times in various memory and storage devices in a computer, and which, when read and executed by one or more hardware processors in a computer ( eg, microprocessors, processing cores, or other hardware logic), cause the computer to perform the steps implementing the desired functionality. Further, although embodiments will and will be described hereinafter in the context of fully operational computers and computer systems, those skilled in the art will appreciate that the various embodiments are capable of being distributed as a product. program in various forms, and that the description applies identically regardless of the particular type of computer readable medium used to actually perform the distribution. Such computer readable media may include computer readable storage media and communication media. The computer-readable storage media are non-transient in nature, and may include volatile and nonvolatile media, and removable and non-removable, implemented in any information storage method or technology, such as instructions. computer readable, data structures, program modules or other data. Computer readable storage media may include RAM, ROM, reprogrammable read-only memory 3034191 29469 / 290FRI 8 (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory or other solid state memory technology, a CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and which may be accessible by a computer 10. The communication media may comprise computer readable instructions, data structures or other program modules. By way of example, and not limited to, communication media may include wired media such as wired or direct wired network connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of any of the above may also be included in the scope of the computer readable media. The various program codes described below can be identified according to the application in which they are implemented in a specific embodiment. However, it should be understood that any particular program nomenclature that follows is before all used for convenience, and therefore the embodiments should not be limited to use only in any specific application identified and / or implied by such nomenclature. . Furthermore, given the infinite number of ways in which computer programs can be organized into routines, procedures, methods, modules, objects, and the like, as well as the various ways in which a functionality of a program can be allocated between various layers software that are resident in a typical computer (eg, operating systems, libraries, programming interfaces APIs, applications, applets, etc.), it should be understood that the embodiments are not limited to the organization and the specific allocation of a functionality of a program described herein. In addition, those skilled in the art having the teachings of this disclosure will understand that the various operations described herein which may be performed by any program code, or performed in any routine, process, or other, may be combined, divided, reordered, omitted, and / or supplemented with other techniques known in the art, and therefore the embodiments are not limited to the particular operation sequences described herein. Those skilled in the art will understand that the exemplary environment illustrated in FIG. 1 is not intended to be limiting. Indeed, those skilled in the art will appreciate that other alternative hardware and / or software environments may be used without departing from the object described herein. Oil Field Operations 3034191 29469 / 290EN1 9 [0038] FIGS. 2A-2D illustrate simplified schematic views of an oil field 100 having an underground formation 102 enclosing a reservoir 104 in accordance with the implementations of various technologies and techniques described in FIGS. present. Figure 2A illustrates a prospecting operation performed by a survey tool, such as a seismic truck 106.1, to measure properties of the subterranean formation. The prospecting operation is a seismic survey operation aimed at generating acoustic vibrations. In FIG. 2A, such an acoustic vibration, the acoustic vibration 112 generated by a source 110, is reflected on horizons 114 in a terrestrial formation 116. A set of acoustic vibrations is received by sensors, such as receiving geophones 118, located on the surface of the earth. The received data 120 is provided as input data to a computer 122.1 of a seismic truck 106.1, and in response to the input data, the computer 122.1 generates a seismic data output 124. This seismic data output can be stored, transmitted or transformed if desired, for example by reducing the data. [0039] FIG. 2B illustrates a drilling operation carried out by drilling tools 106.2 suspended on a drilling rig 128 and advanced in underground formations 102 to form a wellbore 136. A sludge tank 130 is used to draw on drilling mud in the drilling tools through a flow line 132 to move the drilling mud to the bottom by the drilling tools, then to the top of the wellbore 136 and again to the area. The drilling mud can be filtered and returned to the sludge tank. A circulation system can be used to store, regulate, or filter circulating drilling muds. The drilling tools are advanced into the underground formations 102 to reach the reservoir 104. Each well may target one or more reservoirs. Drilling tools are suitable for measuring downhole properties using logging tools while drilling. The logging tools being drilled can also be adapted to take a core 133 as indicated. [0040] Computer equipment may be positioned at various locations around the oil field 100 (eg, surface unit 134) and / or at remote locations. The surface unit 134 may be used to communicate with drilling tools and / or off-site operations, as well as with other surface or downhole sensors. The surface unit 134 is able to communicate with the drilling tools to send commands to the drilling tools, and to receive data therefrom. The surface unit 134 may also collect data generated during the drilling operation and produce a data output 135, which may then be stored or transmitted. [0041] Sensors (S), such as gauges, may be positioned around the oil field 100 to collect data relating to the various oilfield operations as previously described. As indicated, a sensor (S) is positioned at one or more locations in the drill tools and / or at the drill apparatus 128 for measuring drilling parameters, such as the weight on a tool, the torque on tool, pressures, temperatures, flow rates, compositions, rotational speed, and / or other field operating parameters. Sensors (S) can also be positioned at one or more points in the circulation system. The drilling tools 106.2 may comprise a bottom assembly (BHA) (not shown), generally referenced, near the drill bit (eg, at a length of some drill collars of the drill bit). drilling). The bottom assembly includes means for measuring, processing, and storing information, but also communicating with the surface unit 134. The bottom assembly further includes drill collars to provide various other measuring functions. [0043] The bottom assembly may comprise a communication subassembly that communicates with the surface unit 134. The communication subassembly is adapted to send signals to and receive signals from the surface using a communications channel such as sludge impulse transmission, electromagnetic telemetry, or wireline communications by drill pipes. The communication subassembly may include, for example, an emitter that generates a signal, such as an acoustic or electromagnetic signal, that is representative of the measured drilling parameters. Those skilled in the art will understand that a variety of telemetry systems may be employed, such as wire rod systems, electromagnetic systems and other known telemetry systems. Generally, the wellbore is drilled according to a drilling plan that is established before drilling. The drilling plan indicates the equipment, pressures, trajectories and / or other parameters that define the drilling process for the well location. The drilling operation can then be carried out in accordance with the drilling plan. However, as information is collected, the drilling operation may have to deviate from the drilling plan. In addition, when drilling or other operations are performed, conditions below the surface may change. The terrestrial model may also require adjustments as new information is collected. The data collected by the sensors (S) may be collected by the surface unit 134 and / or other sources of data collection for analysis or other processing by the data processing system 10 and / or other similar systems. The data collected by the sensors (S) can be used in isolation or together with other data. The data may be collected in one or more databases and / or transmitted on or off site. The data may be historical data, real-time data, or combinations thereof. Real-time data can be used in real time, or stored for later use. The data may also be combined with historical data or other inputs for further analysis. Data can be stored in separate databases, or combined into a single database. The surface unit 134 may include a transceiver 137 to allow communications between the surface unit 134 and various parts of the oil field 100 or other locations. The surface unit 134 may also be operatively or functionally connected to one or more controllers (not shown) for operating mechanisms at the oil field 100. The surface unit 134 may then send control signals to the field. 100 in response to the data received. The surface unit 134 may receive commands through the transceiver 137 or may itself execute commands to the controller. A processor may be provided to analyze the data (locally or remotely), make decisions and / or activate the controller. In this way, the oil field 100 can be selectively adjusted according to the data collected. This technique can be used to optimize parts of the field operation, for example control drilling, tool weight, or other parameters. These adjustments can be made automatically on the basis of a computer protocol, and / or manually by an operator.
[0003] In some cases, well plans may be adjusted to select optimal operating conditions, or to avoid problems. FIG. 2C illustrates a cable operation carried out by a tool on cable 106. 3 suspended from the drilling apparatus 128 and within the wellbore 136 of Figure 2B. The cable tool 106. 3 is adapted to be deployed in the wellbore 136 to generate well logs, perform downhole tests and / or collect samples. The cable tool 106. 3 may be used to implement another method and apparatus for conducting a seismic survey operation. The cable tool 106. 3 may, for example, have an explosive, radioactive, electrical, or acoustic energy source 144 that sends and / or receives electrical signals from surrounding subterranean formations 102 and fluids therein. The tool on cable 106. 3 may be operably connected, for example, to geophones 118 and a computer 122. 1 of a seismic truck 106. 1 of Figure 2A. The cable tool 106. 3 can also provide data to the surface unit 134. The surface unit 134 can collect data generated during the cable operation and can produce a data output 135 that can be stored or transmitted. The cable tool 106. 3 may be positioned at various depths in the wellbore 136 to conduct a survey or obtain other information regarding the underground formation 102. The cable tool 106. 3 may be configured to collect measurement data for one or more preliminary tests according to some embodiments. [0049] Sensors (S), such as gauges, may be positioned around the oil field 100 to collect data relating to the various field operations as previously described. As indicated, a sensor S is positioned in the cable tool 106. 3 for measuring downhole parameters relating to, for example, porosity, permeability, fluid composition, pressure, and / or other parameters of field operation, well / borehole , and / or tank. [0050] FIG. 2D illustrates a production operation carried out by a production tool 106. 4 deployed from a production unit or Christmas tree 129 and within a completed wellbore 136 for extracting fluid from downhole tanks at surface facilities 142. The fluid flows from the reservoir 104 through perforations in the casing (not shown) within the production tool 106. 4 in the wellbore 136 to join the surface facilities 142 by a collection network 146. Sensors (S), such as gauges, may be positioned around the oil field 100 to collect data relating to various field operations as previously described. As indicated, the sensor (S) can be positioned in the production tool 106. 4 or associated equipment, such as the Christmas tree 129, the collection network 146, the surface facilities 142, and / or the production facilities, for measuring fluid parameters, such as the composition of the fluid, flow rates, pressures, temperatures, and / or other parameters of the production operation. The production may also include injection wells for increased recovery. One or more collection facilities may be operatively connected to one or more of the well locations to selectively collect downhole fluids from the well location (s). Although FIGS. 2B-2D illustrate tools used to measure properties of an oilfield, it will be understood that the tools can be used in conjunction with operations not relating to oil fields, but natural gas fields. , mines, aquifers, storage facilities, or other underground facilities. In addition, although some of the data acquisition tools are shown, it will be understood that various measurement tools capable of detecting parameters such as seismic double time, density, resistivity, rate of production, etc. , the underground formation and / or its geological formations may be used. Various sensors (S) may be positioned at different locations along the wellbore and / or monitoring tools to collect and / or monitor the desired data. Other sources of data may also be obtained from offsite locations. The field configurations of Figs. 2A-2D are intended to provide a brief description of an example of a usable field for oil field applications. All or part of the oilfield 100 may be on land, in freshwater, and / or at sea. In addition, although only one field measured at one location is shown, the oil field applications can be used with any combination of one or more oilfields, one or more treatment plants and one or more several well locations. FIG. 3 illustrates a schematic view, partially in cross-section, of an oil field 200 having a plurality of data acquisition tools 202. 1, 202. 2, 202. 3 and 202. 4 positioned at various locations along the oil field 200 to collect data from an underground formation 204 in accordance with the implementations of various technologies and techniques described herein. Data Acquisition Tools 202. 1-202. 4 can be the same as the data acquisition tools 106. 1-106. Figures 2A-2D, respectively, or others not shown. As indicated, the data acquisition tools 202. 1-202. 4 generate data plots or measurements 208. 1-208. 4, respectively. These data plots are shown along the oil field 200 to illustrate the data generated by the various operations. As will be understood, the data acquisition tools 202. 1-202. 4 may collect measurement data for analysis in accordance with embodiments discussed herein. The data plots 208. 1-208. 3 are examples of static data plots that can be generated by the data acquisition tools 202. 1-202. 3, respectively, but it will be understood that the data plots 208. 1-208. 3 can also be data plots that are updated in real time. These measurements can be analyzed to better define the properties of the formation (s) and / or to determine the accuracy of the measurements and / or to check for errors. The plots of each of the respective measurements can be aligned and scaled for comparison and verification of properties. The static data plot 208. 1 is a bidirectional seismic response over a period of time. The static plot 208. 2 is based on core data measured from a core of formation 204. The core can be used to obtain data, such as a graph of density, porosity, permeability, or some other physical property of the core over the length of the core. Density and viscosity testing can be performed on fluids in the core at various pressures and temperatures. Static data plot 208. 3 is a logging plot that generally provides resistivity or other measure of formation at various depths. The curve or graph of decline of the production 208. 4 is a dynamic data plot of fluid flow over time. The decline curve of production typically provides the rate of production over time. As the fluid flows through the wellbore, fluid property measurements such as flow rates, pressures, composition, etc. are measured. , are taken. Other data may also be collected, such as historical data, user input, economic information, and / or other measurement data and other parameters of interest. As described below, static and dynamic measurements can be analyzed and used to generate models of the subsurface formation to determine their characteristics. Similar measures can also be used to measure changes in time of aspects of training. The underground structure 204 has a plurality of geological formations 206. 1-206. 4. As indicated, this structure has several formations or layers, in particular a shale layer 206. 1, a carbonate layer 206. 2, a layer of shale 206. 3 and a layer of sand 206. 4. A fault 207 extends through the shale layer 206. 1 and the carbonate layer 206. 2. Static data acquisition tools are adapted to take measurements and detect characteristics of the formations. Although a specific subterranean formation with specific geological structures is shown, it will be understood that the oilfield 200 may contain a variety of geological structures and / or formations, sometimes with extreme complexity. In some places, generally below the water-oil boundary, the fluid may occupy the porous spaces of the formations. Each of the measuring devices can be used to measure properties of the formations and / or its geological features. Although each acquisition tool is represented as being at specific locations in the oil field 200, it will be understood that one or more types of measurements may be taken at one or more locations on one or more fields or other locations for comparison and / or analysis. The data collected from various sources, such as the data acquisition tools of Figure 3, can then be processed and / or evaluated. Typically, the seismic data displayed on the static data plot 208. 1 of the data acquisition tool 202. 1 are used by a geophysicist to determine characteristics of underground formations and features. The core data displayed on static plot 208. 2 and 3034191 29469 / 290FRI and / or well logging data 208. 3 are generally used by a geologist to determine various characteristics of the underground formation. The production data of graph 208. 4 are generally used by the reservoir engineer to determine fluid flow characteristics of the reservoir. The data analyzed by the geologist, the geophysicist and the reservoir engineer can be analyzed using modeling techniques. Figure 4 illustrates an oil field 300 for performing production operations in accordance with the implementations of various technologies and techniques described herein. As indicated, the oilfield has a plurality of well locations 302 operably connected to a central processing facility 354. The configuration of the oil field in Figure 4 is not intended to limit the scope of the oil field application system. All or part of the oil field may be on land and / or at sea. Moreover, although a single oilfield with only one treatment plant and a plurality of well locations is shown, any combination of one or more oilfields, one or more treatment plants, and one or more well locations may be present. Each well location 302 has equipment that forms a wellbore 336 in the earth. Drilling wells extend through subterranean formations 306, including tanks 304. These tanks 304 contain fluids, such as hydrocarbons. The well locations extract the fluid from the reservoirs and convey it to the treatment facilities via surface networks 344. The surface networks 344 have tubes and control mechanisms for controlling the flow of fluids from the well location to the treatment facility 354. Determination of Formation Pressure [0065] In accordance with some embodiments, a formation pressure associated with a reservoir can be determined. Generally, a pressure derived response can be determined from the measurement data collected during a preliminary test of reservoir formation, and the formation pressure can be determined at least in part depending on the derived pressure response. By determining the formation pressure at least in part as a function of the pressure derived response determined from the measurement data, embodiments can solve wellbore condition problems, tool positioning problems, and data acquisition, permeability problems of formation, and / or other such factors which may give rise to difficulties in determining the formation pressure from the measurement data. FIG. 5 shows a block diagram 400 which illustrates a sequence of operations that can be performed by the data processing system 10 to determine a formation pressure associated with an oil and gas reservoir. [0066] FIG. according to some embodiments. As indicated, the data processing system 10 receives measurement data (block 402) collected from a formation of the reservoir. Generally, measurement data can be collected by a data acquisition tool positioned in a wellbore associated with the reservoir, such as a probe and / or cable tool. In addition, the measurement data is generally collected during one or more short tests called preliminary tests, the data acquisition tool collecting during such preliminary tests of time pressure data and / or other this guy for training. For a preliminary test, the measurement data over time can be analyzed to identify one or more events during the preliminary test. Events that can be identified in a preliminary test by analyzing the measurement data may include, for example, a mud event before, a start of fall event, a start up event, a last read event, and a mud event after . The data processing system 10 analyzes the measurement data to determine a last read event and a corresponding last read read pressure for the formation for the preliminary test (block 404). [0067] The data processing system determines derived data for flow regime identification based at least in part on the measurement data (block 406). In accordance with some embodiments, time pressure data from the measurement data may be analyzed to determine derived data that may be used for flow regime identification, such derived data may include derived data. spherical and / or radial derived data. The derived data generally indicates a rate of change of pressure with respect to a selected time function. The analysis of these derived data can be performed to identify different flow regimes associated with the fluid collected during the preliminary test. At different times during a preliminary test, a flow of fluid collected by the data acquisition tool varies. flow behavior that can be described as a flow regime. The flow regimes encountered by a data acquisition tool during a preliminary test may include a spherical flow regime, a hemispherical flow regime, a radial flow regime, a flow regime around an obstacle, and / or a strip flow regime with low permeability. In general, the identification of the flow regime at different times during the preliminary test includes the identification of characteristic patterns in the derived data. For example, during an ascent period for the data acquisition tool, a pressure disturbance from the data acquisition tool causes the fluid to flow in a spherical flow regime. . When the pressure disturbance encounters an impermeable barrier in the formation of the well, the spherical flow regime is changed to a hemispherical flow regime. When the pressure disturbance of the data acquisition tool encounters a second impermeable barrier (e.g. , a vertical barrier), the fluid flows in a radial flow regime. Therefore, the data processing system 10 analyzes the derived data to determine a pressure derived response for the preliminary test (block 408). Generally, the determination of the pressure derivative response for the preliminary test comprises identifying a portion of the preliminary test that corresponds to a spherical flow regime and / or identifying a portion of the preliminary test that corresponds to at a radial flow regime. Further, according to some embodiments, the determination of a pressure derived response may include determining a pressure as a function of a spherical time function based on the measurement data and / or determining a pressure as a function of a radial time function based on the measurement data. On the basis of the last read event, the last read pressure, and / or the pressure derivative response, the data processing system 10 determines the formation pressure corresponding to the reservoir (block 410). . In accordance with some embodiments, the data processing system 10 may determine that the last read pressure is an accurate measure of formation pressure. However, in some embodiments, depending on the pressure derived response, the data processing system 10 may determine that the last read pressure is not an accurate measure of formation pressure. The permeability of a formation, the positioning of the data acquisition tool with respect to the formation, the poor conditions of a wellbore, and / or other factors of this type can cause the pressure read last is not an accurate measure of training pressure. The data processing system 10 can analyze the pressure derivative response to adjust the last read pressure to improve the accuracy of the formation pressure determination. As will be understood, although block diagram 400 of FIG. 5 relates to the determination of a formation pressure from a preliminary test conducted by a data acquisition tool, modes of may generally collect measurement data from a plurality of data acquisition tools positioned at various depths of a wellbore associated with the reservoir (called positions) such that a 3034191 29469 / 290EN1 Formation pressure can be determined for each station and a formation pressure gradient can be determined. A formation pressure gradient generally corresponds to the formation pressure at various depths. Therefore, embodiments may determine a plurality of formation pressures for reservoir formation, the formation pressures being determinable at various depths (e.g. -to-d. stations) of a wellbore associated with the reservoir. FIG. 6 shows a schematic illustration of an example of a well 450 associated with a reservoir and of a data acquisition tool 452 in a wellbore 454 of the well 450, the acquisition tool of FIG. The data 452 is positioned such that the data acquisition tool 452 can perform a preliminary test on a formation 456 of the well 450. In this example, the data acquisition tool 452 collects a fluid from the formation 456 for the preliminary test and collects measurement data associated with the pressure and time during the preliminary test. As indicated, the fluid may flow from the formation 456 to the data acquisition tool 452 in a manner similar to the flow lines 458 illustrated in the example. Figure 7A shows a graph 480 illustrating measurement data of examples that can be collected during a preliminary test. In this example, the measurement data includes pressure data 482 collected during a period of time 484 of the preliminary test, and the measurement data further comprises a motor speed over time 486 for the data acquisition tool. . Figure 7B shows the example graph 480 of Figure 7A which includes annotations corresponding to the different events that may occur during a preliminary test according to some embodiments. In particular, FIG. 7B includes an annotation corresponding to a mud event before 490, a start of fall event 492, a start up event 494, an event read last 496, and a mud event after 498. As will be understood, in some embodiments, the last read event 496 can therefore be determined to correspond to a particular moment and pressure (called the last read pressure) by analyzing the pressure data in the time contained in the measurement data received. FIGS. 8A-8C show schematic illustrations of examples of fluid flow regimes of Examples 510-514 that may occur during a preliminary test of a formation 516 by a data acquisition tool 518. . Referring to Fig. 8A, a spherical flow regime 510 may occur during a rise period for the preliminary test. As indicated, a pressure disturbance by the data acquisition tool 518 causes the fluid of the formation 516 to propagate spherically until an impermeable barrier is reached. In some high permeability formations, a first impermeable barrier is reached so rapidly that the measurement data and pressure derivative data derived therefrom can not reflect a spherical flow regime in a derived response. pressure. In Fig. 8B, a first impermeable barrier of the formation 516 has been encountered by the pressure disturbance of the data acquisition tool 518, causing the fluid flow to pass at a hemispherical flow regime 512. In Fig. 8C, when or if a second impermeable barrier of formation 516 is reached by the pressure disturbance, the fluid flow regime changes from a hemispherical flow regime to a radial flow regime 514. Figure 9 shows a block diagram 550 which illustrates a sequence of operations that can be performed by the data processing system 10 to determine and analyze data derived from the measurement data 552 according to some embodiments. As indicated, depending on the measurement data and / or derived data 552, the data processing system identifies a portion of the preliminary test that corresponds to a spherical flow regime at least in part depending on the pressure derivative data. (block 554). As will be understood, the derived data may include spherical derived data and / or radial derived data, and a portion of the preliminary test corresponds to a spherical flow regime when the spherical derived data has a flat tendency (e.g. , a slope close to zero), while the radial derived data have a slope of approximately (- -2). Therefore, the data processing system 10 can identify at least a portion of the spherical derived data that has a flat tendency to thereby identify a portion of the preliminary test that corresponds to a spherical flow regime. The data processing system can identify a portion of the preliminary test that corresponds to a radial flow regime at least in part depending on the radial derived data (block 556). Generally, a portion of the preliminary test corresponds to a radial flow regime when the radial derivative data has a flat tendency (e.g. , a slope close to zero) and the spherical derived data have a slope of about (-21). Therefore, the data processing system 10 can identify a portion of the radial derived data having a flat tendency to thereby identify a portion of the preliminary test that corresponds to a radial flow regime. On the basis of the measurement data and / or the derived data, the data processing system 10 determines the pressure as a function of a spherical time function (block 558). In general, the spherical temporal function can be determined at least in part by the following equation: ## EQU3 ## , 17-F, where At = time elapsed since the beginning of the ascent,,. R = ratio of debn- of two preliminary tests, where R = 1 for a limited drop Q2 or a preliminary test, 5 t2 = flow time of the second preliminary test, t2 = 0 for a preliminary test, tp = production time total. In addition, if a spherical flow regime develops during a preliminary test, a plot of the pressure observed during the ascent (c. -to-d. fs (At)) can be likened to a line with a slope equal to m ,. In such embodiments, the spherical mobility can be estimated at least in part according to the following equation. ; 2 (2) (-k) sP = 1856 (31 (Oct) 3, where qi represents the flow rate of the first preliminary test. On the basis of the measurement data and / or the derived data, the data processing system 10 determines the pressure as a function of a radial time function (block 560). Generally, the radial time function can be determined at least in part according to the following equation: (3) f- (At) = logtp + ot R x log t, FAt + Itt tu [0077] Generally, a regime of Radial flow may develop during a preliminary test, and a plot of the pressure observed during ascent as a function of fi. (At) can be likened to a line with a slope equal to mr. In such embodiments; a total mobility-thickness product can be determined at least in part according to the following equation: (4) = 88,1562 ql g Imr1 [0078] As will also be understood, -k generally corresponds to the mobility of the fluid flowing since the training. On the basis of a spherical flow equation of a slightly compressible fluid in a homogeneous medium, a draw-off mobility (-k) d = (Cpf x -A), where Ap 'is the pressure drop in steady-state withdrawal, Cpf is a ps factor, withdrawal proportionality, and q is the flow rate of the preliminary test. Generally, the drawdown proportionality factor is based on a type of data acquisition tool used when conducting the preliminary test. For example, the draw-off proportionality factor for a normal / long-nozzle probe and a current packer may be 5660, the draw-off proportionality for a Martineau probe may be 6186, the draw-off proportionality for a 3034191 29469 probe. / 290FR1 21 large diameter can be 2395, the proportionality of withdrawal for a large X-ray probe can be 1556.5, the proportionality of withdrawal for a large area packer can be 1107, and / or the proportionality of withdrawal for a StethoScope data acquisition tool provided by Schlumberger Ltd. and its affiliates can be 4857 or 6266 depending on the model. In general, the draw mobility is based at least in part on a drawdown proportionality factor and a preliminary test chamber volume of a data acquisition tool. The draw-off mobility can be determined at least in part by the following equation: DDp f XV dat (5) Tapping mobility = where (dT XdP DDpf is the drawdown proportionality factor, 10 Vdat is the chamber volume of the data acquisition tool, Ti - dPi = pressure at the end of the ascent -, and E (dTi x dPi) is calculated for all the pressures lower than the final ascent pressure. In addition, the determination of a pressure derivative response for a preliminary test may include determining a spherical time function and determining a radial time function. The data processing system may analyze the pressure derivative response to identify a portion of the preliminary test corresponding to a spherical flow regime and / or a portion of the preliminary test corresponding to a radial flow regime. As will be understood, the determination of the pressure derivative response for the preliminary test may include identifying at least a portion of the preliminary test that corresponds to a spherical flow regime. In addition, the determination of the pressure derivative response for the preliminary test may include the identification of at least a portion of the preliminary test which corresponds to a radial flow regime. On the basis of the pressure derivative response, the data processing system 10 determines whether the last read pressure is accurate to determine the formation pressure (block 562). In general, if the portion corresponding to the spherical flow regime and the portion corresponding to the radial flow regime are identified, the pressure derivative response indicates that the last read pressure is accurate to determine the formation pressure. However, as previously discussed, an unsealed seal between the data acquisition tool and the formation, poor wellbore conditions, high permeability of the formation, and / or other conditions of this type can make that the fluid does not have a spherical flow regime and / or a radial flow regime. In turn, the pressure read last may not be accurate in determining the formation pressure. Therefore, in response to the determination that the last read pressure is accurate to determine the formation pressure ("0" branch of block 562), the data processing system 10 determines the formation pressure as the pressure read from last (block 564). In response to the determination that the last read pressure is not accurate in determining the formation pressure ("N" branch of block 562), the data processing system 10 adjusts the read last pressure (block 566). depending on the pressure derivative response to thereby determine the formation pressure (block 564). [0081] FIG. 10A shows an example graph 570 which illustrates pressure derived data which includes spherical derived data of Examples 572 (illustrated by a dashed line) and radial derived data of Examples 574 (illustrated in FIG. by a continuous line). As indicated, the spherical derived data exhibit a flat trend and the radial derived data show a slope of (- 12) during a portion of the preliminary test which displays a spherical flow regime 576, and the radial derived data show a tendency plate and the spherical derived data have a slope of () during a portion of the preliminary test that displays a radial flow regime 578. Figure 10B shows a graph 580 which includes data derived from examples that can be determined from collected measurement data, including spherical derived data and radial derived data. Figure 10C shows an example graph 582 which shows the pressure plotted against a spherical time function (e.g. a spherical time function), and FIG. 10D shows an example graph 584 which represents the pressure plotted against a radial time function (e.g. , a radial temporal function). The slope of a right section of the spherical time function of FIG. 10C and the slope of a right section of the radial time function can be analyzed to determine reservoir and / or formation characteristics, such as spherical mobility, a radial mobility-thickness product, and / or extrapolated pressure at a well closure at infinity. As will be understood, the right hand sections illustrated in FIGS. 10C and 10D correspond to portions of the derived data curves that have a horizontal line (e.g. , the spherical flow regime 576 and the radial flow regime 578 of Figure 10A). Fig. 10E shows an exemplary graph 586 which illustrates the relationship between the draw mobility 588 and a time pressure plot for measurement data that can be collected in accordance with some embodiments. Figure 11A shows a schematic illustration of a well 600 with a data acquisition tool 602 positioned to perform one or more preliminary tests on a formation 604 of the well 600. In this particular example, the data acquisition tool 602 forms a seal with the formation 604. Fig. 11A further includes an exemplary graph 606 which illustrates an exemplary pressure derivative response for an exemplary preliminary test having radial derived data 608 and spherical derived data 610.
[0004] In addition, Fig. 11A includes an example graph 612 which illustrates sample measurement data for the exemplary preliminary test and annotates a last read pressure 614. In this example, the measurement data and the response Pressure derivative indicates that the pressure read last is accurate to determine the formation pressure. FIG. 11B shows a schematic illustration of a well 650 with a data acquisition tool 652 positioned to carry out one or more preliminary tests on a formation 654 of the well 650. In this particular example, the tool of FIG. Data acquisition 652 forms an unsealed seal with the formation 654, so that a pressure leak can develop, which draws the fluid from the borehole of the well 650. Figure 11B further includes a graph of Example 656 which illustrates an exemplary pressure derivative response for an exemplary preliminary test having radial derived data 658 and spherical derived data 660. In this example, the leaky seal caused the radial derived data and the spherical derived data have different characteristics with respect to graph 606 of Fig. 11A. In particular, an annotated region 662 indicates a point at which the pressure derivative response may be affected by the unsealed seal. In addition, Fig. 11B includes an example graph 664 which illustrates sample measurement data for the exemplary preliminary test and annotates a last read pressure 666. In this example, as discussed, the seal is unsealed. of the data acquisition tool 652 leads to a last read pressure 666 which is not accurate to determine the formation pressure. In accordance with embodiments, the annotated region 662 indicates that the last read pressure is not accurate to determine the formation pressure. Therefore, as shown in FIG. 11B, a formation pressure 668 is determined as a function of the last read pressure 666 and the pressure derivative response. In particular, in FIG. 11B, the formation pressure 668 is determined as a function of the point at which the pressure derivative response indicated that the fluid flow was not characteristic for the preliminary test (e.g. prominently 30,662). In general, although the description is provided relative to a preliminary test and the determination of a formation pressure, the embodiments are not limited thereto. As will be understood, for a reservoir and / or reservoir formation, one or more of the data acquisition tools may be positioned at different stations in a wellbore and configured to perform one or more tests. preliminary. A respective data acquisition tool can perform one or more preliminary tests and a training pressure can be determined for each preliminary test. Similarly, several data acquisition tools may perform one or more preliminary tests on one or more formations at different stations in a wellbore of the reservoir, and a formation pressure may be determined for each position. Therefore, embodiments may determine a plurality of formation pressures for reservoir formation, such pressures generally corresponding to different stations (eg, depths), so that the formation may be analyzed according to training pressure at each station. [0085] Fig. 12 shows a schematic illustration of an exemplary graphical user interface 700 that can be generated by the data processing system 10 and displayed through a user interface. In this example, pressure data collected for a pre-test is displayed in a graph 702 which has pressure values 704 as a function of time 706. In addition, the example graph 702 includes engine speed data. preliminary test 708, engine direction data positioning tool 710 (a negative direction indicates that the data acquisition tool is against a formation and a positive direction indicates that the data acquisition tool is withdrawing of training), and preliminary test volume data 712 contained in the received measurement data. In this example, the measurement data comprises pressure data collected from intervals (the intervals being designated A, B, C, D, E, and F) of a preliminary test performed by an acquisition tool. of data. As indicated, in the interval A, a slurry event before 718 occurs after the data acquisition tool is positioned to perform a preliminary test, as indicated by the engine speed of the piston 708. In FIG. the interval B, a start of falling event 720 occurs, as indicated by the speed of the piston engine 708, the direction of the engine 710, and an increase in the volume of the preliminary test 714. An early start event 722 is produced in the interval C, as indicated by the speed of the piston motor 708 and an increase in the volume of the preliminary test 714. In the interval D, a pressure read last 724 for a portion of the preliminary test study is present, and simultaneously, a start-of-fall event 725 for a final portion of the preliminary test occurs, as indicated by the speed of the piston motor 708 and an increase in the volume of the preliminary test 714. In the interval E, a event d The start time 726 for a final portion of the preliminary test occurs, as indicated by the speed of the piston motor 708 and an increase in the volume of the preliminary test 714. In the interval F, an event read last occurs for a second time. final portion of the preliminary test, as indicated by the speed of the piston engine 708, the direction of the engine 710, and a decrease in the volume of the preliminary test 714. In the interval G, a sludge event after produced after the data acquisition tool has withdrawn from a well-forming wall, as indicated by the speed of the piston motor 708 and the direction of the positioning motor 710. [0086] FIG. 13 shows a schematic illustration of an exemplary graphical user interface 750 that can be generated by the data processing system 10 and displayed through a user interface. In this example, the graphical user interface 750 includes a graph 752 which includes derived data based on the measurement data shown in Fig. 12. In particular, graph 752 includes derived data for the identification of the speed regime. flow associated with the spherical derived data 754 and the radial derived data 756 as a function of time (in this case a time variation for the preliminary test). As will be understood, the spherical derived data 754 and the radial derived data 756 indicate a portion of the preliminary test which reveals a spherical flow regime 758 and a portion of the preliminary test which reveals a radial flow regime 760. [0087 Figure 14 shows a schematic illustration of an exemplary graphical user interface 800 that can be generated by the data processing system 10 and displayed through a user interface. The graphical user interface includes a graph 802 which includes time pressure data 804 from measurement data collected by a data acquisition tool. In this example, a seal of the data acquisition tool 20 seems poorly secured and / or leakproof, so that an event read last 806 and a corresponding last read pressure can not be accurate to determine a training pressure. FIG. 15 shows a schematic illustration of an example graphical user interface 820 which includes derived data based on the measurement data of FIG. 14. In particular, the graphical user interface 820 includes a graph 822 which includes Spherical Derived Data 824 and Radial Derived Data 826. In this example, because of the unsealed and / or poorly secured seal, at a time of 11.1 seconds from the time of the start up event 828, the response Pressure derivative for the preliminary test is not a derived pressure response associated with the formation. As shown in FIG. 15, the fluid has a spherical flow regime 830; however, a radial flow regime does not appear due to the non-formation response. [0088] Fig. 16 shows a schematic illustration of an exemplary graphical user interface 840 that can be generated by the data processing system 10 and displayed through a user interface. The graphical user interface 840 includes a graph 842 which is similar to the graph 802 of Fig. 14. However, in this example, a last read event 844 has been adjusted according to the derived pressure response of Fig. 15. As indicated, the last read event was adjusted to be 11.1 seconds after a start up event 846 due to the pressure derived response analyzed in Fig. 15. Fig. 17 shows a schematic illustration of an example graphical user interface 860 that can be generated by the data processing system 10 and displayed through a user interface. Graphical user interface 860 includes a graph 862 that includes pressure gradient information 864. In this example, pressure gradient information 864 includes formation pressures determined for well formation at different depths. In particular, the pressure gradient information 864 illustrates the formation pressure 866 determined as a function of the last read event shown in Fig. 14 and the formation pressure 868 determined in Fig. 16 (i.e. the formation pressure determined according to the event read last adjusted from Figure 16). Figures 18A-C show schematic illustrations of exemplary user graphical interfaces 900, 902, 904 that can be generated by the data processing system 10 and displayed through a user interface. In Fig. 18A, the graphical user interface 900 includes a graph 906 which includes pressure data 908 collected by a data acquisition probe. As indicated, an event read last 910 can be determined from the measurement data. The graphical user interface 902 of Fig. 18B includes a first graph 912 which includes radial derived data and a second graph 914 which includes spherical derived data. A graphic user interface region 918 corresponds to portions of the graphs 912, 914 which indicate that the pressure derivative response for the preliminary test is not a pressure derived response associated with the formation - that is, a Data acquisition probe 25 seal may be loose, formation may be highly permeable, and / or other conditions of the formation / well bore may have affected the performance of the preliminary test and / or collection of measurement data by the data acquisition tool. The graphical user interface 904 of Figure 18C includes a graph 920 which provides formation pressure gradient information for well formation at various depths. In this example, a formation pressure 922 determined from the last read event 910 of FIG. 18A is shown. As indicated, the determined formation pressure 922 does not align with other formation pressures determined for other depths. As will be understood, the pressure derivative response illustrated in Fig. 18B indicates that the last read event 910 of Fig. 18A is not accurate in determining a formation pressure. Figures 19A-B show schematic illustrations of graphical user interfaces of Examples 940, 942 that can be generated by the data processing system 10 and displayed through a user interface. In Fig. 19A, the graphical user interface 940 includes a graph 944 which includes time pressure data 946 which is similar to the time pressure data of Fig. 18A. In this example, at least in part based on the pressure derivative response, the last read event 910 of Fig. 18A has been adjusted to a last adjusted read event 948 of Fig. 19A. As shown in Fig. 19B, the graphical user interface 942 includes a graph 950 which includes formation pressure gradient information (i.e. formation pressure as a function of depth). As indicated, on the basis of the event read last adjusted 948, the formation pressure 952 determined from the event read last adjusted 948 corresponds to the other formation pressures measured for the formation. [0091] FIG. 20A shows an exemplary graph 1000 which illustrates a pressure derivative response for a preliminary test that includes a portion that reveals a spherical flow regime and a portion that reveals a radial flow regime. Fig. 20B shows an example graph 1010 which illustrates a pressure derivative response for a preliminary test in which the high permeability of a formation causes a pressure decrease. In such scenarios, an event read last will not be accurate to determine the formation pressure, but a final well closing event and a corresponding well closing pressure may be used to determine the formation pressure. Fig. 20C shows an example graph 1020 which illustrates a pressure derived response for a preliminary test in which the high permeability and / or instability of a formation induces a sinuous appearance. In such scenarios, a linear adjustment of the time function plots can be used to determine the formation pressure. Figure 20D shows an example graph 1030 which illustrates a pressure derivative response for a preliminary test in which the high permeability of a formation causes the occurrence of a radial flow regime. Figure 20E shows an example graph 1040 that illustrates a pressure derived response for a preliminary test in which the permeability of a formation induces instability of the derived data. In such scenarios, a linear fit can be used to extrapolate pressures, and a formation pressure can be estimated based on the extrapolated pressures. Fig. 20F shows an example graph 1050 which illustrates a pressure derived response for a preliminary test in which the permeability of a formation is correct, but horizontal boundaries are not encountered, so that a regime of radial flow 3034191 29469 / 290EN1 28 does not appear. Fig. 20G shows an example graph 1060 which illustrates a pressure derived response for a preliminary test wherein the permeability of a formation is such that a spherical flow regime does not occur. Fig. 20H shows an example graph 1070 which illustrates a pressure derived response for a preliminary test in which low permeability caused insufficient development or recovery was stopped prematurely. Therefore, according to some embodiments, a formation pressure for formation of an oil and gas reservoir can be determined at least in part as a function of a last read event, a pressure read last, and / or a pressure derived response. Generally, the analysis of the pressure derivative response can indicate whether a last read pressure is accurate to determine the formation pressure. In addition, embodiments may adjust a last read event and the corresponding last read last at least in part as a function of the pressure derivative response to thereby facilitate the determination of a precise formation pressure. As will be understood, the formation pressures determined at different depths of a wellbore associated with the reservoir can be analyzed to determine a formation pressure gradient for reservoir formation. Although particular embodiments have been described, it is not envisaged that the embodiments are limited, because it is understood that the embodiments have a scope as wide as the technique allows, and that the specification must be read accordingly. Therefore, those skilled in the art will appreciate that further modifications could be made without departing from their spirit and scope as claimed.

权利要求:
Claims (20)
[0001]
REVENDICATIONS1. A method of determining a formation pressure for a reservoir, the method comprising: receiving (400) measurement data for a preliminary test of reservoir formation from a data acquisition tool; analyzing, with at least one processor of a data processing system, measurement data for determining (404) a last-read event and a corresponding last-read pressure for the preliminary test; determining (406), with the at least one processor, derived data for flow regime identification based at least in part on the measurement data; analyzing, with the at least one processor, derived data to determine (408) a pressure derivative response; and determining (410), with the at least one processor, the formation pressure for the formation at least in part depending on the last read event, the last read pressure, and the response derived from pressure.
[0002]
The method of claim 1, wherein determining the derived data comprises: determining spherical derived data from the measurement data, the pressure derived response being determined at least in part based on the spherical derived data.
[0003]
The method of claim 2, wherein analyzing the derived data to determine the pressure derivative response comprises analyzing the spherical derived data to identify a portion of the preliminary test corresponding to a spherical flow regime, and the pressure of formation for the formation is determined at least in part according to the portion of the preliminary test corresponding to the spherical flow regime.
[0004]
The method of claim 1, wherein determining the derived data comprises: determining radial derived data from the measurement data, the derived pressure response being determined based on the derived radial data. 3034191 29469 / 290FRI 30
[0005]
The method of claim 4, wherein analyzing the derived data to determine the pressure derived response comprises analyzing the radial derived data to identify a portion of the preliminary test corresponding to a radial flow regime, and formation pressure is determined at least in part according to the portion of the preliminary test corresponding to the radial flow regime.
[0006]
The method of claim 1, wherein the derived data comprises spherical derived data and radial derived data, the analysis of the derived data to determine the pressure derived response comprises analyzing the spherical derived data to identify a first portion of the preliminary test that corresponds to a spherical flow regime, analysis of the derived data to determine the pressure derivative response includes analysis of the radial derivative data to identify a second portion of the preliminary test that corresponds to a regime of radial flow, and the pressure derivative response is determined at least in part as a function of the first portion and the second portion.
[0007]
The method of claim 6, wherein the determination of formation pressure for formation comprises: a pressure adjustment read last at least in part depending on the pressure derivative response to thereby determine the formation pressure .
[0008]
The method of claim 7, further comprising: determining whether the last read pressure is accurate to determine the formation pressure at least in part depending on the pressure derived response, the pressure adjustment. read last at least in part depending on the pressure derivative response to thereby determine the formation pressure being made in response to the determination that the last read pressure is not accurate to determine the formation pressure.
[0009]
The method of claim 1, further comprising: determining a formation pressure gradient for the formation at least in part as a function of the formation pressure.
[0010]
The method of claim 1, wherein analyzing the derived data to determine the pressure derivative response comprises: analyzing the derived data to determine whether a spherical flow regime is revealed during the preliminary test. ; and analyzing the derived data to determine if a radial flow regime is revealed during the preliminary test, wherein the formation pressure is determined at least in part depending on whether the preliminary test reveals the spherical flow regime , and the formation pressure is determined at least in part depending on whether the preliminary test reveals the radial flow regime. 10
[0011]
The method of claim 1, wherein analyzing the derived data to determine the pressure derived response comprises: determining a spherical time function and a radial time function based on the derived data and measurement data. wherein the formation pressure is determined at least in part as a function of the spherical time function and the radial time function.
[0012]
A data processing system (10), comprising: at least one processor (16); a memory (18) coupled to the at least one processor; and a program code stored in the memory and configured to be executed by the at least one processor to cause the at least one processor to: receive measurement data for a preliminary test of a formation of a reservoir; from a data acquisition tool; analyzing the measurement data to determine a last read event and a corresponding last read last read for the preliminary test; determining derived data for flow regime identification based at least in part on the measurement data; analyzing the derived data to determine a pressure derivative response for the preliminary test; and determining a formation pressure for the formation at least in part as a function of the last read event, the last read pressure, and the pressure derivative response.
[0013]
The data processing system according to claim 12, wherein the derived data is determined by determining spherical derived data from the measurement data, the pressure derivative response being determined at least in part by function of spherical derived data. 5
[0014]
The data processing system of claim 13, wherein the derived data is analyzed to determine the pressure derived response: analyzing the spherical derived data to identify a portion of the preliminary test corresponding to a spherical flow regime, and the formation pressure is determined at least in part according to the portion of the preliminary test corresponding to the spherical flow regime.
[0015]
The data processing system of claim 12, wherein the derived data is determined by determining radial derived data from the measurement data, the derived pressure response being determined based on the radial derived data.
[0016]
The data processing system of claim 15, wherein the derived data is analyzed to determine the pressure derivative response: by analyzing the radial derived data to identify a portion of the preliminary test corresponding to a radial flow regime, and the formation pressure is determined at least in part according to the portion of the preliminary test corresponding to the radial flow regime. 25
[0017]
The data processing system of claim 12, wherein the derived data comprises spherical derived data and radial derived data, the derived data is analyzed to determine the pressure derivative response by analyzing the spherical derived data to identify a first As a portion of the preliminary test that corresponds to a spherical flow regime, the derived data is analyzed to determine the pressure derivative response by analyzing the radial derivative data to identify a second portion of the preliminary test that corresponds to a radial flow regime. and the derived pressure response is determined at least in part as a function of the first portion and the second portion. 3034191 29469 / 290EN I 33
[0018]
The data processing system according to claim 17, wherein the formation pressure for the formation is determined by adjusting the pressure read last at least in part according to the pressure derivative response to thereby determine the formation pressure. . 5
[0019]
The data processing system of claim 18, wherein the program code is further configured at runtime to cause the at least one processor to: determine if the last read pressure is accurate to determine the pressure of the at least in part depending on the pressure derivative response, the last read pressure being adjusted at least in part according to the pressure derivative response to thereby determine the formation pressure in response to the determination that the pressure read last is not precise to determine the formation pressure.
[0020]
A computer program product comprising: a computer readable storage medium; and program code stored on the computer readable storage medium and configured, at runtime, to cause at least one processor to: receive measurement data for a preliminary test of a formation of a reservoir from a data acquisition tool; Analyzing the measurement data to determine an event read last and a corresponding last read pressure for the preliminary test; determining derived data for flow regime identification based at least in part on the measurement data; analyzing the derived data to determine a pressure derivative response for the preliminary test; and determining a formation pressure for the formation at least in part as a function of the last read event, the last read pressure, and the pressure derivative response.

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同族专利:

公开号 | 公开日

US20180023389A1|2018-01-25|

US10655461B2|2020-05-19|

EP3274552A1|2018-01-31|

WO2016153754A1|2016-09-29|

FR3034191B1|2019-08-23|

EP3274552A4|2019-01-02|

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US20040133350A1|2003-01-08|2004-07-08|Schlumberger Technology Corporation|Digital pressure derivative method and program storage device|

US20060241867A1|2005-04-26|2006-10-26|Fikri Kuchuk|System and methods of characterizing a hydrocarbon reservoir|

US20100274490A1|2009-04-24|2010-10-28|Schlumberger Technology Corporation|Thickness-independent computation of horizontal and vertical permeability|FR3062737A1|2017-02-06|2018-08-10|Services Petroliers Schlumberger|US4797821A|1987-04-02|1989-01-10|Halliburton Company|Method of analyzing naturally fractured reservoirs|

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WO2011043764A1|2009-10-05|2011-04-14|Halliburton Energy Services, Inc.|Integrated geomechanics determinations and wellbore pressure control|

US8899349B2|2011-07-22|2014-12-02|Schlumberger Technology Corporation|Methods for determining formation strength of a wellbore|

CA2899144A1|2013-01-31|2014-08-07|Schlumberger Canada Limited|Methods for analyzing formation tester pretest data|NL2017006B1|2016-06-20|2018-01-04|Fugro N V|a method, a system, and a computer program product for determining soil properties|

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2016-09-30| PLSC| Publication of the preliminary search report|Effective date: 20160930 |

2017-03-27| PLFP| Fee payment|Year of fee payment: 3 |

2018-03-29| PLFP| Fee payment|Year of fee payment: 4 |

2019-02-13| PLFP| Fee payment|Year of fee payment: 5 |

2020-02-14| PLFP| Fee payment|Year of fee payment: 6 |

2021-02-10| PLFP| Fee payment|Year of fee payment: 7 |

2022-02-10| PLFP| Fee payment|Year of fee payment: 8 |

优先权:

申请号 | 申请日 | 专利标题

FR1552355|2015-03-23|

FR1552355A|FR3034191B1|2015-03-23|2015-03-23|DETERMINATION OF TRAINING PRESSURE|FR1552355A| FR3034191B1|2015-03-23|2015-03-23|DETERMINATION OF TRAINING PRESSURE|

PCT/US2016/020546| WO2016153754A1|2015-03-23|2016-03-03|Formation pressure determination|

US15/546,007| US10655461B2|2015-03-23|2016-03-03|Formation pressure determination|

EP16769294.6A| EP3274552A4|2015-03-23|2016-03-03|Formation pressure determination|

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