Method and device for identifying favorable development area of gas reservoir

Abstract

The invention provides a method and a device for identifying a favorable development area of a gas reservoir. The method comprises the following steps: expanding longitudinal wave impedance and transverse wave impedance logging curves according to an elastic attribute automatic expansion equation to obtain a basic parameter curve; performing pairwise pairing combination transformation on the base parameter curve to obtain a temporary parameter curve; calculating a sensitivity evaluation factor of the temporary parameter curve in each pair of combinations; comparing the sensitivity evaluation factors of all the temporary parameter curves, and taking the parameter represented by the temporary parameter curve with the highest sensitivity evaluation factor value as a target gas reservoir identification parameter; converting the longitudinal wave impedance data body and the transverse wave impedance data body into a gas reservoir identification parameter data body according to the construction process of the target gas reservoir identification parameters and the parameters in the construction process; and according to the abnormal value distribution range of the gas reservoir identification parameter data body, identifying a gas reservoir development favorable area.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas geophysical exploration, and in particular to a method and a device for identifying a favorable area for gas reservoir development. Background Art

[0002] As an important global resource, natural gas exploration and development technology has become a hot topic and difficulty in current research. With the advancement of exploration, gas reservoir exploration targets have become more complex and hidden, making it increasingly difficult to discover new areas with favorable gas reservoir development, increasing the cost of exploring favorable gas reservoir development areas and increasing drilling risks; therefore, a method for identifying favorable gas reservoir development areas is urgently needed. Summary of the invention

[0003] In view of the above problems, the present invention is proposed to provide a method and device for identifying gas reservoir development zones that overcome the above problems or at least partially solve the above problems.

[0004] In a first aspect, an embodiment of the present invention provides a method for identifying a favorable area for gas reservoir development, comprising:

[0005] Automatically expand the equation according to the preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain multiple basic parameter curves;

[0006] Perform pairwise combination transformation on the base parameter curves to expand and obtain multiple temporary parameter curves;

[0007] Calculate the gas reservoir sensitivity evaluation factor of each temporary parameter curve, and select the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter;

[0008] According to the process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, the longitudinal wave impedance data volume and the shear wave impedance data volume are converted into a gas reservoir identification parameter data volume;

[0009] Based on the distribution range of abnormal values ​​of the gas reservoir identification parameter data body, the favorable area for gas reservoir development is identified.

[0010] In one embodiment, the automatic expansion equation according to the preset elastic property expands the longitudinal wave impedance logging curve and the shear wave impedance logging curve to obtain multiple basic parameter curves, including:

[0011] According to the longitudinal wave impedance logging curve and the shear wave impedance logging curve, the mean values ​​of the longitudinal wave impedance and the shear wave impedance are calculated respectively;

[0012] The mean value of the longitudinal wave impedance, the mean value of the transverse wave impedance, the longitudinal wave impedance logging curve and the transverse wave impedance logging curve are substituted into the elastic property automatic expansion equation for calculation by sequentially taking values ​​of the expansion angle θ from the range of -90° to 90° according to the preset step length; the basic parameter curves K(θ1), K(θ2) and K(θ i ); ...

[0014] The elastic property automatic expansion equation is:

[0015]

[0016] in:

[0017] I p0 represents the mean longitudinal wave impedance, I s0 represents the mean value of shear wave impedance;

[0018] I p represents the longitudinal wave impedance logging curve, I s It represents the shear wave impedance logging curve;

[0019] θ represents the expansion angle, a=(cosθ+sinθ), b=-2sinθ;

[0020] K(θ) represents a basis parameter curve.

[0021] In one embodiment, the base parameter curves are transformed in pairs to obtain multiple temporary parameter curves, including:

[0022] Substitute the basis parameter curve into the following combined transformation equation:

[0023]

[0024] in:

[0025] S1 represents the angle θ p The basis parameter curve K(θ p ), S2 represents the angle θ q The basis parameter curve K(θ q ), Indicates the angle of change, represents a temporary parameter curve;

[0026] Through From the range of -90° to 90°, take values ​​in sequence according to the preset step length to obtain a temporary parameter curve

[0027]

[0028] In one embodiment, the temporary parameter curve includes: a gas layer segment, a lithology background, and a water layer segment;

[0029] The step of calculating the gas reservoir sensitivity evaluation factor of each temporary parameter curve and selecting the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter includes:

[0030] For each temporary parameter curve corresponding to each pair of basic parameter curves, the mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background are statistically calculated;

[0031] The mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background are input into the calculation formula of the gas reservoir sensitivity evaluation factor to obtain the gas reservoir sensitivity evaluation factor of each temporary parameter curve;

[0032] Selecting the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor corresponding to each pair of basic parameter curves matched with each other as the final parameter curve corresponding to the basic parameter curves matched with each other;

[0033] The parameter represented by the final parameter curve with the highest gas reservoir sensitivity evaluation factor among the final parameter curves is determined as the target gas reservoir identification parameter.

[0034] The aforementioned target gas reservoir identification parameters can be obtained by, for example, combining the K(25°) base parameter curve and the K(82°) base parameter curve by changing -63°, as shown in FIG.

[0035] In one embodiment, the calculation formula of the gas reservoir sensitivity evaluation factor is:

[0036] I=(G m -N m ) / V G -(W m -N m ) / V w

[0037] in:

[0038] G m Represents the mean value of the gas layer segment of the parameter curve, N m represents the mean value of the background lithology of the parameter curve, W m represents the mean value of the water layer segment of the parameter curve, V G V represents the variance of the gas layer segment of the parameter curve, w represents the variance of the water layer section of the parameter curve, and I represents the gas reservoir sensitivity evaluation factor.

[0039] In one embodiment, the process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, converting the longitudinal wave impedance data volume and the shear wave impedance data volume into the gas reservoir identification parameter data volume, comprises:

[0040] Record the expansion angle θ of the base parameter curve in the process of calculating the target gas reservoir identification parameters p and θ q and changing angles

[0041] Calculate the mean value of the longitudinal wave impedance data volume and the mean value of the shear wave impedance data volume;

[0042] The mean of the longitudinal wave impedance data volume, the mean of the shear wave impedance data volume, the longitudinal wave impedance data volume, the shear wave impedance data volume and θ p Enter the elastic property to automatically expand the equation to obtain K(θ P );

[0043] The mean of the longitudinal wave impedance data volume, the mean of the shear wave impedance data volume, the longitudinal wave impedance data volume, the shear wave impedance data volume and θ q Enter the elastic property to automatically expand the equation to obtain K(θ q );

[0044] K(θ P )、K(θ q )and Substituting into the combined transformation equation, we get

[0045] Said The data body represented is the target gas reservoir identification parameter data body.

[0046] In one embodiment, the step of identifying favorable areas for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body includes:

[0047] The value range of the target gas reservoir identification parameter in the gas layer section is used as the abnormal value distribution range of the gas reservoir identification parameter data body;

[0048] According to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body, the gas reservoir identification parameter data body is delineated to obtain a spatial distribution range, and the spatial distribution range is used to represent a favorable area for developing gas reservoirs.

[0049] In a second aspect, an embodiment of the present invention provides a device for identifying a favorable area for gas reservoir development, comprising:

[0050] An expansion module, used to automatically expand the equation according to preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain multiple basic parameter curves;

[0051] A transformation module is used to perform pairwise combination transformation on the base parameter curves to expand and obtain multiple temporary parameter curves;

[0052] An identification parameter module is used to select a temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value according to the gas reservoir sensitivity evaluation factor of the temporary parameter curve, and use the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value selected as the target gas reservoir identification parameter;

[0053] A conversion module, used for converting a longitudinal wave impedance data body and a transverse wave impedance data body into a gas reservoir identification parameter data body according to a target gas reservoir identification parameter construction process and parameters obtained in the construction process;

[0054] The identification module is used to identify favorable areas for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body.

[0055] In a third aspect, an embodiment of the present invention provides a computing device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the program executed by the processor implements the aforementioned method for identifying favorable areas for gas reservoir development.

[0056] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned method for identifying favorable areas for gas reservoir development is implemented.

[0057] The beneficial effects of the above technical solution provided by the embodiment of the present invention include at least:

[0058] The method and device for identifying favorable gas reservoir development areas provided by the embodiment of the present invention automatically expand the equation according to the preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain a plurality of basic parameter curves; perform pairwise combination transformation on the basic parameter curves to expand and obtain a plurality of temporary parameter curves; calculate the gas reservoir sensitivity evaluation factor of each temporary parameter curve, and select the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter; according to the process of constructing the target gas reservoir identification parameter and the parameters obtained in the construction process, convert the longitudinal wave impedance data body and the shear wave impedance data body into a gas reservoir identification parameter data body; and identify the favorable gas reservoir development area according to the distribution range of the abnormal values ​​of the gas reservoir identification parameter data body. The method for identifying favorable areas for gas reservoir development provided by an embodiment of the present invention selects the parameters represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter to facilitate confirmation that the gas layer section is the section with the highest gas reservoir sensitivity. The depth section with the strongest gas reservoir sensitivity is identified through the gas reservoir sensitivity evaluation factor, that is, the depth section with the most drastic change (i.e., abnormal fluctuation) in the gas reservoir sensitivity evaluation factor. This depth section just represents the favorable area for gas reservoir development. The above scheme makes the judgment result of the favorable area for gas reservoir development accurate and is relatively easy to implement, which solves the problems of difficulty in new discovery of favorable areas for gas reservoir development, high exploration investment cost and high drilling risk, and provides strong technical support for comprehensive evaluation of gas fields and well site deployment.

[0059] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0060] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 A flow chart of a method for identifying favorable areas for gas reservoir development provided by an embodiment of the present invention;

[0063] Figure 2 A flow chart of target gas reservoir identification parameter calculation provided by an embodiment of the present invention;

[0064] Figure 3 The longitudinal wave impedance logging curve and the shear wave impedance logging curve provided by the embodiment of the present invention;

[0065] Figure 4 The basic parameter curves of -90°, -60°, 60° and 90° obtained by the automatic expansion equation of the elastic property provided in the embodiment of the present invention;

[0066] Figure 5 A temporary parameter curve obtained by combining and transforming -30°, 30°, 60° and 90° using a K(-60°) base parameter curve and a K(90°) base parameter curve provided in an embodiment of the present invention;

[0067] Figure 6 A target gas reservoir identification parameter curve provided by an embodiment of the present invention;

[0068] Figure 7 A cross-sectional view of a favorable area for gas reservoir development provided by an embodiment of the present invention;

[0069] Figure 8 A structural block diagram of a device for identifying favorable areas for gas reservoir development provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0071] In order to solve the problems of difficulty in discovering favorable areas for gas reservoir development, high exploration investment cost and high drilling risk, the embodiment of the present invention provides a method for identifying favorable areas for gas reservoir development, and its flow chart is as follows: Figure 1 As shown, the following steps are included:

[0072] Step S11, automatically expanding the equation according to the preset elastic properties, expanding the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtaining a plurality of basis parameter curves;

[0073] Step S12, performing pairwise combination transformation on the basic parameter curves to expand and obtain multiple temporary parameter curves;

[0074] Step S13, calculating the gas reservoir sensitivity evaluation factor of each temporary parameter curve, and selecting the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter;

[0075] Step S14, according to the process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, converting the longitudinal wave impedance data volume and the shear wave impedance data volume into a gas reservoir identification parameter data volume;

[0076] Step S15: identifying favorable areas for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body.

[0077] Specifically, in the above step S11, the automatic expansion equation according to the preset elastic property, the expansion of the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and the acquisition of multiple basic parameter curves include the following steps:

[0078] 1. According to the longitudinal wave impedance logging curve and the shear wave impedance logging curve, calculate the mean values ​​of the longitudinal wave impedance and the shear wave impedance respectively;

[0079] The above-mentioned longitudinal wave impedance logging curve and shear wave impedance logging curve are as follows: Figure 3 As shown, the left curve is the longitudinal wave impedance logging curve, and the right curve is the shear wave impedance logging curve.

[0080] 2. Substitute the mean value of P-wave impedance, the mean value of S-wave impedance, the P-wave impedance logging curve and the S-wave impedance logging curve into the elastic property automatic expansion equation for calculation by taking values ​​of the expansion angle θ from -90° to 90° in sequence according to the preset step length; obtain the basic parameter curves K(θ1), K(θ2) and K(θ i ); ...

[0082] The aforementioned elastic property automatic expansion equation may be, for example:

[0083]

[0084] in:

[0085] I p0 represents the mean longitudinal wave impedance, I s0 represents the mean value of shear wave impedance;

[0086] I p represents the longitudinal wave impedance logging curve, I s It represents the shear wave impedance logging curve;

[0087] θ represents the expansion angle, a=(cosθ+sinθ), b=-2sinθ;

[0088] K(θ) represents a basis parameter curve.

[0089] The expansion angle θ of the elastic property automatic expansion equation can be, for example, -90°, -60°, 60° and 90° as examples for automatic expansion of elastic properties. The obtained basic parameter curve is as follows: Figure 4 As shown, from left to right, they are the K(-90°) basis parameter curve, the K(-60°) basis parameter curve, the K(60°) basis parameter curve and the K(90°) basis parameter curve.

[0090] Specifically, the aforementioned base parameter curves are transformed in pairs to obtain multiple temporary parameter curves, which can be achieved, for example, by the following steps:

[0091] Substitute the basis parameter curve into the following combined transformation equation:

[0092]

[0093] in:

[0094] S1 represents the angle θ p The basis parameter curve K(θ p ), S2 represents the angle θ q The basis parameter curve K(θ q ), Indicates the angle of change, represents a temporary parameter curve;

[0095] Through From the range of -90° to 90°, take values ​​in sequence according to the preset step length to obtain a temporary parameter curve

[0096]

[0097] The angle of change of the above combined transformation equation For example, -30°, 30°, 60° and 90° can be selected. Take -30°, 30°, 60° and 90° to illustrate the example of combining the K(-60°) basis parameter curve and the K(90°) basis parameter curve. Figure 5 As shown, from left to right are the T(-30°) temporary parameter curve obtained by transforming -30° using the combination of the K(-60°) base parameter curve and the K(90°) base parameter curve; the T(30°) temporary parameter curve obtained by transforming 30° using the combination of the K(-60°) base parameter curve and the K(90°) base parameter curve; the T(60°) temporary parameter curve obtained by transforming 60° using the combination of the K(-60°) base parameter curve and the K(90°) base parameter curve; and the T(90°) temporary parameter curve obtained by transforming 90° using the combination of the K(-60°) base parameter curve and the K(90°) base parameter curve.

[0098] The aforementioned temporary parameter curve may include, for example, the following layers: gas layer, lithology background and water layer;

[0099] The above calculation of the reservoir sensitivity evaluation factor of each temporary parameter curve and the selection of the parameter represented by the temporary parameter curve with the highest reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter include the following steps, and the flowchart thereof is referred to Figure 2 As shown:

[0100] Step S21, for each temporary parameter curve corresponding to each pair of paired basic parameter curves, the mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background;

[0101] Step S22, inputting the mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background into the calculation formula of the gas reservoir sensitivity evaluation factor to obtain the gas reservoir sensitivity evaluation factor of each temporary parameter curve;

[0102] Step S23, selecting the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor corresponding to each pair of basic parameter curves matched with each other as the final parameter curve corresponding to the basic parameter curves matched with each other;

[0103] Step S24: Determine the parameter represented by the final parameter curve with the highest gas reservoir sensitivity evaluation factor among the final parameter curves as the target gas reservoir identification parameter.

[0104] The calculation formula of the sensitivity evaluation factor may be, for example:

[0105] I=(G m -N m ) / V G -(W m -N m ) / V w

[0106] in:

[0107] G m Represents the mean value of the gas layer segment of the parameter curve, N m represents the mean value of the background lithology of the parameter curve, W m represents the mean value of the water layer segment of the parameter curve, V G V represents the variance of the gas layer segment of the parameter curve, w represents the variance of the water layer section of the parameter curve, and I represents the gas reservoir sensitivity evaluation factor.

[0108] The aforementioned target gas reservoir identification parameter can be, for example, T(-63°) obtained by combining the K(25°) base parameter curve and the K(82°) base parameter curve and transforming -63°, as Figure 6 Therefore, the expansion angle θ of the base parameter curve in the following target gas reservoir identification parameter calculation process is p and θ q And the changing angle For example: p is 25°, θ q is 82° and It is -63°.

[0109] Specifically, the aforementioned process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, converting the P-wave impedance data volume and the S-wave impedance data volume into the gas reservoir identification parameter data volume, should include the following steps:

[0110] S1. Record the expansion angle θ of the base parameter curve in the process of calculating the target gas reservoir identification parameters p and θ q and changing angles

[0111] S2, calculating the mean value of the longitudinal wave impedance data volume and the mean value of the transverse wave impedance data volume;

[0112] S3, the mean value of the longitudinal wave impedance data volume, the mean value of the transverse wave impedance data volume, the longitudinal wave impedance data volume, the transverse wave impedance data volume and θ p Enter the elastic property to automatically expand the equation to obtain K(θ P );

[0113] S4, the mean value of the longitudinal wave impedance data volume, the mean value of the transverse wave impedance data volume, the longitudinal wave impedance data volume, the transverse wave impedance data volume and θ q Enter the elastic property to automatically expand the equation to obtain K(θ q );

[0114] S5. K(θ P )、K(θ q )and Substituting into the combined transformation equation, we get Said The data body represented is the target gas reservoir identification parameter data body.

[0115] In one embodiment, in the above step S15, identifying the favorable area for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body can be achieved, for example, by the following method:

[0116] The value range of the target gas reservoir identification parameter is used as the abnormal value distribution range of the gas reservoir identification parameter data body;

[0117] According to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body, the gas reservoir identification parameter data body is delineated to obtain a depth range, and the depth range is used to represent a favorable area for developing gas reservoirs.

[0118] The reason for selecting the value range of the target gas reservoir identification parameter in the gas layer section as the distribution range of the abnormal value of the gas reservoir identification parameter data body is that Figure 6 As shown in the figure, the fluctuation of target gas reservoir identification parameters in the gas layer section is particularly obvious compared with the water layer section and the background lithology section, which can well highlight the changes in the gas reservoir section.

[0119] exist Figure 6 In the analysis, the target gas reservoir identification parameter of the gas layer section fluctuates more violently in the range of 0.4-1. According to the value range of the target gas reservoir identification parameter of 0.4-1, the spatial range of 4020-4054m at depth is delineated in the gas layer section, and the delineated range is taken as the favorable area for developing gas reservoirs.

[0120] The cross-section diagram of the favorable gas reservoir development area of ​​the above gas reservoir identification parameter data body is as follows: Figure 7 As shown, Figure 7 The spatial range framed by the middle dotted line is the range of the favorable area for gas reservoir development.

[0121] Based on the same inventive concept, the embodiment of the present invention also provides a device for identifying favorable areas for gas reservoir development, and the device diagram is as follows: Figure 8 As shown, including:

[0122] An expansion module 81 is used to automatically expand the equation according to the preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain multiple basic parameter curves;

[0123] A transformation module 82 is used to perform pairwise combination transformation on the base parameter curves to expand and obtain multiple temporary parameter curves;

[0124] The identification parameter module 83 is used to select a temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value according to the gas reservoir sensitivity evaluation factor of the temporary parameter curve, and use the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value selected as the target gas reservoir identification parameter;

[0125] A conversion module 84, used for converting the longitudinal wave impedance data body and the shear wave impedance data body into a gas reservoir identification parameter data body according to the target gas reservoir identification parameter construction process and the parameters obtained in the construction process;

[0126] The identification module 85 is used to identify favorable areas for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body.

[0127] A computing device provided by an embodiment of the present invention includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the program executed by the processor implements the aforementioned method for identifying favorable areas for gas reservoir development.

[0128] An embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for identifying favorable areas for gas reservoir development described above is implemented.

[0129] Since the principles of the problems solved by these devices are similar to the aforementioned method for identifying favorable areas for gas reservoir development, the implementation of the devices can refer to the implementation of the aforementioned method, and the repeated parts will not be repeated.

[0130] The method and device for identifying favorable gas reservoir development areas provided by the embodiment of the present invention automatically expand the equation according to the preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain a plurality of basic parameter curves; perform pairwise combination transformation on the basic parameter curves to expand and obtain a plurality of temporary parameter curves; calculate the gas reservoir sensitivity evaluation factor of each temporary parameter curve, and select the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter; according to the process of constructing the target gas reservoir identification parameter and the parameters obtained in the construction process, convert the longitudinal wave impedance data body and the shear wave impedance data body into a gas reservoir identification parameter data body; and identify the favorable gas reservoir development area according to the distribution range of the abnormal values ​​of the gas reservoir identification parameter data body. The method for identifying favorable areas for gas reservoir development provided by an embodiment of the present invention selects the parameters represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter to facilitate confirmation that the gas layer section is the section with the highest gas reservoir sensitivity. The depth section with the strongest gas reservoir sensitivity is identified through the gas reservoir sensitivity evaluation factor, that is, the depth section with the most drastic change (i.e., abnormal fluctuation) in the gas reservoir sensitivity evaluation factor. This depth section just represents the favorable area for gas reservoir development. The above scheme makes the judgment result of the favorable area for gas reservoir development accurate and is relatively easy to implement, which solves the problems of difficulty in new discovery of favorable areas for gas reservoir development, high exploration investment cost and high drilling risk, and provides strong technical support for comprehensive evaluation of gas fields and well site deployment.

[0131] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0132] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The present invention is a block or a plurality of blocks. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for identifying favorable areas for gas reservoir development, characterized in that: include: Automatically expand the equation according to the preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain multiple basic parameter curves; Perform pairwise combination transformation on the base parameter curves to expand and obtain multiple temporary parameter curves; Calculate the gas reservoir sensitivity evaluation factor of each temporary parameter curve, and select the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter; According to the process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, the longitudinal wave impedance data volume and the shear wave impedance data volume are converted into a gas reservoir identification parameter data volume; Based on the distribution range of abnormal values ​​of the gas reservoir identification parameter data body, the favorable area for gas reservoir development is identified.

2. The method according to claim 1, characterized in that The automatic expansion equation according to the preset elastic properties expands the longitudinal wave impedance logging curve and the shear wave impedance logging curve to obtain multiple basic parameter curves, including: According to the longitudinal wave impedance logging curve and the shear wave impedance logging curve, the mean values ​​of the longitudinal wave impedance and the shear wave impedance are calculated respectively; The mean value of the longitudinal wave impedance, the mean value of the transverse wave impedance, the longitudinal wave impedance logging curve and the transverse wave impedance logging curve are substituted into the elastic property automatic expansion equation for calculation by sequentially taking values ​​of the expansion angle θ from the range of -90° to 90° according to the preset step length; the basic parameter curves K(θ1), K(θ2) and K(θ i ); ... The elastic property automatic expansion equation is: in: I p0 represents the mean longitudinal wave impedance, I s0 represents the mean value of shear wave impedance; I p represents the longitudinal wave impedance logging curve, I s It represents the shear wave impedance logging curve; θ represents the expansion angle, a=(cosθ+sinθ), b=-2sinθ; K(θ) represents a basis parameter curve.

3. The method according to claim 2, characterized in that The base parameter curves are transformed in pairs to obtain multiple temporary parameter curves, including: Substitute the basis parameter curve into the following combined transformation equation: in: S1 represents the angle θ p The basis parameter curve K(θ p ), S2 represents the angle θ q The basis parameter curve K(θ q ), Indicates the angle of change, represents a temporary parameter curve; Through From the range of -90° to 90°, take values ​​in sequence according to the preset step length to obtain a temporary parameter curve 4. The method according to claim 1, characterized in that Temporary parameter curves include: gas layer section, lithology background and water layer section; The step of calculating the gas reservoir sensitivity evaluation factor of each temporary parameter curve and selecting the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value as the target gas reservoir identification parameter includes: For each temporary parameter curve corresponding to each pair of basic parameter curves, the mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background are statistically calculated; The mean and variance of the temporary parameter curve of the gas layer section, the mean and variance of the temporary parameter curve of the water layer section, and the mean and variance of the temporary parameter curve of the lithology background are input into the calculation formula of the gas reservoir sensitivity evaluation factor to obtain the gas reservoir sensitivity evaluation factor of each temporary parameter curve; Selecting the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor corresponding to each pair of basic parameter curves matched with each other as the final parameter curve corresponding to the basic parameter curves matched with each other; The parameter represented by the final parameter curve with the highest gas reservoir sensitivity evaluation factor among the final parameter curves is determined as the target gas reservoir identification parameter.

5. The method according to claim 4, characterized in that The calculation formula of the gas reservoir sensitivity evaluation factor is: I=(G m -N m ) / V G -(W m -N m ) / V w in: G m Represents the mean value of the gas layer segment of the parameter curve, N m represents the mean value of the background lithology of the parameter curve, W m represents the mean value of the water layer segment of the parameter curve, V G V represents the variance of the gas layer segment of the parameter curve, w represents the variance of the water layer section of the parameter curve, and I represents the gas reservoir sensitivity evaluation factor.

6. The method according to claim 3, characterized in that The process of constructing the target gas reservoir identification parameters and the parameters obtained in the construction process, converting the longitudinal wave impedance data volume and the shear wave impedance data volume into a gas reservoir identification parameter data volume, comprises: Record the expansion angle θ of the base parameter curve in the process of calculating the target gas reservoir identification parameters p and θ q and changing angles Calculate the mean value of the longitudinal wave impedance data volume and the mean value of the shear wave impedance data volume; The mean of the longitudinal wave impedance data volume, the mean of the shear wave impedance data volume, the longitudinal wave impedance data volume, the shear wave impedance data volume and θ p Enter the elastic property to automatically expand the equation to obtain K(θ P ); The mean of the longitudinal wave impedance data volume, the mean of the shear wave impedance data volume, the longitudinal wave impedance data volume, the shear wave impedance data volume and θ q Enter the elastic property to automatically expand the equation to obtain K(θ q ); K(θ P )、K(θ q )and Substituting into the combined transformation equation, we get Said The data body represented is the target gas reservoir identification parameter data body.

7. The method according to claim 1, characterized in that The method of identifying favorable areas for gas reservoir development based on the abnormal value distribution range of the gas reservoir identification parameter data body includes: The value range of the target gas reservoir identification parameter in the gas layer section is used as the abnormal value distribution range of the gas reservoir identification parameter data body; According to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body, the gas reservoir identification parameter data body is delineated to obtain a spatial distribution range, and the spatial distribution range is used to represent a favorable area for developing gas reservoirs.

8. A device for identifying favorable areas for gas reservoir development, characterized in that: include: An expansion module, used to automatically expand the equation according to preset elastic properties, expand the longitudinal wave impedance logging curve and the shear wave impedance logging curve, and obtain multiple basic parameter curves; A transformation module is used to perform pairwise combination transformation on the base parameter curves to expand and obtain multiple temporary parameter curves; An identification parameter module is used to select a temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value according to the gas reservoir sensitivity evaluation factor of the temporary parameter curve, and use the parameter represented by the temporary parameter curve with the highest gas reservoir sensitivity evaluation factor value selected as the target gas reservoir identification parameter; A conversion module, used for converting a longitudinal wave impedance data body and a transverse wave impedance data body into a gas reservoir identification parameter data body according to a target gas reservoir identification parameter construction process and parameters obtained in the construction process; The identification module is used to identify favorable areas for gas reservoir development according to the distribution range of abnormal values ​​of the gas reservoir identification parameter data body.

9. A computing device, characterized in that include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the program executed by the processor implements the method for identifying favorable areas for gas reservoir development as described in claims 1-6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for identifying favorable areas for gas reservoir development described in claims 1-6 is implemented.

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