• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    apparatus and method for assessing the quality of downhole data the present invention relates to a method for assessing the quality of a downhole data that is provided. the method, according to a modality, may include defining a quality criterion based on one or more parameters of interest, determining a quality assessment value for a first data, determining a quality assessment value for each drilling of a plurality perforations using the quality criterion, determine a quality factor from the computed quality assessment values of the plurality of perforations, and determine a quality level of the first data using the quality assessment value of the first data and the quality of computed quality assessment values.
    公开号:BR112012002473B1
    申请号:R112012002473
    申请日:2010-08-03
    公开日:2020-01-21
    发明作者:Baule Ansgar；Oleg Akimov；Hartmann Andreas；Fulda Christian
    申请人:Baker Hughes Inc；
    IPC主号:
    专利说明:

    [0001] This order claims priority for the provisional order
    61 / 230,907 filed on August 3, 2009.
    Field of the Invention [0002] The invention in this document relates generally to apparatus and methods for estimating downhole data quality.
    2. Related Art Background [0003] Oil wells (also referred to in this document as well boreholes) are drilled to recover hydrocarbons (oil and gas) from underground formations. A drill string containing a drill pipe carrying a drill assembly (also referred to as a downhole assembly or BHA) is used to drill the well hole. BHA typically includes a large number of sensors that measure a variety of parameters relating to the formation or the drilling environment. Such sensors typically include resistivity sensors, gamma ray sensors, nuclear sensors, acoustic sensors, nuclear magnetic resonance sensors, formation test sensors, sensors for estimating inclination, azimuth, etc. BHA also includes one or more processors to process downhole measurements and transmit selected information in real time relating to formation and other parameters to the surface via a telemetry unit. The telemetry method most often used is mud pulse telemetry, in which signals are transmitted through the drilling fluid (or mud) circulating through the drilling column. Such telemetry methods are capable of transmitting
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    2/21 only a few pulses per minute. Therefore, a large amount of downhole data is often stored on one or more data storage devices (such as a solid state memory device) and only certain results obtained from such data are transmitted in real time to the surface. . The data stored in the downhole memory device (memory data) is recovered when the drilling column is removed from the well hole and processed to estimate the various properties of interest and to generate images of one or more parameters. The quality level of downhole data or images obtained from such data is assessed after drilling is completed. The evaluation of the quality of such data or images is usually subjective. Therefore, it is desirable to provide apparatus and methods for objectively assessing the level of quality of data in real time and of data retrieved from memory.
    Summary of the Invention [0004] In one aspect, a method for assessing downhole data quality is provided. The method, according to one modality, may include: defining one or more quality parameters or quality indicators; define a quality criterion based on one or more quality parameters; determine a quality assessment value for a first piece of data corresponding to the quality criterion; obtaining a second set of data from a plurality of well holes (drilling); determine a quality assessment value for each drilling corresponding to the quality criterion; determine a quality factor from the quality assessment values computed from the plurality of perforations; and determining a quality level of the first data using the quality assessment value for the first data and the quality factor of the computed quality assessment values.
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    3/21 [0005] In another aspect, a computer-readable medium accessible by a processor is provided. The computer-readable media, in one aspect, may have a computer program embedded in it that includes instructions for: accessing downhole data corresponding to a plurality of well holes (perforations) defining a base data; access a quality criterion based on one or more quality parameters; compute a quality assessment value for each drilling corresponding to the quality criterion; determine a quality factor from the quality assessment values computed for the plurality of perforations; access a result data; determine a quality assessment value of the result data corresponding to the quality criterion; and determining a quality level of the result data using the quality assessment value of the result data and the quality factor.
    [0006] Examples of certain features of the device and method for assessing data quality have been summarized rather than widely described so that the following detailed description can be better understood. There are, of course, additional features of the apparatus and method disclosed below that will form the subject of the claims made under this invention. Brief Description of the Drawings [0007] The illustrative modalities and their advantages will be better understood when referring to the detailed description below and the attached drawings, in which:
    [0008] figure 1 shows a schematic diagram of a drilling system that can be used to obtain downhole data for a set of drilling and / or to perform a quality assessment on real-time data while drilling a hole well according to an embodiment of the invention;
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    4/21 [0009] figure 2 is a flowchart illustrating an exemplary method for determining a quality level of a first downhole data set in relation to a data quality level of several wells or drilling or a subset corresponding to the selected quality criteria;
    [0010] figure 3 is a flow chart illustrating an exemplary method for determining a quality level of a downhole data set in real time in relation to a memory data corresponding to a selected quality criterion; and [0011] figure 4 is a functional block diagram illustrating an exemplary processor configured to implement the methods described in this invention.
    Description of Illustrative Modalities [0012] A large number of sensors are used to estimate a variety of formation parameters and others during the execution of a well hole. Such sensors, referred to in general in this document as the measurement sensors during drilling (MWD) or profiling sensors during drilling (LWD), typically form a part of a drilling assembly (also referred to as a bottom mounting of well or BHA) and are used to obtain a variety of downhole measurements when drilling well holes. Downhole measurements made by such sensors are processed by a processor at BHA for use in estimating one or more properties of the well formation and borehole. Such sensors typically include: resistivity sensors, nuclear sensors, acoustic sensors, nuclear magnetic resonance sensors, formation test sensors, etc. Part of the processed data (referred to in this document as real-time data) is transmitted from the BHA to the surface during the drilling of the well. A large amount of data
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    Processed 5/21 is stored on a data storage device, such as a memory device. Data from the memory device is retrieved and processed after the BHA has been removed from the well hole. Data from different wells or boreholes are often stored in the form of profiles or images. [0013] The invention in this document, in general, provides apparatus and methods for evaluating the quality of a data in real time, a drilling data or data of several perforations relative to another data, which can be data of a particular drilling or several other perforations. In one aspect, the invention provides apparatus and methods for assessing the quality of a first data (also referred to as the result data) in relation to the quality of a second data (also referred to as the base data) using a selected quality criterion. In one aspect, to determine the quality level of a particular outcome data, one or more quality parameters or quality indicators can be specified. A quality assessment value for each data set in the base data (ie, data set corresponding to all drilling data) is calculated using the selected quality criterion. A quality factor for the total baseline data, which can be a statistical measure obtained from the various quality assessment values, is calculated. A quality assessment value of the result data is calculated using the selected quality criterion. The quality level of the outcome data in relation to the quality factor for the base data set can then be determined using the quality assessment value of the outcome data and the quality factor of the base data. A detailed exemplary process for determining the quality level of a result data is described with reference to figures 1-4. [0014] Figure 1 is a schematic diagram of a system of
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    6/21 exemplary drilling 100 that can be used to obtain drilling data for well holes, to provide real-time data during the execution of a well hole and / or to process data to determine a real-time data quality level according to one aspect of the invention. Figure 1 shows a drilling column 120 that includes a drilling assembly or downhole assembly (BHA) 190 carried within a wellhole 126. The drilling system 100 includes a drilling tower 111 mounted on a platform or floor 112 that supports a rotary table 114 that can be rotated by a driving machine, such as an electric motor (not shown), at a desired rotational speed. A pipe 122 (such as a joined drill pipe), having the drill assembly 190 attached to its lower end, extends from the surface to the bottom 151 of the well hole 126. A drill bit 150 attached to the drill assembly 190 disintegrates geological formations when it is rotated to make borehole 126. Drill column 120 is coupled to a main winch 130 by means of a swivel drill column connection assembly gasket 121, swivel 128 and swivel cable 129 through a pulley. The main winch 130 is operated to control the weight on the bit (WOB). Drill column 120 can be rotated by a top drive (not shown) instead of rotating rotary table 114. Alternatively, a continuous flexible tubing can be used like tubing 122. A tubing injector 114a can be used to transport the continuous flexible tubing and the BHA into the well hole 126. In some applications, the drill bit 150 is turned by just turning the pipe 122. However, in other applications a downhole motor 155 (mud motor) arranged in the drill assembly 190 can be used to rotate the drill bit 150.
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    7/21 [0015] A suitable drilling fluid 131 (also referred to as mud) from a source 132 thereof, such as a mud pit, is circulated under pressure through the drilling column 120 by means of a mud pump. 134. The drilling fluid 131 passes through the mud pump 134 into the drilling column 120 through a pulsation or irregularity damper 136 and a fluid line 138. The drilling fluid 131 discharges into the wellbore bottom 151 through the openings in the drill bit 150. The drilling fluid 131 carrying the drilling chips 186 returns to the mud pit 132 through the annular space 127 (between the drill column 120 and the well hole 126), of the return 135 and the drill sieve 185. The drill sieve 185 removes the drill cuttings 186 from the return drilling fluid. A Si sensor in line 138 provides information regarding the fluid flow rate. A surface torque sensor S2 and a sensor S3 associated with the drill column 120 provide information about the torque and rotational speed of the drill column 120 respectively. The pipe injection speed is determined by the sensor S5, while the sensor S6 provides the hook load of drill column 120.
    [0016] A control unit or surface controller 140 receives signals from sensors and downhole devices (described later) through a sensor 143 placed in fluid line 138 and signals from sensors S1-S6 and other sensors used in system 100 and processes such signals according to programmed instructions provided for surface control unit 140. Surface control unit 140 displays drilling parameters and other desired information on a display 148 which is used by an operator to control drilling operations. The surface control unit 140 can be a unit based on
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    8/21 computer which, in one aspect, may include a processor 142 (such as a microprocessor), a storage device 144 (such as a solid-state memory, tape or hard drive), and one or more computer programs 146 accessible by processor 142 to execute instructions contained in such programs. The surface control unit 140 can additionally communicate with a remote control unit 147. The surface control unit 140, in one aspect, can process downhole and surface data to determine the quality level of a data in real time, provide images, control one or more sensors in the BHA and control one or more drilling operations.
    [0017] BHA 190, in aspects, can include a variety of sensors or formation assessment devices (also referred to as measurement sensors during drilling (MWD) or profiling sensors during drilling (LWD)) to determine various properties of the formation, including, but not limited to, resistivity, density, porosity, permeability, acoustic properties, nuclear magnetic resonance properties, rock properties, well-bottom fluid properties and other desired properties of the 195 formation surrounding the BHA assembly 190. Such sensors can typically include, but are not limited to, resistivity sensors, nuclear sensors, acoustic sensors, nuclear magnetic sensors and formation evaluation sensors. For convenience, such sensors are collectively designated by the number 165. BHA 190 may additionally include a variety of other sensors and devices (collectively referred to herein as number 160) to determine one or more properties of BHA 190, (including, but not limited to bending moment, acceleration, oscillations, turning, discontinuous advance, etc.) and drilling operation parameters, such as
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    9/21 as weight on the bit, fluid flow rate, pressure, temperature, penetration rate, azimuth, tool face and drill bit rotation.
    [0018] BHA 190 also includes a power generation unit 178 that supplies electrical power to sensors 160 and 165 and other electrical circuits and devices in BHA 190. A telemetry unit 180 on drill column 120 establishes bidirectional communication between BHA 190 and surface controller 140. Power generating unit 178 may be any suitable device, including, but not limited to, a turbine operated by drilling fluid 131 flowing through BHA 190 that drives an alternator (not shown). The telemetry unit 180 can be any suitable unit, including a mud pulse telemetry unit, an electromagnetic wave propagation unit, an acoustic telemetry unit and a wired tube telemetry system. The drill assembly 190 additionally includes a downhole controller 170, which may additionally include a processor 172, such as a microprocessor, a data storage device (or computer-readable media) 174, data and algorithms and computer programs 176. Data storage device 174 may be any suitable device, including, but not limited to, read-only memory (ROM), random access memory (RAM), flash memory and hard disk.
    [0019] During drilling operations, controller 170 receives data from sensors 160 and 165, processes such data, transmits part of the data in real time (real time data) to the surface through the telemetry unit 180 and stores other data in the downhole storage device 174 (memory data). In one aspect, the downhole controller 170 can determine the level of
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    10/21 real-time data quality and provide such information to surface controller 140. In another aspect, downhole controller 170 can determine a quality level of real-time data or memory data such as described in more detail with reference to figures 2-4. In another aspect, memory data can be recovered when BHA 190 is pulled out of well hole 126. Drilling data from various perforations can be stored on the surface and used by a computer system to determine the quality level. of one or more drilling data in relation to data from various drilling, as described in more detail with reference to figures 2-
    4.
    [0020] Figure 2 is a flow chart illustrating an exemplary method
    200 that can be used to determine a quality level (or a quality assessment) of a drilling data or a particular memory data in relation to a base data constituting data from different perforations corresponding to a selected quality criterion. In one aspect, one or more quality parameters (also referred to in this document as quality indicators) Q1-Qm (201) are defined for use in method 200 (BOX 240). A quality criterion (202) is then selected using one or more quality parameters Q1-Qm (BOX 250). Examples of quality parameters and quality criteria may include, but are not limited to: (a) cuttings - a sudden change from a single pixel color in the image to a maximum / minimum value can be a quality parameter and the density of the piles by a defined depth (for example, a well hole extension or a research azimuth well hole depth) can be the quality criterion; (b) bands in the image - darkening of visible colors on the underside of the well hole can be the parameter of
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    11/21 quality and the fraction of the borehole affected by strips can be used as the quality criterion; (c) a sudden change in the color of all sectors of the image can be the quality parameter and the number of sudden changes by a selected well hole depth can be used as a quality criterion; (d) identification of intervals - intervals in a data set, which occur in real time because of communications problems, or in memory data because of problems related to the downhole tool getting measurements and problems with the designation of time and depth, can be a quality parameter and a measure of the intervals (such as the number of intervals or percentage of data in the intervals, etc.) by a selected depth interval can be used as a quality criterion; (e) truncations sometimes caused by problems of time and depth can be a quality parameter and the density of the truncations can be used as a quality criterion; and (f) a qualitative parameter, such as comments from educated people (customers, drilling rig operators, etc.) or a subjective scale of degrees. In other respects, quality criterion 202 may be based on or derived from more than one quality parameter. The use of such quality parameters results in a defined set of quantitative indicators, each such indicator producing a single value per analyzed data set or a statistical value (such as an average value plus a standard deviation). Also, a classification algorithm can be defined based on such quantitative indicators for use in determining the quality level of the result data.
    [0021] A base data set 204 is then selected corresponding to the various Ri-Rn perforations (Block 252). A QAV quality assessment value (206) for each drilling (Ri-Rn) in the
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    12/21 base data is then calculated (Block 254) corresponding to the selected quality criterion. For example, if the quality parameter or indicator is intervals and the quality criterion is the number of intervals per unit of depth, then for each drilling the QAV will be the number of intervals per unit of depth. Such values of quality evaluation are denoted by QAVRi-QAVRn for the Ri-Rn perforations respectively, whose values can be stored in a data storage device. Using the QAVRi-QAVRn quality assessment values, a QF quality factor (208) is calculated for the base data 204 (Block 256). The QF quality factor may comprise one or more numbers that can be selected from statistical measures of the data set, such as an average value, a median value, a standard deviation, a weighted average, or another suitable QAVRi-QAVRn value. In one aspect, the quality factor QF represents a baseline quality level for the perforations in the baseline data. A quality assessment value (210) is calculated for the result data (212) corresponding to the quality criterion 202, whose quality assessment value is called QAVresult. The quality level (QL) (214) for the result data (212) in relation to the quality factor can then be calculated using the quality factor QF and the resulting quality assessment value QAV. The QL quality level of the outcome data can be represented by any suitable value, such as a rating against the QF quality factor of the baseline data, a percentile at which the quality level of the outcome data falls in relation to the factor QF quality, etc.
    [0022] In some cases, it may be desirable to use a subset of the QAVRi-QAVRn quality assessment values from the baseline data to determine the quality level of an outcome data. For example, if the base data correspond to perforations in a
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    13/21 hemisphere it may be desirable to use QAVs for drilling in a particular geographic area within the hemisphere or drilling over a period of time, such as a year of data acquisition, to determine the level of quality of the particular outcome data. In a case like this, quality assessment values corresponding to a subset of the values in the QAVRiQAVRn set can be selected (Block 270). The values in the subset are called QAVs. A QFs quality factor of the QAVs subset quality assessment values can then be computed. The QL quality level for the result data can then be computed using the QAVresult quality assessment (210) of the result data and the subset QFs (Block 272).
    [0023] In one aspect, the quality assessment values of a particular drilling data corresponding to the various quality parameters Q1-Qm result in a set of quantitative quality indicators, each indicator corresponding to a single value. An average value plus a standard deviation for a quality indicator can be computed from several perforations. Such qualitative values can be stored in a globally accessible database and used in a classification or comparison to individual drilling quality levels, drilling groups (referred to in this document as comparison groups or CGs). CGs can be groups of data having similar parameters so that their quality levels can be compared and / or classified. Any of the parameters described above or other useful parameters can be used for comparison and classification of CGs. In one aspect, a statistical value for each such parameter (for example, an average value and standard deviation) can be calculated. The data in a particular GC can be classified with respect to an average group value for
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    14/21 each parameter considered. For example, a cumulative interval parameter for a particular data set can be classified as worse than 90% of the data sets in the GC. The images in the same CG can be additionally grouped, for example, on the basis of geographic regions. A grouping like this can help to assess the performance of the region, as a region X has better image quality in real time when compared to region Y. This reason for the difference in quality between regions X and Y may be a reason identifiable, such as the communication devices used to obtain data in the X region had a higher telemetry rate when compared to the communication devices used in the Y region. As noted earlier, the use of data in a CG can be time-limited, such as data no older than two years, to ensure that recent or updated data is used for classification. In addition, the level of statistical quality of a GC can be tracked over a longer period of time to identify trends in quality of service. In another aspect, the data collected can be used to track the quality and reliability of a particular service. The quality assessment data collected in this document can be used to establish baselines for the quality of certain tools and services, demonstrate the service quality of certain tools and services, modify certain tools and / or develop new tools and technologies.
    [0024] Figure 3 is a flow chart illustrating an exemplary method
    300 to perform a real-time data quality assessment using data in a memory as the base data. In the case of real-time data, quality parameters or indicators other than the quality parameters indicated above can also be used. For example, the peak signal ratio value for
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    15/21 noise (PSNR) can be used as a quality parameter. The PSNR value for a real-time data set can be calculated under the assumption that the memory data set corresponds to the base data and the real time data set corresponds to the result data. Another example could be the intervals that occur in the data in real time because of problems associated with the communication channel (such as the mud pulse telemetry channel) used in drilling system 100 to obtain the well hole data . The maximum value of such intervals and the sum value of such intervals can be used as the quality indicator. Additional characteristics of a real-time data set, such as energy, entropy, frequency and contrast content, can also be used as quality indicators when relating them to the corresponding characteristic of the memory data set. For example, the ratio of real-time data energy to memory data energy can measure the quality of real-time data. In one aspect, values of such characteristics can be calculated for real-time and memory data and compared to determine the quality level of the real-time data. Pixel size of a real-time image can be another indicator of quality. Image resolution can also influence the quantitative quality assessment. It may be useful to use different quantitative values for quality assessment for different image formats. Truncations caused by problems of time and depth can also be used as a parameter and their density can be used to define the quality criterion.
    [0025] Referring further to figure 3, to determine a QL quality level for real-time data, the process may include: defining a QC 302 quality criterion for real-time data
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    16/21
    304 (Block 350); determine a QAVM quality assessment value for a base data, such as a memory data (Block 352); determine a QAVR quality assessment value for the data in real time during the execution of a well hole (Block 354); and determine the QL quality level for the real-time data 304 using the QAVM quality assessment value for the memory data and the QAVR quality assessment value for the real-time data 304. The quality assessment methods of the invention in this document can be implemented in a computer-based system or in a processor-based system, arranged in a surface location or in a BHA.
    [0026] Figure 4 is a functional block diagram illustrating an exemplary computer system 400 configured to implement the methods described in this document, according to one modality. System 400 is shown to include a processor 410, which can be a microprocessor used to perform computing and processing data. The 410 processor can be a part of a surface computer system or a part of a circuit in a downhole tool. Result data 420, which can include real-time data 422, memory or drill data 424, is accessible by processor 410. Also, base data 430, which can include data 432 of a drilling In particular, drilling data 434 in a geographic area and / or time-based data 436 or a combination of data 438 are accessible by processor 410. Result data 420 and base data 430 can be stored in one or more more computer-readable media accessible by the 410 processor. The computer-readable media can be any data storage device, including, but not limited to, random access memory, memory
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    17/21 read-only, a flash memory and a disc. A quality criterion 440 based on one or more parameters of interest 442 is made accessible to processor 410 for use in performing the methods disclosed in this document. A computer program 450 containing instructions for performing the methods disclosed in this document is accessible to the 410 processor through suitable computer-readable media. Programmed instructions can include, among other things, instructions for accessing results data and baseline data; determine the quality assessment values in relation to the outcome data and the baseline data (452); determine a quality factor for the baseline data and use the quality factor for the baseline data and the quality assessment value of the outcome data (454); and determining a QL quality level of the outcome data (456); and provide the various calculations and results thus obtained in the form of on-screen and hard copy reports (458).
    [0027] Thus, in one aspect, the invention provides a method of determining a relative quality level of a downhole data (a first data set or a result data) that can comprise: defining a quality criterion ( QC) based on one or more quality parameters (or quality indicators); determine a quality assessment value (QAV) for the first data corresponding to the quality criterion; determining a QAV for a second data set (base data) comprising one or more data sets corresponding to the quality criterion; determine a QF quality factor from the quality assessment values determined from the second data set; and determining the relative quality level of the first data set using the QAV of the first data and the quality factor QF of the second data. In one respect, determining the quality factor may include using a
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    18/21 subset of the quality assessment values of a plurality of drilling data sets. In another aspect, the quality factor can be a statistical measure.
    [0028] The second data set may include data sets selected according to one or more specific criteria. These may include, but are not limited to: data from a single drilling, data from a specified period of time within a drilling; a selected geographic region; a combination of two or more geographic regions; perforations made during a selected period of time; data sets using at least one common downhole tool; perforations for the same customer; and any combination of the above.
    [0029] Also in another aspect, a method for determining the relative quality of a real-time downhole data set is provided, the method of which may include: defining a quality criterion based on at least one quality parameter ; obtain a first set of downhole data in real time during the execution of a wellhole; obtain a second set of downhole data; determine a quality assessment value for the first downhole data set corresponding to the quality criterion; determine a quality assessment value for the second data set corresponding to the quality criterion; and determining the relative quality level of the first downhole data set using the quality assessment value of the first downhole data set and the quality assessment value of the second data set during drilling the well hole . In one aspect, the second data set can include one of: data stored in a tool memory during drilling the well; and data stored at a surface location. In another aspect, the first data set can be a
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    19/21 subset of the second data set. In another aspect, the method may additionally include determining the quality level of the first data set before transmitting the first data set to a surface location during drilling the well.
    [0030] The quality parameters used when defining the quality criterion can include one or more parameters that can provide a quantitative measure of a quality level of a downhole data. Quality parameters can include, but are not limited to: peak to noise ratio (PSNR); number of anomalous data; breaks; energy; entropy; contrast; data density; resource data; data artifacts; a sudden change in measured values; a data artifact caused by a problem with time and depth tracking; pixel size; density of a resource per depth range; tracks in an image; a sudden change in color; truncation, as caused by an event of time and depth; and a subjective criterion.
    [0031] In another aspect, a computer-readable media accessible by processor is provided, in which the computer-readable media has a program embedded in it, whose program may include instructions to be performed by the processor, whose instructions may include additional instructions to: access a well bottom data comprising data corresponding to one or more well holes (drilling); access a quality criterion based on one or more parameters of interest; compute a QAV quality assessment value for each well hole using the quality criterion; instructions for determining a statistical value of SQAV quality assessment from the computed quality assessment values of well bores; determine a
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    20/21 QAV quality assessment value of a result data using the quality criterion; and determining a quality level of the result data using the QAV of the result data and SQAV of the base data. In aspects, the parameter of interest can include at least one parameter that provides a quantitative measure of a quality level of a downhole data. In addition, the parameter of interest can be selected from the group consisting of: peak to noise ratio (PSNR); number of anomalous data; breaks; energy; entropy; contrast; data density; resource data; data artifacts; a sudden change in measured values; a data artifact caused by a problem with time and depth tracking; pixel size; density of a resource per depth range; tracks in an image; a sudden change in color; truncation caused by a time and depth event; and a subjective criterion.
    [0032] Also in another aspect, an apparatus for determining a quality level of a downhole data is provided, whose apparatus, in one embodiment, may include; a processor, a data storage device containing the first data and a second data set, a computer program executable by the processor, in which the computer program may include instructions for accessing the first data; determine a quality assessment value of the first data using a defined quality criterion; determine a quality assessment value of the second data using the quality criterion, and determine the quality level of the first data in relation to the second data using the quality assessment values of the first data and the second data.
    [0033] In one aspect, the instruction to determine a quality level of the first data set in relation to the second
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    21/21 data set may include instructions for determining a quality factor from the determined quality assessment value of the second data set. Furthermore, the quality factor can be a statistical measure. In another aspect, the instruction for determining a quality level of the first data set in relation to the second data set comprises instructions for determining a quality factor from a subset of quality assessment values determined from a plurality of sets drilling data. In aspects, the second data set comprises data sets selected according to one or more specific criteria. In one respect, specific criteria are selected from the group consisting of: data from a single drilling; data for a specified time period within a drilling; a selected geographic region; a combination of two or more geographic regions; perforations made during a selected period of time; data sets using at least one common downhole tool; and drilling for the same customer.
    [0034] The invention in this document describes particular modalities of an apparatus and methods of quality assessment. Such modalities are not to be interpreted as limitations on the concepts described in this document. Various modifications to the apparatus and methods described in this document will be apparent to persons of ordinary skill in the art. All such modifications are considered to be a part of the invention in this document.
    权利要求:
    Claims (12)
    [1]
    1. Method for determining the relative quality of a downhole data set in real time, characterized by the fact that it comprises:
    define a quality criterion based on at least one quality parameter;
    obtaining a first real-time downhole data set for a downhole parameter using a first downhole tool while drilling a wellhole;
    obtaining a second set of downhole data relating to the downhole parameter comprising data different from the first data set, using a second downhole tool;
    determine a quality assessment value for the first downhole data set corresponding to the quality criterion;
    determine a quality assessment value for the second data set corresponding to the quality criterion;
    determining a quality factor of the second data set from the determined quality assessment value of the second data set; and determine the relative quality level of the first downhole dataset using the quality assessment value of the first downhole dataset and the quality assessment factor of the second dataset during wellhole execution .
    [2]
    2. Method according to claim 1, characterized by the fact that the second set of downhole data comprises data selected from the group consisting of: data
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    2/4 stored in a tool memory during drilling the well; and data stored at a surface location.
    [3]
    Method according to claim 1, characterized by the fact that the first downhole data set is a subset of the second downhole data set.
    [4]
    Method according to claim 1, characterized in that determining the relative quality level comprises determining the quality level of the first downhole data set before transmitting the first downhole data set to a surface location while drilling the well.
    [5]
    5. Method according to claim 1, characterized by the fact that at least one quality parameter used when defining the quality criterion comprises at least one parameter that provides a quantitative measure of a quality level of a downhole data .
    [6]
    6. Method according to claim 1, characterized by the fact that at least one quality parameter is selected from the group consisting of: peak to noise ratio (PSNR); number of anomalous data; breaks; energy; entropy; contrast; data density; resource data; data artifacts; a sudden change in measured values; a data artifact caused by a problem with time and depth tracking; pixel size; density of a resource per depth range; tracks in an image; a sudden change in color; truncation caused by a time and depth event; and a subjective criterion.
    [7]
    7. Apparatus for determining a quality level of a downhole data, characterized by comprising:
    Petition 870190088425, of 09/06/2019, p. 7/34
    3/4 a processor (142);
    a data storage device (144) containing a first data set, obtained from the measurements of a downhole parameter by a first downhole tool during the drilling of the wellhole, and a second set of data containing obtained data generated from different measurements of the downhole parameter by a second downhole tool; and a computer program (146) executable by the processor (142), wherein the computer program (146) comprises instructions for:
    access the first data set of the downhole parameter from the first database set;
    determine a quality assessment value for the first data set using a defined quality criterion;
    determining a quality assessment value for the second data set of the downhole parameter of the second data set using the quality criterion;
    determining a quality factor of the second data set from the determined quality assessment value of the second data set; and determining a quality level of the first data set in relation to the second data set using the quality assessment values of the first data set and the quality factor of the second data set.
    [8]
    8. Apparatus according to claim 7, characterized in that the instruction to determine a quality level of the first data set in relation to the second data set comprises instructions for determining a quality factor from the evaluation value of determined quality of the second set
    Petition 870190088425, of 09/06/2019, p. 8/34
    4/4 of data.
    [9]
    9. Apparatus according to claim 7, characterized by the fact that the quality factor is a statistical measure.
    [10]
    Apparatus according to claim 7, characterized in that the instruction to determine a quality level of the first data set relative to the second data set comprises instructions for determining a quality factor from a subset of values of quality assessment determined from a plurality of drilling data sets.
    [11]
    11. Apparatus according to claim 7, characterized by the fact that the quality parameter is selected from the group consisting of: peak to noise ratio (PSNR); breaks; energy; entropy; contrast; resource data; a sudden change in measured values; time and depth tracking; pixel size; density of a resource per depth range; tracks in an image; a sudden change in color; and truncation caused by a time and depth event.
    [12]
    12. Apparatus according to claim 11, characterized by the fact that the second set of data is selected from the group consisting of: data from a single perforation; data for a specified period of time during drilling; a selected geographic region; a combination of two or more geographic regions; perforations made during a selected period of time; data sets using at least one common downhole tool; and drilling for a specific customer.
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    法律状态:
    2019-01-15| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|
    2019-07-09| B06T| Formal requirements before examination [chapter 6.20 patent gazette]|
    2019-11-19| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2020-01-21| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 03/08/2010, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    US23090709P| true| 2009-08-03|2009-08-03|
    PCT/US2010/044197|WO2011017289A2|2009-08-03|2010-08-03|Apparatus and method for quality assessment of downhole data|
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