Method for predicting gas saturation of shale reservoir based on fracture index

Abstract

The invention discloses a method for predicting gas saturation of a shale reservoir based on a fracture index, which belongs to the technical field of petroleum and natural gas exploration and development, and is characterized by comprising the following steps of: a, selecting faults around coordinates of a predicted target area according to geophysical data; b, obtaining a fault displacement G of the fault, a distance Dt between a fault hanging wall section coordinate and a predicted target area coordinate, and a distance Db between a fault footwall section coordinate and the predicted target area coordinate; c, calculating a fracture index F; and d, predicting the gas saturation of the shale reservoir in the target area. According to the method, on the basis of the fracture index, by utilizing the influence effect of the fracture zone on the shale gas reservoir, and by calculating the relationship between the gas saturation of the shale reservoir and the distance between the shale reservoir and the fault and the fault displacement of the fault, the gas saturation of the shale reservoir can be quickly predicted, and the prediction is more accurate; and the method has extremely high operability and field practical applicability.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and particularly relates to a method for predicting the gas saturation of shale reservoirs based on fracture index. Background Technique

[0002] The geological structure of shale gas in China is active, resulting in complex fracture development and oil and gas enrichment laws. With the development of domestic shale gas exploration work, gas saturation has also become a key evaluation parameter for evaluating the exploitation value of shale gas reservoirs. According to the exploration practice of shale gas in southern Sichuan, if the gas saturation of shale reservoirs is lower than 45%, a single well does not meet the industrial gas flow standard. At present, the methods for predicting and evaluating the gas saturation of shale reservoirs mainly include: direct determination of core, calculation using logging parameters, calculation based on organic carbon, and seismic data inversion. These methods first need to solve the problem of low resistivity of shale under the influence of complex fracture zones, resulting in large differences in calculation results; secondly, it is necessary to drill wells to obtain data for calculation, which belongs to post-exploration evaluation. At present, there is a lack of a method that is easy to operate and fast for predicting the gas saturation of shale reservoirs under the influence of complex fracture zones and without a large number of exploration wells in the early stage of exploration evaluation.

[0003] Chinese patent document with publication number CN104977618A and publication date of October 14, 2015 discloses a method for evaluating shale gas reservoirs and finding sweet spots, which is characterized by being realized through the following steps:

[0004] 1) Drill core columns in different directions on the core columns at different buried depths of all wells in the exploration area, evacuate the core columns, and pressurize and saturate them with mineralized water having the same resistivity as the formation mineralized water;

[0005] 2) Under the conditions of simulating underground confining pressure and pore pressure in the laboratory, measure the dynamic and static elastic parameters, elastic wave attenuation coefficient, dispersion effect, and P-S wave velocity anisotropy coefficient of the saturated core columns, obtain the conversion relationship between the dynamic and static elastic moduli of the core, conduct anisotropic rock physics simulation, and elastic parameter calculation and crossplotting;

[0006] According to the crossplotting results, obtain the corresponding correlation between sensitive elastic parameters or combinations of sensitive elastic parameters and shale gas sweet spot parameters, and obtain and predict the parameters or parameter combinations of shale gas sweet spots;

[0007] 3) Obtain the logging data of all boreholes in the exploration area, correct the logging data in the logging area, eliminate the influence of factors such as borehole environment, well deviation change, well fluid change, well temperature change, and logging instrument error on the logging curve, and obtain the optimal logging curve that can truly reflect the change of formation physical properties;

[0008] Apply the multi-mineral analysis method and core test analysis method to calculate the formation mineral composition and content, formation density, P-wave and S-wave velocities, and porosity, and establish a lithology / rock physics model from the surface to the bottom of the well based on the geophysical logging curves of the entire well section;

[0009] 4) Conduct attribute replacement perturbation analysis on the corrected logging curves, such as fluid, porosity, and lithology data;

[0010] 5) Use the optimal logging principle and matrix solution method to perform mineral component analysis on the optimal logging curves, obtain the content and distribution law of minerals in the entire well section, and calculate the mineral composition and total formation saturation;

[0011] 6) Establish a lithology / rock physics model for the entire well section, compare the P-wave velocity, S-wave velocity, density, P-wave and S-wave impedance, and Poisson's ratio curves predicted based on the rock physics model with the measured logging curves, and verify the reliability and rationality of the lithology / rock physics model based on the coincidence degree between the predicted and measured curves;

[0012] 7) Calibrate the results calculated or predicted from the logging curves using the dynamic and static elastic parameters, elastic wave attenuation coefficient, dispersion effect, and P-wave and S-wave velocity anisotropy coefficient measured by the core column in step 2);

[0013] 8) Conduct rock component perturbation analysis on the logging data, such as total organic carbon content, quartz, and clay minerals;

[0014] 9) Conduct multi-attribute crossplots on various reservoir attribute parameters, obtain the attribute characteristics of favorable shale intervals based on the crossplot results, and determine the parameters or parameter combinations that can be used to predict shale gas sweet spots;

[0015] 10) Use the rock physics model of the entire well section established in step 6) to obtain the synthetic seismogram or gather of the rock physics model, perform well-seismic calibration processing on the logging data and the synthetic seismogram or gather, and conduct amplitude-versus-offset and amplitude-versus-azimuth analysis near the depth of the shale reservoir;

[0016] 11) Collect full-azimuth or wide-azimuth 3D seismic data in the exploration area;

[0017] 12) Collect 2D moving-offset vertical seismic profile or 3D vertical seismic profile data in the wells in the exploration area; or collect 2D moving-offset vertical seismic profile or 3D vertical seismic profile data synchronously with the surface 3D seismic data;

[0018] 13) Perform velocity analysis, migration imaging, and inversion on the 2D or 3D vertical seismic profile data in the exploration area based on the depth of downhole geophones and the travel time of seismic waves from the ground to the downhole geophones to obtain accurate formation velocities, formation attenuation coefficients, and anisotropic parameters of each formation velocity;

[0019] 14) Conduct high-precision surface comprehensive modeling on the surface omnidirectional or wide-azimuth 3D seismic data, calculate static correction amounts, and perform static correction processing; use well constraints and well vertical seismic profile data to drive the processing of surface seismic data to improve the resolution and accuracy of surface seismic data, then perform fine excision and iterative velocity calculation, and finally complete velocity modeling and 3D prestack time migration and 3D prestack depth migration imaging processing;

[0020] 15) Perform resolution improvement processing on the data after 3D prestack depth migration imaging processing;

[0021] 16) Use the seismic trace high-resolution processing method of non-parametric spectral analysis based on statistical adaptive signal theory and the high-resolution underground reflection information estimation method with fidelity to perform high-resolution processing on the data after 3D prestack depth migration processing.

[0022] 17) Extract the accurate burial depth, thickness, occurrence, and planar distribution of shale reservoirs from 3D high-resolution seismic data;

[0023] 18) Invert the 3D high-resolution post-stack seismic data to obtain the post-stack inversion seismic attribute data volume for interpreting faults and fractures;

[0024] 19) Use coherence and correlation attributes, dip and dip azimuth attributes, maximum and minimum curvature, positive and negative curvature attributes, etc. to describe and characterize the distribution characteristics of underground faults, fracture fissures, and tectonic boundaries;

[0025] 20) Use the unsupervised adaptive statistical model neural network calculation method to automatically classify attributes such as coherence, minimum and maximum curvature, curvature shape index, instantaneous dip, and dip azimuth in a non-linear manner, determine seismic facies bodies according to the distribution characteristics of fracture density, establish seismic fracture facies, and draw the distribution data volume of faults and fracture zones to characterize seismic facies anomaly bodies and fracture zones;

[0026] 21) Use post-stack attribute data for automatic fault picking;

[0027] 22) Perform optimization, denoising, stretching correction, and flattening processing on prestack seismic trace gathers;

[0028] 23) Perform elliptical velocity inversion on prestack seismic data, and at the same time determine the formation pressure and delineate the high-pressure area in the shale reservoir according to the changes and differences in interval velocities in the shale reservoir;

[0029] 24) Perform the amplitude variation with offset and simultaneous P-wave and S-wave impedance inversion of 3D prestack seismic data;

[0030] 25) Perform the elliptical inversion of anisotropic parameters of 3D prestack seismic data;

[0031] 26) Perform the elliptical inversion of elastic moduli of prestack seismic data to obtain anisotropic elastic moduli, and through petrophysical analysis, convert the anisotropic elastic moduli into reservoir parameters of the target layer;

[0032] 27) Conduct the joint geological interpretation and calibration of various seismic attributes characterizing faults and fractures;

[0033] 28) Determine the possible well completion formation damage zones and the possibility of fracturing fluid interfering with adjacent wells according to the fracture development status of shale layers;

[0034] 29) According to the conversion relationship between the dynamic and static elastic moduli of the core in step 2), convert the dynamic elastic modulus obtained from the simultaneous inversion of anisotropic elastic waves of 3D prestack seismic data into a static elastic modulus;

[0035] 30) Utilize the correlation between the static elastic modulus and rock brittleness to determine the brittleness distribution law and characteristics of shale reservoirs, and optimize the well completion and fracturing design of horizontal wells;

[0036] 31) Utilize the distribution law of the static elastic modulus or the derived static elastic modulus in shale reservoirs to determine the brittleness characteristics of shale reservoirs, obtain the azimuth and intensity of local in-situ stress, determine the azimuth trends and density of faults, fractures and fissures in shale reservoirs, and predict and delineate the areas with high total organic carbon content and high formation pressure in shale reservoirs;

[0037] 32) Synthesize various favorable parameters of the shale gas reservoir obtained, and combine with the accurate burial depth, thickness, attitude and planar distribution of the shale reservoir to obtain the gas-bearing prospect of the shale gas reservoir and delineate the sweet spots for shale gas exploration and development.

[0038] The method for evaluating shale gas reservoirs and finding sweet spots disclosed in this patent document can evaluate the gas-bearing prospect of shale gas reservoirs according to the accurate burial depth, thickness, attitude, planar distribution, distribution of total organic carbon content or organic matter abundance, and the development degree, intensity, azimuth distribution law and characteristics of faults, fractures and fissures in shale reservoirs. However, the entire evaluation process is quite cumbersome, and due to the large number of influencing parameters, errors are likely to occur, thus affecting the prediction accuracy. Summary of the Invention

[0039] In order to overcome the defects of the above-mentioned prior art, the present invention provides a method for predicting the gas saturation of shale reservoirs based on the fracture index. Based on the fracture index and using the influence of the fracture zone on the shale gas reservoir, by calculating the relationship between the gas saturation of the shale reservoir, the distance from the shale reservoir to the fault, and the throw of the fault itself, the gas saturation of the shale reservoir can be quickly predicted, the prediction is more accurate, and it has strong operability and practical application in the field.

[0040] The present invention is realized through the following technical solutions:

[0041] A method for predicting the gas saturation of shale reservoirs based on the fracture index, characterized by comprising the following steps:

[0042] a. Collect the coordinates and geophysical data of the prediction target area, and select the faults around the coordinates of the prediction target area according to the geophysical data;

[0043] b. According to the faults around the coordinates of the prediction target area selected, obtain the throw G of the fault, the distance D from the cross-section coordinate of the hanging wall of the fault to the coordinate of the prediction target area t and the distance D from the cross-section coordinate of the footwall of the fault to the coordinate of the prediction target area b ;

[0044] c. Establish a parameter matrix A of m selected faults, conduct optimization of the throw of the hanging wall and the footwall, select the effective faults, and calculate the fracture index F;

[0045] d. Predict the gas saturation of the shale reservoir in the prediction target area according to the fracture index F calculated in step c.

[0046] In the above step a, selecting the faults around the coordinates of the prediction target area according to the geophysical data specifically means selecting the faults within a range of 20 kilometers with the coordinate point of the prediction target area as the center point.

[0047] In the above step b, the throw G of the fault refers to the vertical elevation difference between the corresponding reservoir strata of the upper and lower fault planes of the fault.

[0048] In the above step b, the distance D from the cross-section coordinate of the hanging wall of the fault to the coordinate of the prediction target area t refers to the vertical distance from the coordinate of the prediction target area perpendicular to the strike of the fault to the cross-section coordinate of the upper fault plane.

[0049] In the above step b, the distance D from the cross-section coordinate of the footwall of the fault to the coordinate of the prediction target area b refers to the vertical distance from the coordinate of the prediction target area perpendicular to the strike of the fault to the cross-section coordinate of the lower fault plane.

[0050] In the above step c, the parameter matrix A is formula 1;

[0051]

[0052] Among them, G m1 is the displacement of each fault; Dt m2 is the distance from the coordinate of the predicted target area to the coordinate of the upper wall section of the fault; D bm3 is the distance from the coordinate of the predicted target area to the coordinate of the lower wall section of the fault.

[0053] In the said step c, the upper wall displacement and the lower wall displacement are optimized by Equation 2;

[0054]

[0055] In the said step c, calculating the fracture index F means, according to the output result of Equation 2, Min(((D t12+ D b13 ) / 2, (D t22+ D b23 ) / 2,... and (D tm2+ D bm3 ) / 2)), selecting the smallest ((D tMIN+ D bMIN ) / 2), if (D tMIN - D bMIN ) > 0, then calculate by Equation 3;

[0056]

[0057] Among them, A, C, α, and β are all constants; G m is the displacement; D bm is the distance from the coordinate of the predicted target area to the coordinate of the upper wall section of the fault.

[0058] In the said step c, calculating the fracture index F means, according to the output result of Equation 2, Min(((D t12+ D b13 ) / 2, (D t22+ D b23 ) / 2,... and (D tm2+ D bm3 ) / 2)), selecting the smallest ((D tMIN+ D bMIN ) / 2), if (D tMIN - D bMIN ) < 0, then calculate by Equation 4;

[0059] F = Aln(αG m + BD tm + C) - B Equation 4

[0060] Among them, D tm is the distance from the coordinate of the predicted target area to the coordinate of the lower wall section of the fault.

[0061] In step d, the gas saturation of the shale reservoir in the target area is calculated by Equation 5;

[0062] S = Aln(F) + B Equation 5

[0063] Where S is the gas saturation of the shale reservoir in the target area, and B is a constant.

[0064] The basic principle of the present invention is as follows:

[0065] Existing methods for measuring and predicting the gas saturation of shale reservoirs, such as direct core measurement, calculation using logging parameters, calculation based on organic carbon, and seismic data inversion, must have a large amount of post-drilling data such as core sampling analysis data and logging data. They are used to measure and predict the gas saturation of the reservoir in the predicted area after drilling has been carried out. In the case of a lack of a large amount of exploration well data in the early stage of exploration, other prediction methods will fail or the prediction compliance will be extremely low. The present invention determines the influence of the fault zone on the shale gas reservoir, and predicts the gas saturation of the shale reservoir in the predicted area through the data of the distance between the shale reservoir in the predicted area and the fault and the fault throw size. The prediction data collection is simple and has foresight, especially suitable for evaluation and well selection in the early stage of exploration, ensuring the geological success rate of exploration well drilling.

[0066] The beneficial effects of the present invention are mainly manifested in the following aspects:

[0067] 1. The present invention, based on the fracture index, utilizes the influence of the fault zone on the shale gas reservoir, and can quickly predict the gas saturation of the shale reservoir by calculating the relationship between the gas saturation of the shale reservoir and the distance between the shale reservoir and the fault and the fault throw size itself. The prediction is more accurate, with extremely strong operability and on-site practical applicability.

[0068] 2. The present invention utilizes the geophysical data in the early stage of exploration evaluation and the influence of the fault zone on the shale reservoir, establishes a correlation through the fault throw, fault distance and fracture influence index of the fault parameters in the geophysical data, and then establishes a correlation through the fracture index and the gas saturation of the shale reservoir. Finally, in the early stage of exploration evaluation, in the case of a lack of a large amount of exploration wells, the gas saturation of the shale reservoir is predicted through the parameter data of the faults around the predicted area, which can reduce the exploration risk and is simple and easy to operate.

[0069] 3. The parameters used in the present invention are all geophysical data in the early stage of exploration. The parameters are easy to process and collect, and do not involve post-exploration evaluation data, with universality and predictability.

[0070] 4. Compared with the prior art, the present invention can predict the gas saturation of the target area to be predicted without a large amount of drilling well data, and then effectively guide the selection of shale gas exploration areas and the evaluation and deployment.

[0071] 5. For the present invention, only by using the influence of the fault zone on the shale gas reservoir and through the data of the distance between the shale reservoir in the prediction area and the fault and the fault throw size, the gas saturation of the shale reservoir can be predicted. Especially in the case of lacking a large amount of exploration well data in the early stage of exploration, the prediction result has a high degree of consistency with the actual exploration result. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The present invention will be further specifically described below in conjunction with the drawings in the specification and the specific embodiments:

[0073] Figure 1 It is a comparison chart of the predicted gas saturation and the actual gas saturation of the present invention. SPECIFIC EMBODIMENTS

[0074] Example 1

[0075] A method for predicting the gas saturation of a shale reservoir based on a fracture index, comprising the following steps:

[0076] a. Collect the coordinates and geophysical data of the target area to be predicted, and select the faults around the coordinates of the target area to be predicted according to the geophysical data;

[0077] b. According to the faults selected around the coordinates of the target area to be predicted, obtain the fault throw G of the fault and the distance D between the coordinate of the upper wall section of the fault and the coordinate of the target area to be predicted t and the distance D between the coordinate of the lower wall section of the fault and the coordinate of the target area to be predicted b ;

[0078] c. Establish a parameter matrix A of m selected faults, perform optimization on the upper wall throw and the lower wall throw, select the effective faults, and calculate the fracture index F;

[0079] d. Predict the gas saturation of the shale reservoir in the target area according to the fracture index F calculated in step c.

[0080] This embodiment is the most basic implementation manner. Based on the fracture index, using the influence of the fault zone on the shale gas reservoir, by calculating the relationship between the gas saturation of the shale reservoir and the distance between the shale reservoir and the fault and the fault throw size itself, the gas saturation of the shale reservoir can be quickly predicted, the prediction is more accurate, and it has strong operability and on-site practical applicability.

[0081] Example 2

[0082] A method for predicting the gas saturation of shale reservoirs based on the fracture index, comprising the following steps:

[0083] a. Collect the coordinates and geophysical data of the target prediction area, and select the faults around the coordinates of the target prediction area according to the geophysical data;

[0084] b. According to the faults around the coordinates of the target prediction area selected, obtain the fault throw G of the fault, the distance D between the cross-section coordinates of the hanging wall of the fault and the coordinates of the target prediction area t and the distance D between the cross-section coordinates of the footwall of the fault and the coordinates of the target prediction area b ;

[0085] c. Establish a parameter matrix A for the m selected faults, conduct optimization of the hanging wall throw and the footwall throw, select the effective faults, and calculate the fracture index F;

[0086] d. Predict the gas saturation of the shale reservoir in the target prediction area according to the fracture index F calculated in step c.

[0087] In the said step a, selecting the faults around the coordinates of the target prediction area according to the geophysical data specifically means selecting the faults within a range of 20 kilometers with the coordinate point of the target prediction area as the center point.

[0088] In the said step b, the fault throw G of the fault refers to the vertical elevation difference between the corresponding reservoir strata of the upper and lower fault planes of the fault.

[0089] In the said step b, the distance D between the cross-section coordinates of the hanging wall of the fault and the coordinates of the target prediction area t refers to the vertical distance from the coordinates of the target prediction area perpendicular to the fault strike to the cross-section coordinates of the upper fault plane.

[0090] In the said step b, the distance D between the cross-section coordinates of the footwall of the fault and the coordinates of the target prediction area b refers to the vertical distance from the coordinates of the target prediction area perpendicular to the fault strike to the cross-section coordinates of the lower fault plane.

[0091] This embodiment is a preferred embodiment. By using the geophysical data in the early stage of exploration and evaluation and the influence of the fault zone on the shale reservoir, a correlation is established through the fault parameters of the geophysical data, namely the fault throw, the fault distance, and the fracture influence index. Then a correlation is established between the fracture index and the gas saturation of the shale reservoir. Finally, in the early stage of exploration and evaluation, when there is a lack of a large number of exploration wells, the gas saturation of the shale reservoir is predicted through the parameter data of the faults around the prediction area, which can reduce the exploration risk and is simple and easy to operate.

[0092] Example 3

[0093] A method for predicting the gas saturation of shale reservoirs based on the fracture index, comprising the following steps:

[0094] a. Collect the coordinates and geophysical data of the predicted target area, and select the faults around the coordinates of the predicted target area according to the geophysical data;

[0095] b. According to the faults around the coordinates of the predicted target area selected, obtain the throw G of the fault, the distance D between the coordinate of the fault hanging wall section and the coordinate of the predicted target area, t and the distance D between the coordinate of the fault footwall section and the coordinate of the predicted target area; b ;

[0096] c. Establish the parameter matrix A of m selected faults, conduct optimization of the hanging wall throw and the footwall throw, select the effective faults, and calculate the fracture index F;

[0097] d. Predict the gas saturation of the shale reservoir in the predicted target area according to the fracture index F calculated in step c.

[0098] In step a, selecting the faults around the coordinates of the predicted target area according to the geophysical data specifically refers to selecting the faults within a range of 20 kilometers with the coordinate point of the predicted target area as the center point.

[0099] In step b, the throw G of the fault refers to the vertical elevation difference between the corresponding reservoir formations of the fault hanging wall and the fault footwall.

[0100] In step b, the distance D between the coordinate of the fault hanging wall section and the coordinate of the predicted target area t refers to the vertical distance from the coordinate of the predicted target area perpendicular to the fault strike to the coordinate of the fault hanging wall section.

[0101] In step b, the distance D between the coordinate of the fault footwall section and the coordinate of the predicted target area b refers to the vertical distance from the coordinate of the predicted target area perpendicular to the fault strike to the coordinate of the fault footwall section.

[0102] In step c, the parameter matrix A is as shown in Equation 1;

[0103]

[0104] where G m1 is the throw of each fault; Dt m2 is the distance between the coordinate of the predicted target area and the coordinate of the fault hanging wall section; Db m3 is the distance between the coordinate of the predicted target area and the coordinate of the fault footwall section.

[0105] In step c, conduct optimization of the hanging wall throw and the footwall throw through Equation 2;

[0106]

[0107] In step c, the calculation of the fracture index F refers to the output result according to Equation 2, Min((D t12+ D b13 ) / 2, (D t22+ D b23 ) / 2, …, and (D tm2+ D bm3 ) / 2)), select the smallest ((D tMIN+ D bMIN ) / 2). If (D tMIN -D bMIN ) > 0, then calculate through Equation 3;

[0108]

[0109] where A, C, α, and β are all constants; G m is the fault throw; D bm is the distance from the coordinate of the predicted target area to the coordinate of the fault hanging wall section.

[0110] This embodiment is another preferred embodiment. The parameters used are all geophysical data in the early stage of exploration. The parameters are easy to process and collect and do not involve the evaluation data in the later stage of exploration, having universality and predictability.

[0111] Example 4

[0112] A method for predicting the gas saturation of shale reservoirs based on the fracture index, comprising the following steps:

[0113] a. Collect the coordinates and geophysical data of the predicted target area, and select the faults around the coordinates of the predicted target area according to the geophysical data;

[0114] b. According to the faults around the coordinates of the predicted target area selected, obtain the fault throw G of the fault, the distance D t from the coordinate of the fault hanging wall section to the coordinate of the predicted target area, and the distance D b from the coordinate of the fault footwall section to the coordinate of the predicted target area;

[0115] c. Establish a parameter matrix A for the m selected faults, perform optimization of the hanging wall throw and the footwall throw, select the effective faults, and calculate the fracture index F;

[0116] d. Predict the gas saturation of the shale reservoir in the predicted target area according to the fracture index F calculated in step c.

[0117] In step a, selecting the faults around the coordinates of the predicted target area according to the geophysical data specifically means selecting the faults within a range of 20 kilometers centered on the coordinate point of the predicted target area.

[0118] In step b, the fault throw G of the fault refers to the vertical elevation difference between the corresponding reservoir formations of the upper and lower fault planes of the fault.

[0119] In step b, the distance D between the coordinate of the upper fault plane and the coordinate of the predicted target area t refers to the vertical distance from the coordinate of the predicted target area perpendicular to the fault strike to the coordinate of the upper fault plane section.

[0120] In step b, the distance D between the coordinate of the lower fault plane and the coordinate of the predicted target area b refers to the vertical distance from the coordinate of the predicted target area perpendicular to the fault strike to the coordinate of the lower fault plane section.

[0121] In step c, the parameter matrix A is Equation 1;

[0122]

[0123] where G m1 is the fault throw of each fault; Dt m2 is the distance between the coordinate of the predicted target area and the coordinate of the upper fault plane of the fault; Db m3 is the distance between the coordinate of the predicted target area and the coordinate of the lower fault plane of the fault.

[0124] In step c, the upper and lower fault throws are optimized by Equation 2;

[0125]

[0126] In step c, calculating the fracture index F means, according to the output result of Equation 2, Min(((D t12+ D b13 ) / 2, (D t22+ D b23 ) / 2, … and (D tm2+ D bm3 ) / 2)), selecting the smallest ((D tMIN+ D bMIN ) / 2), and if (D tMIN - D bMIN ) < 0, then calculate by Equation 4;

[0127] F = Aln(αG m + BD tm + C) - B Equation 4

[0128] where D tm is the distance between the coordinate of the predicted target area and the coordinate of the lower fault plane of the fault.

[0129] In step d, the gas saturation of the shale reservoir in the target area is calculated by Equation 5;

[0130] S = Aln(F) + B Equation 5

[0131] Where S is the gas saturation of the shale reservoir in the target area, and B is a constant.

[0132] This embodiment is the best implementation mode. Compared with the prior art, it can predict the gas saturation of the target area without a large number of drilling well data, and then effectively guide the exploration and evaluation deployment of shale gas exploration areas.

[0133] Only by using the influence of the fault zone on the shale gas reservoir and through the data of the distance from the shale reservoir in the prediction area to the fault and the fault throw size, the gas saturation of the shale reservoir can be predicted. It is especially suitable for the case where there is a lack of a large number of exploration well data in the early stage of exploration, and the prediction result has a high degree of coincidence with the actual exploration result.

[0134] The present invention will be described below by taking the application in the Longmaxi Formation shale reservoir in southern Sichuan as an example:

[0135] Collect the coordinates and geophysical data of the prediction target area, and select the faults around the coordinates of the prediction area according to the geophysical data. Mainly select the faults within a range of 20 kilometers centered on the coordinate point of the prediction target area;

[0136] According to the 5 faults within 20 kilometers around the coordinates of the selected prediction area, obtain the fault throw G of these 5 faults through geophysical data. The fault throw G of the fault is the vertical elevation difference between the upper and lower reservoir formations corresponding to the fault, with the unit of m; obtain the shortest vertical distance D from the coordinates of the prediction target area perpendicular to the fault strike to the upper fault plane through geophysical data t and the shortest vertical distance D from the coordinates of the prediction target area perpendicular to the fault strike to the lower fault plane b , with the unit of km;

[0137] According to the G and D of the 5 selected faults t , D b Select the effective faults and establish the parameter matrix A, where the fault throw G ≥ 100m;

[0138]

[0139] Where:

[0140] A is the parameter matrix of the 5 selected faults; the first column is the fault throw G of each fault m1 , with the unit of m; the second column is the distance D from the coordinates of the prediction target area to the upper fault plane coordinate of the fault t m2 , with the unit of km; the third column is the distance D from the coordinates of the prediction target area to the lower fault plane coordinate of the fault b m2 , with the unit of km;

[0141] Optimize the hanging wall throw and footwall throw:

[0142]

[0143] According to the output result, Min((the second column + the third column) / 2), the smallest valid data selected is the first row. According to (2), the calculation result of the first row > 0. Based on the distance from the coordinate of the smallest predicted target area to the coordinate of the fault footwall section, calculate the fracture index F according to the following formula:

[0144]

[0145] If the calculation result of the row with the smallest valid data selected < 0, calculate the fracture index F according to the following formula:

[0146] F = 9.4888 * ln((-0.088) * G m +(1.12) * D tm +46.146)+28.717

[0147] Calculate the gas saturation S of the shale reservoir in the target area;

[0148] S = 10.701ln(F)+26.052

[0149] Predict the gas saturation of the shale reservoir in the target area. For the shale reservoir of the Longmaxi Formation in southern Sichuan, 23 predicted regional target points are selected for verification. By comparing the predicted gas saturation with the gas saturation data of the later drilling materials in the predicted regional targets Figure 1 It can be seen that the correlation coefficient R is as high as 9.4, and the average prediction error rate is below 6%.

Claims

1. A method for predicting the gas saturation of shale reservoirs based on the fracture index, characterized in that, it includes the following steps: a. Collect the coordinates and geophysical data of the prediction target area, and select the faults around the coordinates of the prediction target area according to the geophysical data; b. According to the faults around the coordinates of the selected predicted target area, obtain the throw G of the fault through geophysical data, the distance D between the coordinates of the upper wall section of the fault and the coordinates of the predicted target area t and the distance D between the coordinates of the lower wall section of the fault and the coordinates of the predicted target area b ; c. Establish a parameter matrix A of the selected m faults, conduct optimization of the hanging wall throw and footwall throw, select the effective faults, and calculate the fracture index F; d. Predict the gas saturation of the shale reservoir in the prediction target area according to the fracture index F calculated in step c.

2. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step a, selecting the faults around the coordinates of the prediction target area according to the geophysical data specifically means selecting the faults within a range of 20 kilometers with the coordinate point of the prediction target area as the center point.

3. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step b, the throw G of the fault refers to the vertical elevation difference between the upper plate surface of the fault and the corresponding reservoir formation of the lower plate surface of the fault.

4. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step b, the distance D between the coordinate of the fault hanging wall section and the coordinate of the predicted target area t refers to the vertical distance from the coordinate of the predicted target area perpendicular to the fault strike to the coordinate of the fault hanging wall section.

5. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step b, the distance D between the cross-section coordinate of the footwall of the fault and the coordinate of the predicted target area b refers to the vertical distance from the coordinate of the predicted target area perpendicular to the strike of the fault to the cross-section coordinate of the footwall surface of the fault.

6. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step c, the parameter matrix A is formula 1; Among them, G m1 is the throw of each fault; D tm2 is the distance from the coordinate of the predicted target area to the coordinate of the hanging-wall section of the fault; D bm3 is the distance from the coordinate of the predicted target area to the coordinate of the footwall section of the fault.

7. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 6, characterized in that: In step c, the hanging wall throw and footwall throw are optimized through formula 2; 8. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 7, characterized in that: In step c, the calculation of the fracture index F refers to the output result according to Equation 2, Min((D t12 +D b13 ) / 2, (D t22 +D b23 ) / 2, … and (D tm2 +D bm3 ) / 2)), select the smallest ((D tMIN +D bMIN ) / 2). If (D tMIN -D bMIN ) > 0, then calculate through Equation 3; where A, C, α, and β are all constants; G m is the throw; D bm is the distance from the coordinate of the predicted target area to the coordinate of the fault hanging wall section.

9. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 7, characterized in that: In step c, the calculation of the fracture index F refers to the output result according to Equation 2, Min((D t12 +D b13 ) / 2, (D t22 +D b23 ) / 2, … and (D tm2 +D bm3 ) / 2)), select the smallest ((D tMIN +D bMIN ) / 2). If (D tMIN -D bMIN ) < 0, calculate through Equation 4; F = Aln(αG m + βD tm + C) - B Equation 4 Among them, D tm is the distance from the coordinates of the predicted target area to the coordinates of the cross-section of the hanging wall of the fault.

10. The method for predicting the gas saturation of shale reservoirs based on the fracture index according to claim 1, characterized in that: In step d, the gas saturation of the shale reservoir in the target area is calculated through formula 5; S = Aln(F) + B Formula 5 where S is the gas saturation of the shale reservoir in the target area, and B is a constant.

Images