Rock stratum gas production intensity prediction method and device, computer device and storage medium

Abstract

The application discloses a rock stratum gas production strength prediction method and device, computer equipment and a storage medium, and relates to the technical field of oil and gas field development. The method comprises the following steps: performing rock stratum testing on a target rock stratum, and determining the brittleness index, the compressive strength and the horizontal stress difference of the target rock stratum according to the testing data; determining the target compressibility index of the target rock stratum based on the brittleness index, the compressive strength and the horizontal stress difference; and determining the predicted gas production strength of the target rock stratum after fracturing from a target fitting curve based on the target compressibility index, wherein the compressibility index and the gas production strength are in a positive correlation relationship. According to the method provided in the application, the brittleness index, the compressive strength and the horizontal stress difference are combined to form the compressibility index, and the rock stratum gas production strength is predicted according to the compressibility index, so that the prediction accuracy is improved.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, and in particular to a method, apparatus, computer equipment and storage medium for predicting gas production intensity in rock formations. Background Technology

[0002] In the process of tight gas reservoir development, it is necessary to carry out fracturing operations on the rock strata to form a complex network of fractures, providing gas production channels for the gas-bearing reservoir and thus increasing the gas production intensity.

[0003] Before fracturing a rock formation, it is necessary to predict the expected gas production intensity after fracturing. Based on the expected gas production intensity, the rock formation to be fractured can be selected. The brittleness index is used for prediction in related technologies.

[0004] However, in actual production, the brittleness index has a low degree of fit with the gas extraction intensity, and using the brittleness index for prediction results in a low accuracy rate for gas extraction intensity prediction. Summary of the Invention

[0005] This application provides a method, apparatus, computer equipment, and storage medium for predicting the intensity of gas production in rock formations. The technical solution is as follows:

[0006] On one hand, embodiments of this application provide a method for predicting the intensity of gas production in rock formations, the method comprising:

[0007] Rock strata are tested, and the brittleness index, compressive strength and horizontal stress difference of the target rock strata are determined based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing, the compressive strength characterizes the ultimate ability of the rock to resist failure under external force, and the horizontal stress difference characterizes the ability of the rock to extend and change cracks during the fracturing stage.

[0008] The target compressibility index of the target rock stratum is determined based on the brittleness index, the compressive strength, and the horizontal stress difference.

[0009] Based on the target compressibility index, the expected gas production intensity after fracturing the target rock formation is determined from the target fitting curve, wherein the compressibility index is positively correlated with the gas production intensity.

[0010] On the other hand, embodiments of this application provide a device for predicting the intensity of gas production in rock formations, the device comprising:

[0011] The first determining module is used to conduct rock layer tests on the target rock layer and determine the brittleness index, compressive strength and horizontal stress difference of the target rock layer based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing. The compressive strength characterizes the rock's ultimate ability to resist failure under external force. The horizontal stress difference characterizes the ability of the rock to extend and change cracks during the fracturing stage.

[0012] The second determining module is used to determine the target compressibility index of the target rock layer based on the brittleness index, the compressive strength, and the horizontal stress difference;

[0013] The third determining module is used to determine the expected gas production intensity after fracturing the target rock formation from the target fitting curve based on the target compressibility index, wherein the compressibility index is positively correlated with the gas production intensity.

[0014] On the other hand, embodiments of this application provide a computer device including a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the method for predicting the gas production intensity of rock formations as described above.

[0015] On the other hand, embodiments of this application provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for predicting gas production intensity in rock formations as described above.

[0016] On the other hand, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for predicting gas production intensity in rock formations provided in various alternative implementations of the above aspects.

[0017] The technical solutions provided in this application have at least the following beneficial effects:

[0018] In this embodiment, the target compressibility index of the target rock layer is determined based on the brittleness index, compressive strength, and horizontal stress difference parameters of the target rock layer. The gas production intensity corresponding to the target compressibility index is determined based on the target fitting curve, thereby obtaining the expected gas production intensity after fracturing the target rock layer. Compared with related technologies, which only use a single brittleness index for prediction, the prediction accuracy can be improved. Furthermore, selecting the rock layer to be fractured based on the predicted gas production intensity avoids ineffective fracturing of the rock layer, which helps to increase production capacity and reduce costs. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of the fitting curve between the brittleness index and gas production intensity in related technologies is shown;

[0021] Figure 2 A flowchart illustrating a method for predicting gas production intensity in rock formations provided in an exemplary embodiment of this application is shown;

[0022] Figure 3 A flowchart illustrating a method for predicting gas production intensity in rock formations provided in another exemplary embodiment of this application is shown;

[0023] Figure 4 A flowchart illustrating the process of generating a target fitting curve according to an exemplary embodiment of this application is shown;

[0024] Figure 5 A schematic diagram of a target fitting curve provided in an exemplary embodiment of this application is shown;

[0025] Figure 6 A structural block diagram of a rock formation gas production intensity prediction device provided in one embodiment of this application is shown;

[0026] Figure 7 A structural block diagram of a computer device provided in an exemplary embodiment of this application is shown. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0028] In this article, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0029] In related technologies, before fracturing rock formations, the brittleness index is used to determine the compressibility of the rock formations. Rock formations with a high brittleness index are then fractured to increase gas production intensity. However, the brittleness index has a low correlation with the gas production intensity of the rock formations. Figure 1 As shown, the data for fitting the brittleness index and gas production intensity of multiple rock strata are relatively discrete and the fitting degree is low.

[0030] Therefore, if the expected gas production intensity after fracturing a rock formation is judged solely by the brittleness index, the predicted gas production intensity may not match the actual gas production intensity. This could result in ineffective fracturing of rock formations, increasing costs and failing to improve production efficiency. In this embodiment, however, the compressibility index of the target rock formation is obtained by comprehensively considering the brittleness index, compressive strength, and horizontal stress difference. The gas production intensity is then predicted using the compressibility index, improving prediction accuracy.

[0031] Please refer to Figure 2 The diagram illustrates a flowchart of a method for predicting gas production intensity in rock formations, provided in an exemplary embodiment of this application. The method includes:

[0032] Step 201: Conduct rock layer tests on the target rock layer and determine the brittleness index, compressive strength, and horizontal stress difference of the target rock layer based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing, the compressive strength characterizes the ultimate ability of the rock to resist damage under external force, and the horizontal stress difference characterizes the ability of the rock to extend and change cracks during the fracturing stage.

[0033] In one possible implementation, before predicting the gas extraction intensity of the target rock layer, a rock layer test is first performed on the target rock layer to obtain various parameters of the target rock layer. Then, computer equipment can determine the brittleness index, compressive strength, and horizontal stress difference based on the various parameters of the target rock layer.

[0034] Among them, rock brittleness is one of the important factors affecting the formation of multiple cracks. The brittleness index characterizes the ability of a rock to undergo plastic deformation before it fractures. The brittleness index is inversely correlated with the ability to undergo plastic deformation. That is, the larger the brittleness index, the less likely the rock is to undergo plastic deformation before it fractures and the easier it is to form a complex crack network. Conversely, the smaller the brittleness index, the easier the rock is to undergo plastic deformation before it fractures and the less likely it is to form a complex crack network.

[0035] Compressive strength characterizes the ultimate ability of a rock to resist damage under external forces. The lower the compressive strength, the easier the rock is to break and the easier it is to form cracks during fracturing, which can improve the gas extraction intensity.

[0036] The horizontal stress difference characterizes the ability of cracks to extend and change during the rock fracturing stage. When the horizontal stress difference is large, the direction of maximum stress dominates the direction of crack extension, the directionality is more significant, and the crack morphology is simple. When the horizontal stress difference is small, the direction of crack extension is diverse, and it is easier to form a complex crack network, thereby increasing the gas production intensity.

[0037] Step 202: Determine the target compressibility index of the target rock stratum based on the brittleness index, compressive strength, and horizontal stress difference.

[0038] Since compressive strength can reflect the compressibility state of rock strata before cracking, brittleness index can reflect the deformation state of rock strata during micro-cracking, and horizontal stress difference can reflect the crack extension and change state of rock strata during fracturing, in one possible implementation, the state of rock strata before cracking, micro-cracking, and fracturing is comprehensively considered to obtain the target compressibility index, thereby improving the accuracy of gas production intensity prediction.

[0039] Step 203: Based on the target compressibility index, determine the expected gas production intensity after fracturing the target rock formation from the target fitting curve, wherein the compressibility index is positively correlated with the gas production intensity.

[0040] In one possible implementation, the computer device determines the expected gas production intensity after fracturing the target rock formation based on the obtained target compressibility index and a pre-stored target fitting curve. The target fitting curve represents the correspondence between the compressibility index and the gas production intensity; the compressibility index and gas production intensity are positively correlated, meaning the higher the compressibility index of the rock formation, the stronger its gas production intensity.

[0041] Optionally, the determination of whether to fracturing the corresponding rock formation can be based on the obtained expected gas production intensity. In one possible application scenario, the compressibility index of multiple candidate rock formations can be obtained, and the expected gas production intensity of the candidate rock formations can be determined based on the compressibility index. When selecting a target rock formation for fracturing among the candidate rock formations, the rock formation with the higher expected gas production intensity can be selected as the target rock formation, thereby achieving optimal selection of the fracturing rock formation.

[0042] In summary, in this embodiment, the target compressibility index of the target rock stratum is determined based on its brittleness index, compressive strength, and horizontal stress difference parameters. The gas production intensity corresponding to the target compressibility index is then determined based on the target fitting curve, thereby obtaining the expected gas production intensity after fracturing the target rock stratum. Compared with related technologies that rely solely on a single brittleness index for prediction, this method improves prediction accuracy. Furthermore, selecting the rock stratum for fracturing based on the predicted gas production intensity avoids ineffective fracturing, which helps increase production capacity and reduce costs.

[0043] Please refer to Figure 3 This illustrates a flowchart of a method for predicting gas production intensity in rock formations, provided in another exemplary embodiment of this application. The method includes:

[0044] Step 301: Determine the rock mechanical parameters of the target rock layer based on the well logging data. The rock mechanical parameters include Young's modulus, Poisson's ratio, overlying rock pressure, and pore pressure.

[0045] In one possible implementation, the brittleness index, compressive strength, and horizontal stress difference are determined based on rock mechanical parameters. These parameters include Young's modulus, Poisson's ratio, overlying strata pressure, and pore pressure.

[0046] Young's modulus is the elastic modulus along the longitudinal direction, and it is an indicator of how easily a material undergoes elastic deformation. Poisson's ratio is the ratio of the absolute values ​​of the transverse normal strain to the axial normal strain when a material is under uniaxial tension or compression, reflecting the elastic constant of the material's transverse deformation. In this embodiment, Young's modulus and Poisson's ratio are rock mechanics parameters characterizing the brittleness of rock strata. Young's modulus characterizes the ability of a rock strata to retain fractures after being fractured by compression, and it is mainly related to the internal structure, mineral composition, texture, and porosity of the rock strata; Poisson's ratio characterizes the ability of a rock strata to fracture under pressure.

[0047] Overlying strata pressure refers to the pressure exerted by the total weight of the formation matrix and fluids within the pores above the target stratum. The formation matrix refers to the rock, and the fluids within the pores include oil, gas, and water. Pore pressure is the pressure of the fluids within the pores of the stratum.

[0048] In one possible implementation, determining the rock mechanical parameters of a rock stratum may include the following steps:

[0049] Step 1: Perform sonic logging and density logging on the target rock formation to obtain the P-wave transit time, S-wave transit time, and rock density of the target rock formation;

[0050] In one possible implementation, acoustic logging is performed on the target rock formation to obtain the P-wave and S-wave transit times. Acoustic logging involves placing a controlled acoustic source into the well. The source emits sound waves that cause vibrations in surrounding particles, generating P-waves and S-waves in the formation. These sound waves serve as carriers of formation information and are received and recorded by a downhole receiver. The P-wave and S-wave transit times can then be obtained from the recorded acoustic data.

[0051] Similarly, to obtain the rock density of the target rock formation, density logging is performed on the target rock formation. Density logging is a logging method that measures the bulk density of a formation based on the Compton effect, and the rock density can be obtained from the logging results.

[0052] Step 2: Determine the dynamic Young's modulus and dynamic Poisson's ratio based on the P-wave transit time, S-wave transit time, and rock density, and obtain the overlying strata pressure based on the rock density.

[0053] In one possible implementation, the computer device can calculate the dynamic Young's modulus and dynamic Poisson's ratio based on the P-wave transit time, S-wave transit time, and rock density, as follows:

[0054]

[0055]

[0056] Where E refers to the dynamic Young's modulus, PR refers to the dynamic Poisson's ratio, and Δt p For the P-wave time difference, Δt s ρ represents the transverse wave time difference, and ρ refers to the rock density.

[0057] It can also calculate the pressure of the overlying strata, and the calculation method is as follows:

[0058] P0 = 0.001·ρgH

[0059] Where g refers to gravitational acceleration and H is the depth of the target rock layer.

[0060] Step 302: Determine the brittleness index based on Young's modulus and Poisson's ratio.

[0061] There are differences between static Young's modulus and static Poisson's ratio and dynamic Young's modulus and dynamic Poisson's ratio. Static Young's modulus and static Poisson's ratio are more reflective of the brittleness index of rocks. Therefore, in one possible implementation, after determining the dynamic Young's modulus and dynamic Poisson's ratio of the target rock layer, they need to be converted into static Young's modulus and static Poisson's ratio. The computer equipment determines the brittleness index of the target rock layer based on the converted static Young's modulus and static Poisson's ratio.

[0062] Optionally, the conversion between dynamic Young's modulus and dynamic Poisson's ratio and static Young's modulus and static Poisson's ratio can be performed based on the linear relationship between the two.

[0063] The brittleness index is determined based on static Young's modulus and static Poisson's ratio as follows:

[0064] BRIT = (ES + PRS) / 2

[0065] Among them, BRIT refers to the brittleness index, ES refers to the static Young's modulus, and PRS refers to the static Poisson's ratio.

[0066] Step 303: Determine the compressive strength based on Young's modulus and the clay content of the target rock layer.

[0067] Clayey material refers to clastic material with a particle diameter of less than 0.01 mm, and clayey content refers to the ratio of clayey volume to the total rock volume. In one possible implementation, determining the compressive strength based on Young's modulus and the clayey content of the target rock layer may include the following steps:

[0068] Step 1: Perform natural gamma logging on the target rock formation to obtain the natural gamma curve;

[0069] The higher the clay content in a rock stratum, the stronger its radioactivity. Therefore, to determine the clay content in a rock stratum, the clay content can be analyzed based on the logging results of natural gamma ray logging. Natural gamma ray logging is a logging method that uses a gamma ray detector to measure the total natural gamma intensity of the formation rocks to study the properties of the formation profile. After obtaining the natural gamma curve through natural gamma logging, computer equipment can analyze the natural gamma curve to determine the clay content of the target rock stratum.

[0070] Step 2: Determine the clay content based on the natural gamma curve;

[0071] Optionally, when determining the clay content based on the natural gamma curve, a relative value calculation method can be used, as follows:

[0072]

[0073]

[0074] Among them, I GR V is the mud content index. sh GR represents the natural gamma value of the target rock layer, specifically the mud content. max The natural gamma value of pure mudstone and shale, GR min The value represents the natural gamma of a pure sandstone layer, and GCUR is the Hillcatch index, which is related to the stratigraphy.

[0075] Step 3: Determine the compressive strength based on Young's modulus and clay content.

[0076] Optionally, the compressive strength can be determined based on the static Young's modulus and clay content, calculated as follows:

[0077] S c =0.0045·ES(1-V sh +0.008·ES·V sh

[0078] Among them, S c This refers to compressive strength.

[0079] Step 304: Determine the horizontal stress difference based on the pressure of the overlying strata and the pore pressure.

[0080] In one possible implementation, horizontal geostress is calculated based on the Huang model. The Huang model posits that geostress in rock strata is the result of the combined effects of vertical stress and geological structural stress; therefore, to determine horizontal geostress, it is first necessary to determine the vertical stress of the rock strata.

[0081] Optionally, the vertical stress can be determined based on the pressure of the overlying strata and the pore pressure, calculated as follows:

[0082] σ z =P0-αP p

[0083] Where, σ z Vertical stress, P0 is the pressure of the overlying strata, P p Here, α represents the pore pressure, and α is the contribution coefficient of pore pressure to the effective stress. Optionally, α and P... p The calculation method is as follows:

[0084]

[0085] Where, Δt mp The longitudinal wave time difference, Δt, refers to the longitudinal wave time difference of the rock skeleton. ms The transverse wave time difference, Δt, refers to the time difference of the rock skeleton. p The total P-wave transit time, Δt, includes the rock skeleton and the fluids within the rock strata. s The total transverse wave transit time, ρ, includes the rock skeleton and the fluids within the rock strata. ma The highest rock density in the area where the target rock stratum is located.

[0086] P p =G p ·H

[0087] Among them, G p Refers to the pore pressure gradient.

[0088] After determining the vertical stress, it is also necessary to determine the geological structural stress coefficient. Optionally, the determination of the horizontal structural stress coefficient may include the following steps:

[0089] Step 1: Conduct a small-scale hydraulic fracturing test on the target rock layer to obtain the hydraulic fracturing test curve;

[0090] Small-scale fracturing tests involve conducting fracturing experiments without proppant using a small volume of fracturing fluid identical to that used in formal fracturing. These tests yield fracturing curves, which can then be used to determine the characteristics of fracture formation and propagation pressures.

[0091] Step 2: Determine the horizontal tectonic stress coefficient based on the fracturing test curve. The horizontal tectonic stress coefficient includes the maximum horizontal tectonic stress coefficient and the minimum horizontal tectonic stress coefficient.

[0092] The maximum and minimum horizontal tectonic stress coefficients can be obtained based on the characteristics of crack formation and propagation pressure. Optionally, in this embodiment, the maximum horizontal tectonic stress coefficient can be 0.66, and the minimum horizontal tectonic stress coefficient can be 0.42.

[0093] After determining the vertical stress and the horizontal tectonic stress coefficient, the computer equipment can determine the maximum and minimum horizontal ground stress based on the vertical stress and the horizontal tectonic stress coefficient using the Huang model.

[0094] The maximum horizontal ground stress can be obtained based on the vertical stress and the maximum horizontal tectonic stress coefficient, and the calculation method is as follows:

[0095]

[0096] Where, σ H That is, the maximum horizontal ground stress, and ω1 is the maximum horizontal tectonic stress coefficient.

[0097] The minimum horizontal ground stress can be obtained based on the vertical stress and the minimum horizontal tectonic stress coefficient, and the calculation method is as follows:

[0098]

[0099] Where, σ h That is, the maximum horizontal ground stress, and ω2 is the minimum horizontal tectonic stress coefficient.

[0100] Finally, the computer equipment determines the difference between the maximum and minimum horizontal ground stress as the horizontal ground stress difference, i.e., Δσ = σ H -σ h .

[0101] Step 305: Normalize the compressive strength and the horizontal stress difference to obtain the compressive strength index and the stress difference index.

[0102] Because the compressive strength index and horizontal stress difference vary considerably, a normalization process is performed on the compressive strength and horizontal stress difference to facilitate fitting of these parameters to the brittleness index, yielding the compressive strength index and stress difference index. During the normalization process, the compressive strength and horizontal stress difference of multiple rock layers, including the target rock layer, are obtained. The normalization method is as follows:

[0103]

[0104]

[0105] Among them, S c I represents the compressive strength index, and S... cminS represents the minimum compressive strength of multiple rock strata. cmax The maximum compressive strength of multiple rock strata is given by ΔσI, where Δσ is the stress difference exponent. min Δσ represents the minimum horizontal stress difference among multiple rock strata. max This represents the maximum value of the horizontal stress difference among multiple rock strata.

[0106] Step 306: The product of the brittleness index, compressive strength index, and stress difference index is determined as the target compressibility index of the target rock layer.

[0107] Optionally, after normalizing the compressive strength and the difference in horizontal ground stress, it can be combined with the brittleness index to obtain the target compressibility index, which is calculated as follows:

[0108] CI = S c I·ΔσI·BRIT

[0109] CI stands for Compression Index.

[0110] Step 307: Based on the target compressibility index, determine the expected gas production intensity after fracturing the target rock formation from the target fitting curve, wherein the compressibility index is positively correlated with the gas production intensity.

[0111] The implementation method of this step can refer to step 203 above, and will not be repeated here in this embodiment.

[0112] In this embodiment, the brittleness index, compressive strength, and horizontal stress difference are calculated by integrating basic rock mechanics parameters. The compressibility index is obtained by integrating multiple parameters involved in the fracturing process to ensure the accuracy of gas production intensity prediction using the compressibility index.

[0113] In one possible implementation, the fitting curve of compressibility index and gas production intensity is obtained by fitting the compressibility index of multiple rock formations with their actual gas production intensity data, providing support for determining the expected gas production intensity of the target rock formation.

[0114] Please refer to Figure 4 The diagram illustrates a flowchart of the process for generating a target fitting curve provided in an exemplary embodiment of this application.

[0115] Step 401: Conduct rock layer tests on multiple sample rock layers, and determine the sample brittleness index, sample compressive strength, and sample horizontal stress difference of the sample rock layers based on the test data.

[0116] In one possible implementation, since the target fitting curve is determined based on the compressibility index of multiple rock layers and the gas production intensity, it is necessary to first test multiple sample rock layers. After the rock layer test, test data of multiple sample rock layers will be obtained. Then, the computer equipment can obtain the sample brittleness index, sample compressive strength and sample horizontal stress difference of multiple sample rock layers based on the test data.

[0117] Optionally, the determination methods for the sample brittleness index, sample compressive strength, and sample horizontal force difference of the sample rock layer can refer to steps 302 to 304 above, which will not be repeated here in this embodiment.

[0118] Step 402: Determine the compressibility index of the sample rock strata based on the sample brittleness index, sample compressive strength, and sample horizontal stress difference.

[0119] Optionally, the compressibility index of each sample is obtained based on the sample brittleness index, sample compressive strength, and sample horizontal stress difference of each sample rock layer. The method for determining the sample compressibility index can refer to steps 305 and 306 above, which will not be repeated here in this embodiment.

[0120] Step 403: Perform curve fitting on the sample compressibility index and the sample gas production intensity corresponding to the sample rock layer to obtain the target fitting curve.

[0121] Optionally, the computer equipment performs curve fitting based on the compressibility index of multiple samples and the gas production intensity corresponding to each sample rock layer to obtain a target fitting curve. The sample gas production intensity refers to the actual gas production intensity of the sample rock layer, and the target fitting curve is obtained by fitting measured data.

[0122] Indicative, such as Figure 5 As shown, the computer equipment performs curve fitting between the compressibility index and gas production intensity of the seven sample rock formations to obtain the target fitting curve. Based on the target fitting curve, the corresponding relationship between the compressibility index and gas production intensity can be obtained as follows:

[0123] y = 0.0208e 3.7752x

[0124] Where y refers to gas extraction intensity and x refers to compressibility index.

[0125] Once the compressibility index of the rock strata is obtained, the gas extraction intensity of the rock strata can be obtained according to the above relationship, thus realizing the prediction of the gas extraction intensity of the rock strata.

[0126] In this embodiment, the compressibility index and actual gas production intensity of multiple sample rock formations are obtained. A target fitting curve is obtained by fitting the actual data. The relationship between the compressibility index and the gas production intensity is obtained from the fitting curve, thereby providing support for predicting the gas production intensity of rock formations.

[0127] Please refer to Figure 6 The diagram shows a structural block diagram of a rock formation gas production intensity prediction device provided in one embodiment of this application.

[0128] The first determining module 601 is used to perform rock layer testing on the target rock layer and determine the brittleness index, compressive strength and horizontal stress difference of the target rock layer based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing. The compressive strength characterizes the ultimate ability of the rock to resist failure under external force. The horizontal stress difference characterizes the ability of the rock to extend and change cracks during the fracturing stage.

[0129] The second determining module 602 is used to determine the target compressibility index of the target rock layer based on the brittleness index, the compressive strength and the horizontal stress difference;

[0130] The third determining module 603 is used to determine the expected gas production intensity after fracturing the target rock formation from the target fitting curve based on the target compressibility index, wherein the compressibility index is positively correlated with the gas production intensity.

[0131] Optionally, the first determining module 601 includes:

[0132] The first determining unit is used to determine the rock mechanical parameters of the target rock layer based on well logging data. The rock mechanical parameters include Young's modulus, Poisson's ratio, overlying rock pressure, and pore pressure.

[0133] The second determining unit is used to determine the brittleness index based on the Young's modulus and the Poisson's ratio;

[0134] The third determining unit is used to determine the compressive strength based on the Young's modulus and the clay content of the target rock layer;

[0135] The fourth determining unit is used to determine the horizontal stress difference based on the pressure of the overlying strata and the pore pressure.

[0136] Optionally, the first determining unit is further configured to:

[0137] Sonic logging and density logging were performed on the target rock formation to obtain the P-wave transit time, S-wave transit time and rock density of the target rock formation.

[0138] The dynamic Young's modulus and dynamic Poisson's ratio are determined based on the longitudinal wave transit time, the transverse wave transit time, and the rock density, and the pressure of the overlying strata is obtained based on the rock density.

[0139] Optionally, the second determining unit is further configured to:

[0140] The dynamic Young's modulus and dynamic Poisson's ratio are converted into static Young's modulus and static Poisson's ratio;

[0141] The brittleness index is determined based on the static Young's modulus and the static Poisson's ratio.

[0142] Optionally, the third determining unit is further configured to:

[0143] Natural gamma logging was performed on the target rock formation to obtain the natural gamma curve;

[0144] The mud content was determined based on the natural gamma curve.

[0145] The compressive strength is determined based on the Young's modulus and the clay content.

[0146] Optionally, the fourth determining unit is further configured to:

[0147] The vertical stress is determined based on the pressure of the overlying strata and the pore pressure.

[0148] Based on the vertical stress and the horizontal tectonic stress coefficient, the maximum and minimum horizontal ground stresses are determined using the Huang model.

[0149] The difference between the maximum horizontal ground stress and the minimum horizontal ground stress is defined as the horizontal ground stress difference.

[0150] Optionally, the fourth determining unit is further configured to:

[0151] A small-scale hydraulic fracturing test was performed on the target rock strata to obtain the hydraulic fracturing test curve;

[0152] The horizontal tectonic stress coefficient is determined based on the fracturing test curve, and the horizontal tectonic stress coefficient includes the maximum horizontal tectonic stress coefficient and the minimum horizontal tectonic stress coefficient.

[0153] Based on the vertical stress and the maximum horizontal tectonic stress coefficient, the maximum horizontal ground stress is determined using the Huang model;

[0154] Based on the vertical stress and the minimum horizontal tectonic stress coefficient, the minimum horizontal ground stress is determined using the Huang model.

[0155] Optionally, the second determining module 602 includes:

[0156] The processing unit is used to normalize the compressive strength and the horizontal stress difference to obtain the compressive strength index and the stress difference index.

[0157] The fifth determining unit is used to determine the target compressibility index of the target rock layer by multiplying the brittleness index, the compressive strength index and the stress difference index.

[0158] Optionally, the device further includes:

[0159] The fourth determination module is used to conduct rock layer tests on multiple sample rock layers and determine the sample brittleness index, sample compressive strength, and sample horizontal stress difference of the sample rock layers based on the test data.

[0160] The fifth determining module is used to determine the compressibility index of the sample rock strata based on the sample brittleness index, the sample compressive strength, and the sample horizontal stress difference.

[0161] The fitting module is used to perform curve fitting on the compressibility index of the sample and the gas production intensity corresponding to the sample rock layer to obtain the target fitting curve.

[0162] In summary, in this embodiment of the application, the target compressibility index of the target rock layer is determined based on the brittleness index, compressive strength, and horizontal stress difference parameters of the target rock layer. The gas production intensity corresponding to the target compressibility index is determined based on the target fitting curve, thereby obtaining the expected gas production intensity after fracturing the target rock layer. Compared with related technologies, which only use a single brittleness index for prediction, this method can improve prediction accuracy. Furthermore, selecting the rock layer to be fractured based on the predicted gas production intensity avoids ineffective fracturing of the rock layer, which helps to increase production capacity and reduce costs.

[0163] Please refer to Figure 7 This diagram illustrates a structural block diagram of a computer device provided in an exemplary embodiment of this application. The computer device can be used to implement the rock formation gas extraction intensity prediction method provided in the above embodiments, specifically:

[0164] The computer device 700 includes a central processing unit (CPU) 701, a system memory 704 including random access memory (RAM) 702 and read-only memory (ROM) 703, and a system bus 705 connecting the system memory 704 and the CPU 701. The computer device 700 also includes a basic input / output system (I / O system) 706 to facilitate information transfer between various components within the computer device, and a mass storage device 707 for storing the operating system 713, application programs 714, and other program modules 715.

[0165] The basic input / output system 706 includes a display 708 for displaying information and an input device 709 for user input, such as a mouse or keyboard. Both the display 708 and the input device 709 are connected to the central processing unit 701 via an input / output controller 710 connected to the system bus 705. The basic input / output system 706 may also include the input / output controller 710 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 710 also provides output to a display screen, printer, or other types of output devices.

[0166] The mass storage device 707 is connected to the central processing unit 701 via a mass storage controller (not shown) connected to the system bus 705. The mass storage device 707 and its associated computer-readable storage media provide non-volatile storage for the computer device 700. That is, the mass storage device 707 may include computer-readable storage media (not shown), such as a hard disk or a compact disc read-only memory (CD-ROM) drive.

[0167] Without loss of generality, the computer-readable storage medium may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable storage instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other solid-state storage devices, CD-ROM, digital versatile disc (DVD) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that the computer storage medium is not limited to the above-mentioned types. The system memory 704 and mass storage device 707 described above can be collectively referred to as memory.

[0168] The memory stores one or more programs, which are configured to be executed by one or more central processing units 701. The one or more programs contain instructions for implementing the above method embodiments, and the central processing unit 701 executes the one or more programs to implement the methods provided by the various method embodiments described above.

[0169] According to various embodiments of this application, the computer device 700 can also be connected to a remote server on a network, such as the Internet. That is, the computer device 700 can be connected to a network 712 via a network interface unit 711 connected to the system bus 705, or it can use the network interface unit 711 to connect to other types of networks or remote server systems (not shown).

[0170] The memory further includes one or more programs stored in the memory, and the one or more programs include steps performed by a computer device in the methods provided in the embodiments of this application.

[0171] This application provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for predicting the gas production intensity of rock formations as described above.

[0172] This application provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the rock formation gas production intensity prediction method provided in various optional implementations of the above aspects.

[0173] Those skilled in the art will recognize that the functions described in the embodiments of this application in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0174] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for predicting the intensity of gas production from rock formations, characterized in that, The method includes: The target rock strata are subjected to rock layer testing, and the brittleness index, compressive strength, and horizontal stress difference of the target rock strata are determined based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing, the compressive strength characterizes the ultimate ability of the rock to resist failure under external force, and the horizontal stress difference characterizes the ability of the rock to extend and change fractures during the fracturing stage. The rock layer testing and determination of the brittleness index, compressive strength, and horizontal stress difference of the target rock strata include: performing sonic logging and density logging on the target rock strata to obtain the P-wave transit time, S-wave transit time, and rock density of the target rock strata; determining the dynamic Young's modulus and dynamic Poisson's ratio based on the P-wave transit time, the S-wave transit time, and the rock density, and obtaining the overlying strata pressure based on the rock density; the rock mechanical parameters include Young's modulus, Poisson's ratio, overlying strata pressure, and pore pressure; converting the dynamic Young's modulus and dynamic Poisson's ratio into static Young's modulus and static Poisson's ratio; and determining the static Young's modulus based on the... The brittleness index is determined by the static Poisson's ratio; natural gamma logging is performed on the target rock layer to obtain a natural gamma curve; the clay content is determined based on the natural gamma curve; the compressive strength is determined based on the Young's modulus and the clay content; the vertical stress is determined based on the overlying rock pressure and the pore pressure; a small-scale fracturing test is performed on the target rock layer to obtain a fracturing test curve; the horizontal tectonic stress coefficient is determined based on the fracturing test curve, the horizontal tectonic stress coefficient including a maximum horizontal tectonic stress coefficient and a minimum horizontal tectonic stress coefficient; the maximum horizontal stress is determined based on the vertical stress and the maximum horizontal tectonic stress coefficient using the Huang model; the minimum horizontal stress is determined based on the vertical stress and the minimum horizontal tectonic stress coefficient using the Huang model; the difference between the maximum horizontal stress and the minimum horizontal stress is determined as the horizontal stress difference; the compressive strength and the horizontal stress difference are normalized to obtain the compressive strength index and the stress difference index. The product of the brittleness index, the compressive strength index, and the stress difference index is determined as the target compressibility index of the target rock stratum. Based on the target compressibility index, the expected gas production intensity after fracturing the target rock formation is determined from the target fitting curve. The target fitting curve is used to characterize the correspondence between the compressibility index and the gas production intensity. The target fitting curve is obtained by curve fitting based on the sample compressibility index of multiple samples and the sample gas production intensity corresponding to each of the multiple sample rock formations. The compressibility index and the gas production intensity are positively correlated. The method further includes: Multiple sample rock layers were tested, and the sample brittleness index, sample compressive strength, and sample horizontal stress difference were determined based on the test data. The compressibility index of the sample rock strata is determined based on the sample brittleness index, the sample compressive strength, and the sample horizontal stress difference. The target fitting curve is obtained by performing curve fitting on the compressibility index of the sample and the gas production intensity corresponding to the sample rock layer.

2. A device for predicting the intensity of gas production from rock formations, characterized in that, The device includes: The first determining module is used to conduct rock layer tests on the target rock layer and determine the brittleness index, compressive strength and horizontal stress difference of the target rock layer based on the test data. The brittleness index characterizes the ability of the rock to undergo plastic deformation before fracturing. The compressive strength characterizes the rock's ultimate ability to resist failure under external force. The horizontal stress difference characterizes the ability of the rock to extend and change cracks during the fracturing stage. The first determining module is configured to: perform acoustic logging and density logging on the target rock formation to obtain the P-wave transit time, S-wave transit time, and rock density of the target rock formation; determine the dynamic Young's modulus and dynamic Poisson's ratio based on the P-wave transit time, the S-wave transit time, and the rock density, and obtain the overlying strata pressure based on the rock density; the rock mechanical parameters include Young's modulus, Poisson's ratio, overlying strata pressure, and pore pressure; convert the dynamic Young's modulus and dynamic Poisson's ratio into static Young's modulus and static Poisson's ratio; determine the brittleness index based on the static Young's modulus and static Poisson's ratio; perform natural gamma logging on the target rock formation to obtain a natural gamma curve; and determine the clay content based on the natural gamma curve. The compressive strength is determined based on the Young's modulus and the clay content; the vertical stress is determined based on the overlying strata pressure and the pore pressure; a small-scale hydraulic fracturing test is performed on the target strata to obtain a fracturing test curve; the horizontal tectonic stress coefficient is determined based on the fracturing test curve, the horizontal tectonic stress coefficient including a maximum horizontal tectonic stress coefficient and a minimum horizontal tectonic stress coefficient; the maximum horizontal stress is determined based on the vertical stress and the maximum horizontal tectonic stress coefficient using the Huang's model; the minimum horizontal stress is determined based on the vertical stress and the minimum horizontal tectonic stress coefficient using the Huang's model; the difference between the maximum horizontal stress and the minimum horizontal stress is determined as the horizontal stress difference. The second determining module is used to normalize the compressive strength and the horizontal stress difference to obtain the compressive strength index and the stress difference index; the product of the brittleness index, the compressive strength index, and the stress difference index is determined as the target compressibility index of the target rock layer; the third determining module is used to determine the expected gas production intensity after fracturing of the target rock layer from the target fitting curve based on the target compressibility index, the target fitting curve is used to characterize the correspondence between the compressibility index and the gas production intensity; the target fitting curve is obtained by curve fitting based on the sample compressibility index of multiple samples and the sample gas production intensity corresponding to each of the multiple sample rock layers, wherein the compressibility index and the gas production intensity are positively correlated. The device is also used for: Multiple sample rock layers were tested, and the sample brittleness index, sample compressive strength, and sample horizontal stress difference were determined based on the test data. The compressibility index of the sample rock strata is determined based on the sample brittleness index, the sample compressive strength, and the sample horizontal stress difference. The target fitting curve is obtained by performing curve fitting on the compressibility index of the sample and the gas production intensity corresponding to the sample rock layer.

3. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set, or instruction set, the at least one instruction, the at least one program, the code set, or instruction set being loaded and executed by the processor to implement the method for predicting gas production intensity in rock formations as described in claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or instruction set is loaded and executed by a processor to implement the method for predicting gas production intensity in rock formations as described in claim 1.

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