• 专利附录
  • 专利说明
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    • 专利摘要:
    A method may include: modeling a complex fracture network in the subterranean formation with a mathematical model based on a natural fracture network map and measured subterranean formation data collected in association with a fracturing treatment underground formation to produce a network map of complex fractures; the importation of the microseismic data collected in association with the fracturing treatment of the underground formation in the mathematical model; identifying directions of continuity within microseismic data through a geostatistical analysis that is part of the mathematical model; and the correlation of continuity directions within the microseismic data with the complex fracture network using the mathematical model to produce a microseismic weighted complex (MSW) complex fracture map.
    公开号:FR3057092A1
    申请号:FR1758584
    申请日:2017-09-15
    公开日:2018-04-06
    发明作者:Jeffrey Marc Yarus；Ashwani Dev；Jin Fei；Trace Boone Smith
    申请人:Landmark Graphics Corp；
    IPC主号:
    专利说明:

    (57) a method can comprise: modeling a network of complex fractures in the underground formation with a mathematical model on the basis of a network map of natural fractures and measured data of the underground formation collected in association with a fracturing treatment of the underground formation to produce a network map of complex fractures; importing the microseismic data collected in association with the fracturing treatment of the underground formation in the mathematical model; the identification of the directions of continuity within the microseismic data by means of a geostatistical analysis which is part of the mathematical model; and correlating the directions of continuity within the microseismic data with the complex fracture network using the mathematical model to produce a microseismic weighted complex fracture network map (MSW).
    2015-IPM-099785-U1-FR i
    GEOSTATISTICAL ANALYSIS OF MICROSISMIC DATA IN THE FRAMEWORK OF A FRACTURE MODELING
    BACKGROUND The present application relates to methods and systems for modeling networks of fractures of underground formations.
    Oil and gas wells produce oil, gas, and / or by-products from underground oil tanks. Oil reservoirs, like those containing oil and gas, generally include finite, discontinuous, inhomogeneous, anisotropic, and non-elastic (DIANE) rock formations. These formations, in their natural state (before any fracturing treatment), generally include networks of natural fractures. As used in this document, the term “network of natural fractures” refers to the set of fractures, connected or not, within an underground formation before any fracturing treatment. Fractures within a network of natural fractures can have different sizes, shapes and orientations.
    During a hydraulic fracturing treatment, the fluids are pumped at high pressure into a rock formation via a wellbore in order to cause or form fractures in the formations and to increase the permeability and the production. from training. Fracturing treatments (and production and other activities) can lead to the development of complex fracture models within the training. As used in this document, the term “network of complex fractures” refers to the set of natural fractures and induced fractures, connected or not, within an underground formation. Complex fracture networks can include fractures that extend to the wellbore, along several azimuths, on several different planes and in several directions, along the discontinuities of rock, and in several areas of a training.
    ] BRIEF DESCRIPTION OF THE FIGURES [0004] The following figures are included to illustrate certain aspects of the embodiments, and should not be considered as exclusive embodiments. Disclosed object admits considerable modifications, transformations, combinations, and form equivalents
    2015-IPM-099785-U1-FR and function, as will be understood by a specialist in the field who benefits from this disclosure.
    FIG. 1 is a flow diagram of a method which uses a mathematical model to correlate the microseismic data with maps of the networks of fractures according to at least certain embodiments of the present disclosure.
    Figure 2 is a representation of the determination of a horizontal variogram according to the EQ. 1.
    FIG. 3 illustrates a diagram of an example of a cable line system which can use the principles of the present description.
    FIG. 4 illustrates a diagram of an exemplary system which comprises a horizontal well which can use the principles of the present description.
    Figure 5 is a polar diagram of the semi-variance derived from microseismic data using a geostatistical analysis.
    Figures 6 and 7 are diagrams of the probability of failure of the dip azimuth and the attack azimuth, respectively, derived from the measured data of the image of the borehole.
    FIG. 8 is an enlarged view of the polar diagram of FIG. 5 and of the two-dimensional representation of the attack azimuth of FIG. 7.
    FIG. 9 is a representation in the form of a geocellular grid of the network map of complex fractures with microseismic weighting (MSW).
    FIG. 10 illustrates a plan of the network map of complex fractures MSW of FIG. 9.
    Figure 11 is an alternative view of the MSW complex fracture network map.
    DETAILED DESCRIPTION The present application relates to methods and systems which use microseismic data during the modeling of networks of fractures of underground formations.
    Hydraulic fracturing treatments (also referred to here as "fracturing treatments") are generally carried out in order to induce fractures in an underground formation, and thus improve the
    2015-IPM-099785-U1-EN productivity of underground formation hydrocarbons. The pressures generated by the fracturing treatment can induce low amplitude or low energy seismic events in the underground formation, known as "microseismic events". As used in this document, the term “microseismic event” refers to a micro-earthquake that follows a change in the distribution of stresses in an underground formation, for example in response to hydraulic fracturing treatments . Microseismic events may be due, for example, to rock slides, rock movements, rock fractures, or other events within the underground formation.
    The microseismic events can be detected by sensors, and the relevant microseismic data can be collected for analysis. As used in this document, the term "seismic data" refers to data collected by one or more sensors related to microseismic events and may include location and magnitude information on the microseismic event. The sensors can be placed in several places relative to the wellbore, for example in a wellbore in which the fracturing treatment is carried out, in a well (for example an observation well, an injection well, or a production well) in which the fracturing treatment is not carried out, but which is close enough to the fracture network to measure microseismic events, on the surface of the Earth, slightly buried (within about 300 feet ) and close enough to the fracture network to measure microseismic events, and the like. In some cases, combinations of sensor placement may be used. Examples of sensors that can be used on the surface, near the surface, or in the background may include, but are not limited to, geophones, eleometers, fiber optic sensors, and the like, and any combination thereof. this. In some cases, more than one sensor (for example two or more geophones or one or more geophones in combination with one or more hydrometers) can be used in a sensor network.
    The microseismic data can be collected in association with a fracturing treatment, before the fracturing treatment begins, during the fracturing treatment, after the fracturing treatment, or any combination thereof. Processing
    2015-IPM-099785-U1-FR fracturing can cause, among other things, the creation or extension of at least one fracture in the underground formation.
    The systems and methods of the present application correlate the microseismic data with a map of the fracture networks derived from other measured data in order to improve the accuracy of the map of the fracture network.
    Figure 1 is a flow diagram of a method which uses a mathematical model 100 to correlate the microseismic data 114 with a map of the fracture network according to at least some embodiments of the present description. The mathematical model 100 uses the well log data 102 collected before a fracturing treatment to model a network of natural fractures of an underground formation, for example using a stochastic process, and to produce a map of the network. natural fractures 104. In some cases, other mathematical analysis and manipulation may be performed before or during modeling, and may include, but are not limited to, normalization of well 102 log data, model calibration , cleaning of log data, and the like, and any combination thereof.
    The well 102 logging data can come from one or more measurements of the underground formation, for example measurements by nuclear magnetic resonance, measurements by gamma rays, photoelectric measurements, measurements by neutrons, geochemical measurements , resistivity measurements, acoustic measurements, sonic measurements, borehole imaging measurements, and the like, and any combination thereof, and can be collected with measurement tools during drilling (MWD) and during drilling (LWD), wired line tools, fiber optic tools, or combinations thereof.
    The map of the network of natural fractures 104 can be represented in the form of a three-dimensional matrix of the underground formation (also called “geocellular grid”), of a two-dimensional slice or of a topographic collapse. three-dimensional matrix, one-dimensional network representing the underground formation, and the like. In a one-dimensional network, the formation data points (for example the geocell grid data points) are transformed into a mathematical matrix which has matrix identification values which correspond to each of the grid data points geocellular.
    2015-IPM-099785-U1-FR [0023] The map of the network of natural fractures 104 may be a map of one or more properties or characterizations of the underground formation linked to fractures of the network of natural fractures. Examples of properties or characterizations may include, but are not limited to, the probability of fault, the attributes of curvature, seismic impedance, and the like. As used in this document, the term "probability of a fault" refers to a probability that a fault exists at a given location. In some cases, the probability of a fault can be reported as a volume of probability calculated using the fault-oriented semblance algorithm described by Haie (GEOPHYSICS, VOL. 78, NO. 2 (MARCH-APRIL 2013), P 033-043, Methods to compute fault images, extract fault surfaces, and estimate fault throws from 3D seismic images).
    In combination with the fracturing treatment of the underground formation, which can be performed before the fracturing treatment, during the fracturing treatment, after the fracturing treatment, or any combination thereof, data additional data (referred to here as "measured data 106") may be collected in connection with the underground formation. The measured data 106 can come, for example, from measurements by nuclear magnetic resonance, from measurements by gamma rays, from density measurements, from neutron measurements, from geochemical measurements, from resistivity measurements, from acoustic measurements, from sonic measurements, borehole imaging measurements, and the like, and any combination thereof, and can be collected with surface tools, measurement during drilling (MWD) / logging during drilling (LWD) tools, wired line tools, fiber optic tools, or combinations thereof.
    The mathematical model 100 uses the map of the network of natural fractures 104 and the measured data 106 to model a network of complex fractures, for example using a stochastic process, and to produce a map of the network of fractures. complex 108 which represents the network of fractures after the fracturing treatment. In some cases, other mathematical analyzes and manipulations can be performed before or during modeling, and may include, but are not limited to, normalization of measured data 106, calibration of the model, cleaning of log data, and the like, and any combination thereof.
    The map of the complex fracture network 108 can be represented as a three-dimensional matrix of the underground formation, a one-dimensional network representing the underground formation, and the like, and can
    2015-IPM-099785-U1-EN be a map of one or more properties or characterizations of the underground formation linked to fractures, including those described in this document and linked to the map of the network of natural fractures 104.
    In addition, in combination with the fracturing treatment of the underground formation, microseismic data 114 can be collected about the underground formation using surface sensors or bottom sensors, as described above. . Examples of microseismic data 114 may include, but are not limited to, the magnitude of microseismic events, the absolute duration of microseismic events, the relative duration of microseismic events, the mechanism of microseismic events, the p / wave s ratios, the signal-to-noise ratios, seismic moment, amount of shear associated with microseismic events, tensors of microseismic moment, formation anisotropy, location of microseismic events, and the like, and any combination thereof. In addition, well pressure, formation constraints, or both can be measured and correlated with microseismic data 114.
    The mathematical model 100 can then apply a geostatistical analysis to the microseismic data 114 in order to identify the directions of continuity 112 within the microseismic data 114. The geostatistical analysis quantifies the directions of anisotropic behavior and continuity within the data 114 and identifies trends in azimuths and fracture planes. More specifically, an example of geostatistical analysis involves the application of a variogram to microseismic data 114. As used in this document, the term “variogram” refers to a function (eg EQ. 1) of spatial correlation.
    Figure 2 is a representation of the determination of a horizontal variogram according to the EQ. 1.
    2n
    EQ. 1 where: γ corresponds to the semi-variance h corresponds to the offset distance
    Xi corresponds to the variable considered (microseismic data 114 for the analyzes of this description) as a function of the spatial location
    X (i + h -) corresponds to the offset version of the variable considered
    2015-IPM-099785-U1-EN n corresponds to the number of pairs separated by the offset distance (h) More specifically, Figure 2 illustrates the process of selecting the pairs of data points to be used for the calculation of d '' a variogram (geostatistical spatial model). The image is frozen in time at a stage in order to illustrate the process. Point X, bottom left is an evaluated data point. The object is to find all the other points with which X, will be associated according to a specified distance and azimuth with respect to X ,, and to identify the distance interval (offset distance (h)) in which this occurs. . An angle tolerance and an offset tolerance are provided for the azimuth and offset distance, respectively, to allow modest deviations. In addition, a bandwidth is included at the azimuth tolerance angle to prevent the search from deviating too far from the specified azimuth. The illustration identifies two points which will be pairs, one of which is labeled X, + h and is identified as occurring within the azimuth tolerance and within a specific offset interval (offset + tolerance) indicated by the lines in dotted. The process is repeated at each data point until all possible pairs are identified and assigned to their appropriate offset interval.
    The variograms from the geostatistical analysis can be used to identify the directions of continuity 112 within the microseismic data 114, as described in more detail in the examples.
    Referring again to Figure 1, in some cases, other mathematical analyzes and manipulations can be performed before or during the geostatistical analysis, and can include, but are not limited to, the normalization of microseismic data 114 , validation of the geostatistical analysis (as described in the publication of the patent application US Pat. No. 2010/0121622), and the like, and any combination thereof.
    Optionally, the directions of continuity 112 can be used to produce a microseismic map 110 of the underground formation, which can be represented as a three-dimensional matrix of the underground formation, a one-dimensional network representing the underground formation, and the like. . In some cases, a model, for example, which uses a stochastic process, can be used when producing the 110 seismic map.
    The mathematical model 100 then correlates the directions of continuity 112 (optionally represented in the form of the microseismic map 110) and the network map of complex fractures 108, including one
    2015-IPM-099785-U1-FR example is included in the examples. This correlation interprets the plans of the fractures by comparing the locations of the directions of continuity 112 with the locations of the fractures (and more especially of the new fractures or extended fractures) on the map of the network of complex fractures 108, and weights the fractures which correspond to the directions of continuity 112 as having a higher probability of presence. The result of the correlation of the directions of continuity 112 and of the map of the network of complex fractures 108 is a map of the network of complex fractures with microseismic weighting (MSW) 116.
    The map of the microseismic-weighted complex fracture network 116 can be represented as a three-dimensional matrix of the underground formation, a one-dimensional network representing the underground formation, and the like, and can be a map of one or more properties. or characterizations of the underground formation linked to fractures, including those described in this document and linked to the map of the network of natural fractures 104. In some cases, a stochastic process correctly adapted to balance the correspondence between the directions of continuity 112 and the complex fracture network map 108 can be used to produce the microseismic-weighted (MSW) complex fracture network map 116.
    The network of microseismic-weighted complex fracture network 116 which results from the mathematical model 100 can be used for another analysis and / or for modeling the underground formation. For example, the map of the microseismic-weighted complex fracture network 116 can be used as a basis for estimating the production of hydrocarbons 118 from the underground formation. In another example, the microseismic-weighted complex fracture network map 116 can be used to identify a drilling location of a second wellbore 120 in the underground formation so that the second wellbore intersects the fracture network complex in underground formation. In another example, the map of the microseismic-weighted complex fracture network 116 can be used to determine the parameters of a subsequent fracturing treatment 122 of the underground formation. In some cases, two or more of the preceding examples can be produced using the microseismic-weighted complex fracture network 116 map.
    In another example, which may be distinct from or associated with one or more of the preceding examples, the map of the network of complex fractures with microseismic weighting 116 can be used as input to the model
    2015-IPM-099785-U1-FR 100 in place of the network of natural fractures 104 when a subsequent fracturing treatment is performed. Thus, the mathematical model 100 can be executed again, in which the map of the network of complex fractures 108 is based on the map of the network of complex fractures with microseismic weighting 116 and on the measured data 106 associated with a subsequent fracturing treatment in order to produce a second microseismic-weighted complex fracture network map, which can be used to estimate hydrocarbon production from the underground formation, to identify a drilling location for a second wellbore, to determine the parameters of a subsequent fracturing processing, to run the mathematical model 100 again, and any combination thereof.
    The analyzes and methods described in this document can be implemented by a set of instructions which allow a processor to execute the mathematical model 100. In some cases, the processor and the set of instructions can also be used for subsequent analyzes of the network of microseismic-weighted complex fracture network 116, such as estimating the production of hydrocarbons from the underground formation, identifying a drilling location for a second well drilling, determining the parameters of a subsequent fracturing treatment, running the mathematical model 100 again, and any combination thereof.
    The processor can be part of a computer hardware used to implement the various illustrative blocks, modules, elements, components, methods and algorithms described in this document. The processor can be configured to execute one or more sequences of instructions, programming positions or code stored on a non-transient computer-readable medium. The processor can be, for example, a universal microprocessor, a microcontroller, a digital signal processor, an integrated circuit with specific application, a programmable integrated circuit, a programmable logic device, a controller, a state machine, a logic at door, discrete hardware components, an artificial neural network, or any suitable entity of the same type capable of performing calculations or other manipulation of data. In some embodiments, the hardware may further include such things as, for example, memory (e.g., random access memory (RAM), flash memory, read only memory (ROM), programmable read only memory ( PROM), a memory
    2015-IPM-099785-U1-EN ίο reprogrammable still life (EPROM), registers, hard drives, removable disks, CD-ROMs, DVDs, or any other similar device or suitable storage medium .
    The executable sequences described in this document can be implemented with one or more code sequences contained in a memory. In some embodiments, such code can be read into memory from another machine-readable medium. The execution of the sequences of instructions contained in the memory can cause a processor to implement the process steps described in this document. One or more processors in a multiprocessing arrangement can also be used to execute the sequences of instructions in memory. In addition, a wired circuit can be used in place of or in combination with software instructions to implement various embodiments described in this document. Therefore, the present embodiments are not limited to any specific combination of hardware and / or software.
    As used in this document, the term "machine-readable medium" refers to any medium which directly or indirectly provides instructions to the processor for execution purposes. A machine-readable medium can take many forms such as, for example, a non-volatile medium, a volatile medium and a transmission medium. A non-volatile medium may include, for example, optical and magnetic disks. A volatile medium can include, for example, dynamic memory. A transmission medium can include, for example, coaxial cables, metal wire, optical fiber, and metal wires that form a bus. Typical forms of machine-readable media may include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, other types of magnetic media, CD-ROMs, DVDs, other media similar optical devices, punch cards, paper strips and similar physical media with patterned holes, RAM, ROM, PROM, EPROM, and flash EPROM.
    FIG. 3 illustrates a diagram of an example of cable line system 300 which can use the principles of the present description, according to one or more embodiments. At different times before, during or after a fracturing treatment, the logging data 102, the measured data 106, and the microseismic data 114 of FIG. 1 can be collected to
    2015-IPM-099785-U1-EN an underground formation 310. In some cases, wellbore tools that extend into a wellbore 304 (for example a train intended to perforate formation 310) can be removed from '' a borehole 304 in order to carry out the measurement / logging operations. As illustrated, the wired line system 300 may include one or more wired line tools 302 which can be suspended in the wellbore 304 by a cable 312. The wired line tools 302 can be connected to the cable 312. The cable 312 can include conductors intended to convey energy to the wired line tools 302 and to facilitate communication between the surface and the wired line tools 302. A logging installation 306, illustrated in FIG. 3 in the form of a truck, can collect measurements from the wired line tool 302, and can include computing facilities 308 for monitoring, processing, storing and / or viewing the measurements collected by wired line tools 302 The calculation installations 308 can be connected to the wired line tools 302 using the cable 312. In certain cases, the mathematical model 100 of FIG. 1 can be implemented using computing facilities 308. Otherwise, the measurements collected by wired line tools 302 can be transmitted (wired or wireless) or physically provided to offsite computing facilities, where the mathematical model 100 of Figure 1 can be implemented.
    FIG. 4 illustrates a diagram of an example of a system 400 which can use the principles of the present description, according to one or more embodiments. In the illustrated system 400, a wellbore 402 with a vertical section 404 and a horizontal section 406 is aligned with the casing 408 cemented therein to support the wellbore 402. Otherwise, part of the wellbore 402 may have no casing, and is referred to as an "open hole". For example, the casing 408 may extend from a surface, such as the surface of the Earth, or from an intermediate point between the surface and the formation 410. In the illustrated system 400, a fiber optic cable 412 extends along the casing 408.
    One or more wellbore tools 420, for example a completion assembly or a perforator, can be used to prepare the horizontal section 406 for the subsequent extraction of the hydrocarbons from the surrounding formation 410. For example, a completion assembly may include a plurality of seals which isolate the different production intervals in the horizontal section 406. In some cases, a fluid (for example a stimulation fluid, a treatment fluid, an acidifying fluid,
    2015-IPM-099785-U1-FR a compliance fluid, or any combination thereof) can be injected into the wellbore 402 or surrounding formation 410 through the wellbore tools 420.
    The system 400 also includes an observation well 422 which has a plurality of geophones 424 placed inside in order to measure the seismic and / or microseismic data. In addition, the system 400 includes a plurality of surface geophones 426 intended to measure the seismic and / or microseismic data.
    The embodiments of the present description include, but are not limited to, the embodiment A, the embodiment B and the embodiment C.
    Embodiment A is a method comprising: modeling a network of complex fractures in the underground formation with a mathematical model based on a network map of natural fractures and measured data of the underground formation collected in association with a fracturing treatment of the underground formation in order to produce a network map of complex fractures; importing the microseismic data collected in association with the fracturing treatment of the underground formation in the mathematical model; the identification of the directions of continuity within the microseismic data by means of a geostatistical analysis which is part of the mathematical model; and correlating the directions of continuity within the microseismic data with the complex fracture network using the mathematical model to produce a microseismic weighted complex fracture network map (MSW).
    Embodiment B is a system comprising: a wellbore tool placed along a wellbore which extends into an underground formation; a non-transient computer-readable medium connected to the wellbore tool in order to receive the measured data of the underground formation coming from the wellbore tool and collected in association with a fracturing treatment of the underground formation, and encoded with instructions which, when executed, execute the method of embodiment A.
    Embodiment C is a non-transient computer-readable medium encoded with instructions which, when executed, execute the method of Embodiment A.
    Embodiments A, B and C may further include one or more of the following: Element 1: the process
    2015-IPM-099785-U1-FR further comprising: producing the map of the natural fracture network by modeling a network of natural fractures in the underground formation with the mathematical model based on a logging of the underground formation; element 2: the method further comprising: developing a parameter for a subsequent wellbore operation on the basis of the map of the network of microseismic-weighted complex fractures; element 3: the method further comprising: identifying a drilling location of a second wellbore within the network of complex fractures; item 4: the method further comprising: identifying a drilling location of a second wellbore within the complex fracture network and drilling the second wellbore; element 5: the method further comprising: estimating a quantity of hydrocarbon production based on the map of the network of microseismic-weighted complex fractures; element 6: the method further comprising: estimating a quantity of hydrocarbon production based on the map of the network of complex fractures with microseismic weighting and the production of hydrocarbons from the underground formation; element 7: the method further comprising: determining parameters for a subsequent fracturing treatment of the underground formation on the basis of the map of the network of complex fractures with microseismic weighting; element 8: the method further comprising: determining parameters for a subsequent fracturing treatment of the underground formation on the basis of the map of the microseismic-weighted complex fracture network and carrying out the subsequent fracturing treatment with the parameters; element 9: the method further comprising: fracturing the underground formation a second time through a second fracturing network to produce a second network of complex fractures; modeling the second network of complex fractures based on the map of the network of complex fractures with microseismic weighting and of the second measured data of the underground formation collected in association with the second fracturing treatment; importing the second microseismic data collected in association with the second fracturing treatment of the underground formation in the mathematical model; the identification of second directions of continuity within the second microseismic data by means of geostatistical analysis; and correlating the second directions of continuity within the second microseismic data with the second network of complex fractures using the mathematical model to produce a second map of the network of complex fractures with microseismic weighting; element 10:
    2015-IPM-099785-U1-FR in which the measured underground formation data are chosen from the group consisting of: seismic data, gravimetric data, magnetic data, magnetotelluric data, and any combination of these -this ; and element 11: in which the modeling of the network of natural fractures involves the calculation of a probability of fault with the mathematical model. Examples of combinations may include, but are not limited to: element 1 in combination with one or more of elements 2 to 11; elements 10 and 11 in combination and optionally also in combination with one or more of elements 1 to 9; elements 7 or 8 in combination with elements 5 or 6; elements 3 or 4 in combination with elements 5 or 6; and the like.
    Unless otherwise indicated, it should be understood that all the numbers expressing quantities of ingredients, properties such as molecular weight, reaction conditions, and so on used in the present specification and the associated claims are modified in all cases by the term "approximately". Consequently, unless otherwise indicated, the numerical parameters indicated in the following specification and the appended claims are approximations which may vary depending on the desired properties which it is desired to obtain by the embodiments of the present invention. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claim, each numerical parameter must at least be interpreted according to the number of significant digits indicated and by applying ordinary techniques d 'round.
    One or more illustrative embodiments incorporating the embodiments of the invention disclosed in this document are presented in this document. All the functionalities of a physical implementation are not described or presented in the present request for reasons of clarity. It is understood that during the development of a physical embodiment incorporating the embodiments of the present invention, many specific decisions of an implementation can be taken to achieve the developer's objective, such as compliance with the associated constraints to a system, associated with a company, associated with a government, among others, which vary according to the implementation and from time to time. Although the efforts of a developer may take time, such efforts would nevertheless be a routine undertaking for those skilled in the art and benefiting from this disclosure.
    2015-IPM-099785-U1-FR [0053] Although compositions and methods are described in this document in terms of "comprising" various components or steps, the compositions and methods can also "consist essentially of" or " consist of »the various components and stages.
    In order to better understand the embodiments of the present invention, the following examples of preferred or representative embodiments are given. It should not be construed in any way as the following examples limit or define the scope of the invention.
    EXAMPLES Data was collected for an underground formation in the Permian Basin, including log data 102, measured data 106 (borehole image), and microseismic data 114 (the magnitude of microseismic events) in Figure 1. The following describes in more detail some of the data analyzes and correlations performed by the mathematical model 100.
    FIG. 5 is a polar diagram of the semi-variance (y) derived from microseismic data using a geostatistical analysis, and more specifically by applying the EQ. 1 to 360 ° of microseismic data 114 collected. The polar diagram contains two zones with high semi-variance which are generally at 45 ° and 230 ° and which are surrounded by the solid arrows superimposed on the graph. The polar diagram also presents a less marked semi-variance line which extends between 150 ° and 330 °. These zones or lines of higher semi-variance can indicate the directions of continuity 112 within the microseismic data 114 described in FIG. 1.
    The measured data from the wellbore image 106 was used to derive the probability of failure of the dip azimuth and the dip azimuth and the attack azimuth, which are illustrated in Figures 6 and 7. The probability of failure of the dip azimuth and the attack azimuth provides indications of the location of the fractures within the fracture network. More specifically, the term "dip azimuth" corresponds to the angle of inclination and to the direction of the quadrant perpendicular to "the azimuth of attack", which is the horizontal line on the structural plane (or fracture). The diagrams of FIGS. 6 and 7 illustrate the fact that the measurement data of the image of the borehole 106 indicate that the fractures can be located at 30 °, 70 °, 220 ° and 255 °.
    2015-IPM-099785-U1-FR [0058] FIG. 8 is an enlarged view of the polar diagram of FIG. 5 derived from microseismic data 114 and of the two-dimensional representation of the attack azimuth of FIG. 7 derived measured data from the image of borehole 106. The polar diagram is covered with ovals which indicate the directions of continuity identified by geostatistical analysis, which, as indicated by the superimposed arrows, is correlated with the data azimuth of attack derived from measured data from image of borehole 106. Therefore, modeled fractures which extend in these correlated directions are more likely than fractures which show no correlation between the measured data 106 and microseismic data 114.
    The mathematical model 100 described in this document was then used to simulate or produce a map of the network of complex fractures with microseismic weighting 116, the correlations described in FIG. 8 being weighted as having a higher probability of the presence of 'fracture. FIG. 9 is a geocellular grid representation of the map of the microseismic-weighted complex fracture network 116, and FIG. 10 is a plan of the map of the microseismic-weighted complex fracture network 116 of FIG. 9. Figure 10, the areas where fractures are most likely are covered with ovals. Note that the directions of the ovals are similar, indicating that the fracture may extend in this direction. FIG. 11 is an alternative view of the geocellular representation of the map of the network of complex fractures with microseismic weighting 116 on which the background or the locations of improbable fractures are removed in order to illustrate the plans of probable fractures in a manner to better see on a three-dimensional view the probability of fracture on the map of the network of complex fractures with microseismic weighting 116. Figure 11 also illustrates the location of microseismic events, which is strongly correlated to the location and direction of the most likely fracture on this view.
    The map of the microseismic-weighted complex fracture network 116 can then be used to estimate the production of hydrocarbons from the underground formation, to identify a drilling location for a second wellbore, to determine the parameters of further fracturing processing, to run the mathematical model 100 again, and any combination thereof.
    Therefore, the present invention is well suited to achieve the ends and advantages mentioned as well as those which are inherent here. the particular embodiments disclosed above are only illustrative, since the present invention can be modified and practiced in different but equivalent ways evident to a specialist in the field and who benefits from the present teachings. In addition, there is no limitation to the construction or design details described herein, other than those described in the claims below. It is therefore obvious that the particular illustrative embodiments disclosed above can be altered, combined, or modified and all variations are considered within the scope and spirit of the present invention. The invention disclosed by way of illustration in this document can be practiced appropriately in the absence of any element which is not specifically disclosed in this document and / or any optional element disclosed in this document. Although compositions and methods are described in terms of "comprising", "containing", or "including" various components or steps, the compositions and methods may also "consist essentially of" or "consist of" various components and stages . All of the numbers and ranges disclosed above may vary by a certain amount. Whenever a numeric range with a lower limit and an upper limit is disclosed, any number and any included range falling within the range are specifically disclosed. In particular, each range of values (of the form, "from about a to about b" or, equivalently, "from approximately a to b" or, equivalently, "from approximately ab") disclosed in this document is to be considered as indicating any numbers and ranges included within the widest range of values.
    2015-IPM-099785-U1-FR
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. Process comprising:
    modeling of a network of complex fractures inside the underground formation with a mathematical model on the basis of a network map of natural fractures and measured data of the underground formation collected in association with a fracturing treatment of underground formation to produce a network map of complex fractures;
    importing microseismic data collected in association with the fracturing treatment of the underground formation in the mathematical model;
    identification of directions from continuity in the data microseismic via analysis geostatistics which does part of model mathematical ; andcorrelation of directions from continuity in the data
    microseismic to the complex fracture network with the mathematical model to produce a microseismic-weighted complex fracture network map (MSW).
    [2" id="c-fr-0002]
    2. The method of claim 1 further comprising: producing the network map of natural fractures by modeling a network of natural fractures within the underground formation with the mathematical model on the basis of a logging of underground formation well.
    [3" id="c-fr-0003]
    3. Method according to claim 1, further comprising:
    development of a parameter for a subsequent well drilling operation based on the MSW complex fracture network map.
    [4" id="c-fr-0004]
    The method of claim 1, further comprising: identifying a location for drilling a second wellbore in the network of complex fractures.
    [5" id="c-fr-0005]
    The method of claim 1, further comprising: estimating an amount of hydrocarbon production based on the MSW complex fracture network map.
    2015-IPM-099785-U1-FR
    [6" id="c-fr-0006]
    6. Method according to claim 1, further comprising:
    determining parameters for a subsequent fracturing treatment of the underground formation based on the MSW complex fracture network map.
    [7" id="c-fr-0007]
    7. The method according to claim 1, further comprising:
    fracturing the underground formation a second time via a second fracturing network to produce a second network of complex fractures;
    modeling the second complex fracture network on the basis of the MSW complex fracture network map and second measured data of the underground formation collected in association with the second fracturing treatment;
    the importation of second microseismic data collected in association with the second treatment of fracturing of the underground formation in the mathematical model;
    the identification of second directions of continuity in the second microseismic data via geostatistical analysis; and correlating the second directions of continuity in the second microseismic data to the second network of complex fractures with the mathematical model to produce a second network map of complex fractures MSW.
    [8" id="c-fr-0008]
    8. The method of claim 1, wherein the measured data of the underground formation are selected from the group consisting of: seismic data, gravity data, magnetic data, magnetotelluric data, and any combination thereof.
    [9" id="c-fr-0009]
    9. Method according to claim 1, in which the modeling of the network of natural fractures involves the calculation of a probability of fault with the mathematical model.
    [10" id="c-fr-0010]
    10. System comprising:
    a wellbore tool placed along a wellbore extending into an underground formation;
    2015-IPM-099785-U1-FR a non-transient computer readable medium coupled to the wellbore tool to receive measured data of the underground formation of the wellbore tool collected in association with a fracturing treatment underground training and coded with instructions which, when executed, carry out a process comprising:
    modeling of a network of complex fractures inside the underground formation with a mathematical model on the basis of a network map of natural fractures and measured data of the underground formation collected in association with a fracturing treatment of underground formation to produce a network map of complex fractures;
    importing microseismic data collected in association with the fracturing treatment of the underground formation in the mathematical model;
    identification of directions from continuity in the data microseismic via analysis geostatistics which does part of model mathematical ; andcorrelation of directions from continuity in the data
    microseismic to the complex fracture network with the mathematical model to produce a microseismic-weighted complex fracture network map (MSW).
    [11" id="c-fr-0011]
    11. The system as claimed in claim 10, in which the instructions which, when executed, carry out the method which further comprises:
    the production of the natural fracture network map by modeling a network of natural fractures inside the underground formation with the mathematical model based on a well log of the underground formation.
    [12" id="c-fr-0012]
    The system of claim 10, wherein the instructions which, when executed, perform the method which further comprises at least one of:
    developing a parameter for a subsequent well drilling operation based on the MSW complex fracture network map; and estimating an amount of hydrocarbon production based on the MSW complex fracture network map.
    2015-IPM-099785-U1-FR
    [13" id="c-fr-0013]
    13. The system of claim 10, wherein the instructions which, when executed, carry out the method which further comprises:
    identifying a location for drilling a second wellbore in the complex fracture network.
    [14" id="c-fr-0014]
    14. The system of claim 10, wherein the instructions which, when executed, carry out the method which further comprises:
    determining parameters for a subsequent fracturing treatment of the underground formation based on the MSW complex fracture network map.
    [15" id="c-fr-0015]
    15. The system of claim 10, wherein the instructions which, when executed, carry out the method which further comprises:
    fracturing the underground formation a second time via a second fracturing network to produce a second network of complex fractures;
    modeling the second complex fracture network on the basis of the MSW complex fracture network map and second measured data of the underground formation collected in association with the second fracturing treatment;
    the importation of second microseismic data collected in association with the second treatment of fracturing of the underground formation in the mathematical model;
    the identification of second directions of continuity in the second microseismic data via geostatistical analysis; and correlating the second directions of continuity in the second microseismic data to the second network of complex fractures with the mathematical model to produce a second network map of complex fractures MSW.
    2015-IPM-099785-U1-FR
    1/9
    2015-IPM-099785-U1-FR
    2/9
    North
    2015-IPM-099785-U1-FR
    3/9
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    同族专利:
    公开号 | 公开日
    CA3032780C|2021-03-23|
    CA3032780A1|2018-04-12|
    WO2018067120A1|2018-04-12|
    AU2016425663A1|2019-02-21|
    US20190277124A1|2019-09-12|
    NO20190155A1|2019-02-04|
    GB2569900A|2019-07-03|
    GB2569900B|2022-03-02|
    GB201901535D0|2019-03-27|
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    法律状态:
    2018-07-18| PLFP| Fee payment|Year of fee payment: 2 |
    2019-09-26| PLFP| Fee payment|Year of fee payment: 3 |
    2020-04-10| PLSC| Publication of the preliminary search report|Effective date: 20200410 |
    2021-05-07| RX| Complete rejection|Effective date: 20210329 |
    优先权:
    申请号 | 申请日 | 专利标题
    PCT/US2016/055291|WO2018067120A1|2016-10-04|2016-10-04|Geostatistical analysis of microseismic data in fracture modeling|
    IBWOUS2016055291|2016-10-04|
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