CN116451463A - Comprehensive evaluation method for multi-cluster fracturing characteristics of land shale - Google Patents
Comprehensive evaluation method for multi-cluster fracturing characteristics of land shale Download PDFInfo
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Abstract
The invention provides a comprehensive evaluation method for multi-cluster fracturing characteristics of land shale, which combines two methods of complex expansion of a land shale reservoir fracture network and fracturing performance evaluation of rock mechanical parameters, carries out comprehensive analysis and evaluation on the fracturing characteristics of the land shale, adopts a gray correlation analysis method to sort all calculation parameters according to correlation degree, analyzes master control parameters influencing land shale brittleness, and solves the problem that an oil-gas well in a land shale zone cannot drill a dessert area with high fracturing performance with high probability; the error rate of well position decision is avoided, and the fracturing and reconstruction effects of oil and gas output after fracturing are improved.
Description
Technical Field
The application relates to the technical field of hydraulic fracturing of a land shale reservoir, in particular to a comprehensive evaluation method for multi-cluster fracturing characteristics of land shale.
Background
Shale oil is an important backup force for crude oil yield in China, is an important dependence on energy safety in China, and has been developed in four basins in China at present. The benefit development of shale oil and gas reservoirs is required to solve more problems, such as higher clay mineral content; the lithology of the longitudinal interlayer is complex, and the difference between the lithology of the longitudinal interlayer and the geological structure of the prior sea shale layer dominant is large; the problem of increasing production of medium-deep, normal-pressure and land-phase shale condensate reservoirs is to be solved.
The method provides reservoir transformation processes for efficient development of land shale oil reservoirs, such as ultra-long horizontal wells, small well spacing, dense cutting, three-dimensional development and the like, forms a large number of hydraulic cracks in the shale oil reservoir, greatly increases the drainage area of the reservoir, and forms a large number of oil gas migration channels with high diversion capacity in the reservoir, thereby greatly improving shale oil exploitation conditions and improving reservoir recovery ratio. The hydraulic fracturing technology is a common reservoir reconstruction technology, and can effectively establish a high-permeability channel in a reservoir so as to promote the flow of stratum crude oil and natural gas to a well bore. By combining with the horizontal well drilling technology, staged multi-cluster fracturing can be performed on the horizontal section of the well body, the reservoir transformation range is further improved, the capability of flowing of stratum oil gas to the well shaft is improved, and the productivity is promoted.
Effectively evaluating the frawability of a formation is a key to improving hydraulic fracture quality and obtaining favorable hydraulic fracture morphology. The conventional rock mechanical and geomechanical properties of the reservoir are used for evaluating the fracturing property of the stratum, quantitative knowledge of the brittleness property of the stratum is obtained, and whether the stratum is favorable for hydraulic fracture splitting and complex fracture network formation is judged.
In the aspect of oil and gas reservoir fracturing property evaluation technology, the following problems exist in the prior art:
1) Most of the methods are brittleness evaluation methods based on logging data and empirical formulas or traditional parameter evaluation methods based on indoor stress-strain test data, and the evaluation modes are single.
2) The evaluation model established by the Young modulus Poisson ratio equivalent elastic parameters has wider applicability, but under the field condition, the physical property parameters of many stratum rocks have huge differences, such as a compact sandstone stratum with a limestone thin interlayer, so that the calculated fracturing property evaluation index has poorer applicability.
The invention firstly draws a corresponding stress-strain curve according to uniaxial and triaxial compression test data of a rock sample, and the application number is CN201911399355.1, entitled shale brittleness index evaluation method based on energy evolution; then, based on a stress-strain curve, analyzing the energy evolution process of shale, and calculating the energy of each part; calculating corresponding brittleness indexes based on the energy evolution before and after the peak; and finally, obtaining the shale brittleness evaluation index by adopting a multiplication synthesis method for the brittleness indexes before and after the peak.
The technical characteristics are as follows: the invention can effectively describe the change rule of the mechanical characteristics of shale before and after the peak value.
Technical problem that above-mentioned patent was solved: the invention provides a new thought for quantitative evaluation of shale rock brittleness, but is difficult to meet the multi-factor integral fracturing property evaluation requirement of the on-site stratum.
The defects are as follows:
(1) The method adopts the method of calculating the corresponding brittleness index based on the energy evolution before and after the peak, has single evaluation index and lower accuracy of the predicted result.
The invention relates to a method for quantitatively evaluating the fracturing property of a coalbed methane reservoir by using logging data to determine the coal-rock brittleness index, the coal bed horizontal principal stress difference coefficient and the minimum principal stress difference between a coal bed and a top plate and a bottom plate of the coal bed, and evaluating the fracturing property of the coalbed methane reservoir by using the three evaluation indexes.
The technical characteristics are as follows: the invention has the characteristics of simple and practical method.
Technical problem that above-mentioned patent was solved: the invention aims to improve the accuracy of quantitative evaluation of the fracturing property logging of the coal-bed methane reservoir and provide logging technical support for the fracturing layer optimization of the coal-bed methane reservoir. It is difficult to solve the influence caused by the mechanical characteristics of crack propagation in the dynamic process of actual fracturing construction. The defects are as follows:
(1) The method has the advantages that the used evaluation indexes are few, the lithology of different layers is different, and the calculated fracturing property is difficult to reflect the fracturing property of the target reservoir completely and truly.
(2) The method adopts traditional logging data to determine the brittleness index of the coal rock reservoir, and is difficult to adapt to dynamic change of the rock mechanical parameters of the reservoir after on-site fracturing construction.
The invention firstly takes rock debris with specific depth in a reservoir of an oil-gas well, then calculates a mineral related brittleness index through tests such as an X-ray diffraction experiment, nano indentation micromechanics and the like, then weights the above 4 brittleness indexes according to the actual condition of an oil field to obtain a comprehensive fracturing index, and finally draws a longitudinal development diagram of the comprehensive fracturing index of the whole well.
The technical characteristics are as follows: the method can accurately obtain the comprehensive fracturing index of shale rock debris.
Technical problem that above-mentioned patent was solved: the method provides necessary basis for fracturing and selecting the rock core shale reservoir with difficulty in taking the rock core or without the rock core shale reservoir. It is difficult to meet the overall frac ability evaluation requirements of the in situ formation. The defects are as follows:
(1) The invention adopts various testing instruments and methods such as X-ray diffraction, nanoindentation, electron microscope scanning and the like, and has higher testing cost.
(2) The brittle data used by the method is single in variety, and is difficult to accord with the overall fracturing property evaluation of the on-site stratum.
The invention establishes a rock damage constitutive model of power function distribution by using stress and strain data obtained by testing, under the application number CN201810655972.2 and entitled coal rock brittleness evaluation method; then fitting the rock damage constitutive model distributed by the exponentiation function according to the full stress-strain curve; deducing according to the energy evolution rule of the coal rock uniaxial compression damage whole process to obtain a new brittleness index evaluation model considering the coal rock mechanical property and the cutting and fracture system distribution characteristics; and finally, calculating to obtain the coal and rock brittleness index value of the target fracturing well layer, and comparing the coal and rock brittleness index calculation result of the target fracturing well with an evaluation grading standard.
The technical characteristics are as follows: the method ensures that the fracking property evaluation of the hydraulic fracturing of the coal seam is more accurate.
Technical problem that above-mentioned patent was solved: the accurate coal rock brittleness grading and brittleness index evaluation results are provided, and the three-dimensional fracturing property accurate evaluation requirement of the on-site stratum is difficult to meet. The defects are as follows:
(1) The uniaxial compression of the coal and the rock is adopted to destroy the energy evolution rule, and the method has larger phase difference with the rock mechanical parameters of the underground real coal and rock reservoir.
(2) The method establishes the brittleness evaluation index by using the traditional stress strain data, and is difficult to accord with the three-dimensional fracturing property evaluation of the on-site stratum.
The technical problem solved by the patent is to provide conventional reservoir rock mechanics and geomechanics characteristics, obtain quantitative knowledge of stratum brittleness, judge whether the stratum is favorable for hydraulic fracture splitting and a complex fracture network forming method, and the method has the characteristics of macroscopic integration, local innovation, tight connection, mutual verification, advanced design, obvious technical advantages and the like of design links, but has the following defects:
(1) The used evaluation indexes are few, the lithology of different layers is different, and the calculated fracturing property is difficult to completely and truly reflect the fracturing property of the target reservoir.
(2) And the brittleness index of the reservoir is determined by adopting the traditional logging data, so that the method is difficult to adapt to dynamic change of the rock mechanical parameters of the reservoir after on-site fracturing construction.
(3) In part of the invention, various testing instruments and methods such as X-ray diffraction, nanoindentation, electron microscope scanning and the like are adopted, and the testing cost is high.
(4) The types of the brittle data used in the invention are single, and the brittle evaluation index is established by using the traditional stress strain data, so that the brittle data is difficult to accord with the overall fracturing property evaluation of the field stratum.
After investigation of the current state of the art, it is found that the existing rock brittleness and reservoir fracturing property evaluation method has less parameter data, and the prediction method is relatively backward, so that the fracturing property evaluation of the reservoir near the production position can only be accurately calculated, and most of the fracturing property evaluation of the whole three-dimensional geological reservoir is difficult to be given.
Disclosure of Invention
Aiming at the problems, the invention provides a comprehensive evaluation method for multi-cluster fracturing characteristics of land shale, which adopts a gray correlation analysis method to sort all calculation parameters according to correlation, analyzes main control parameters affecting the brittleness of the land shale, comprehensively analyzes and evaluates the fracturing characteristics of the land shale, and efficiently and accurately carries out multi-cluster fracturing design and hydraulic fracture network occurrence characteristic prediction.
Embodiments of the present application are implemented as follows:
the embodiment of the application provides a comprehensive evaluation method for multi-cluster fracturing characteristics of land shale, which is characterized by comprising the following steps:
s1: obtaining geological engineering parameter indexes through logging data of logging data, microseism data bodies, fracturing design schemes, fracturing construction parameters and production data;
s2: carrying out triaxial mechanical testing on the land shale rock sample by using a rock mechanical testing machine, and measuring each rock mechanical parameter of the land shale in the target area;
s3: calculating key dynamic parameters of the continental shale according to key logging data of the target well in the step S1 by a rock mechanical parameter evaluation method;
s4: according to the dynamic-static conversion relation of rock mechanical parameters, the three-dimensional space rock mechanical property distribution of the land shale stratum under different depths of different coring wells can be obtained after physical verification;
s5: classifying data of geological data of a target area according to shale geological engineering parameters;
s6: based on a gray correlation analysis algorithm, calculating the correlation degree among various data according to the data classification in the step S5;
s7: sorting the association degree to obtain the evaluation value sorting of each evaluation object, so as to optimize a plurality of main control parameters influencing the compressibility of the land shale;
s8: establishing a shale reservoir fracturing evaluation model based on the plurality of main control parameters screened in the step S7, calculating a fracturing evaluation index, and converting a stratum three-dimensional space rock mechanical property model into three-dimensional brittleness distribution characteristics through a rock-mineral composition method;
s9: based on the method of the step 5, the three-dimensional fracturing property distribution characteristics of the land shale stratum are further obtained, and a multi-cluster fracturing favorable area is determined, so that the fracturing characteristic prediction under the static condition is obtained;
s10: on the basis of acquiring static three-dimensional brittleness distribution characteristics and three-dimensional fracturing characteristic distribution characteristics, determining fracturing engineering desserts by predicting real-time change characteristics of crack morphology in the actual fracturing construction dynamic process;
s11: on the basis of the step S10, selecting a construction well section with better fracturing property, designing initial multi-cluster hydraulic fracturing parameters, developing dynamic crack expansion prediction, and calculating a multi-cluster crack expansion mechanism;
s12: analyzing the crack propagation occurrence in the step S11 to obtain quantitative evaluation of the reservoir reconstruction effect;
s13: based on the dynamic fracture expansion prediction method in the step S11, sensitivity parameter analysis is carried out on hydraulic fracturing parameters, optimal yield analysis is carried out, and the most favorable fracture network subsection clustering and dynamic construction parameters are obtained.
In some alternative embodiments, the sample data in step S2 includes young 'S modulus, poisson' S ratio, compressive strength.
In some alternative embodiments, the key logging data in step S3 includes a longitudinal-transverse wave acoustic time difference, a clay content and a density, and the key dynamic parameters are young 'S modulus, poisson' S ratio and brittleness index, and the specific calculation formula is as follows:
young's modulus E of each fracturing segment n ：
Poisson ratio of each fracturing segment
Comprehensive brittleness index of each fracturing segment
Wherein E is max Is the maximum Young's modulus, E min Is the minimum Young's modulus, V max Is the maximum value of Poisson's ratio, V min Is the minimum value of Poisson's ratio, E is the measured value of Young's modulus, V is the measured value of Poisson's ratio, f Brit The average brittle mineral content corresponding to each fracturing segment is Brit, and the rock mechanical brittleness index of each fracturing segment is given.
In some alternative embodiments, the geological engineering parameters described in step S5 include shale fracture toughness, poise Yang Canshu, differential ground stress.
In some alternative embodiments, the association degree calculation in step S6 is as follows:
taking the on-site n oil and gas well productivity as an evaluation object, taking m geological engineering parameters as evaluation indexes, and taking an evaluation object index data matrix X as follows:
carrying out dimensionless processing on each evaluation index, namely carrying out dimensionless processing on each column of X, and then calculating absolute values, maximum values and minimum values of differences between corresponding elements of each evaluated object index sequence and a reference sequence:
calculating a correlation coefficient:
wherein ρ is a resolution coefficient, 0 < ρ < 1, and if ρ is smaller, the difference between the correlation coefficients is larger, and the distinguishing capability is stronger;
calculating the average value of the association coefficient of the index of each evaluation object and the corresponding element of the reference sequence respectively to reflect the association relation between each evaluation object and the reference sequence, and marking as follows:
in some alternative embodiments, the shale reservoir frac-ability evaluation model in step S8 is as follows:
F c ＝(B·Z)/(X·K c ·Y),
wherein: f (F) c For reservoir frawability, B is brittleness index, X, Y, Z is the preferred master parameter for the target zone, K c Is the average value of fracture toughness of the reservoir type I and the reservoir type II,
normalizing the fracturing property index:
FI＝a·B N +b·Z N +c·X N +d·K C-N +e·Y N ，
wherein: FI is normalized fracking index, B N To normalize the brittleness index, X N ，Y N ，Z N Master parameters, K, preferred for the target area C-N The fracture toughness index is normalized, and a, b, c, d and e are proportional coefficients and are adjusted according to field requirements.
In some alternative embodiments, the initial multi-cluster hydraulic fracturing parameters in step S11 include cluster spacing, number of clusters, number of perforations per cluster.
In some alternative embodiments, the crack propagation yield information in step S12 includes a crack length, a crack height, a crack width.
In some alternative embodiments, the hydraulic fracturing parameters in step S13 include hydraulic fracturing segment length, cluster spacing, fluid volume.
The beneficial effects of this application are: according to the comprehensive evaluation method for the multi-cluster fracturing characteristics of the land shale, the influence of the indoor triaxial mechanical physical experiment technology, static rock mechanical parameter analysis and dynamic crack expansion on the occurrence is taken as main content, and the geological engineering parameter with the highest correlation is optimized by combining a gray correlation method, so that technical support is provided for efficient hydraulic fracturing of the land shale; the well logging data and the grey correlation analysis algorithm are combined, so that the limitation that the influence of the dynamic expansion process of the crack on the occurrence can not be predicted in the traditional fracturing property evaluation can be effectively changed, and the method has certain adaptability in the aspects of hydraulic fracturing evaluation and prediction.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a technical block diagram of an embodiment of the present application;
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
In the description of the present application, it should be noted that, directions or positional relationships indicated by terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., are directions or positional relationships based on those shown in the drawings, or are directions or positional relationships that are conventionally put in use of the product of the application, are merely for convenience of description of the present application and simplification of description, and are not indicative or implying that the apparatus or element to be referred to must have a specific direction, be configured and operated in a specific direction, and therefore should not be construed as limiting the present application. Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Furthermore, the terms "horizontal," "vertical," "overhang," and the like do not denote a requirement that the component be absolutely horizontal or overhang, but rather may be slightly inclined. As "horizontal" merely means that its direction is more horizontal than "vertical", and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present application, it should also be noted that, unless explicitly specified and limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context.
In this application, unless expressly stated or limited otherwise, a first feature "above" or "below" a second feature may include both the first and second features being in direct contact, and may also include the first and second features not being in direct contact but being in contact with each other by way of additional features therebetween. Moreover, a first feature being "above," "over" and "on" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature is higher in level than the second feature. The first feature being "under", "below" and "beneath" the second feature includes the first feature being directly under and obliquely below the second feature, or simply means that the first feature is less level than the second feature.
The features and capabilities of the present application are described in further detail below in connection with the examples.
The invention provides a comprehensive evaluation method for multi-cluster fracturing characteristics of land shale, which comprises the following steps (see figure 1):
step 1: obtaining geological data of a target area, wherein the geological data comprise logging data, microseism data bodies, fracturing design schemes, fracturing construction parameters, production data and the like;
step 2: carrying out triaxial mechanical test on the land shale rock sample, and measuring data such as Young modulus, poisson ratio, compressive strength and the like of a sample of a specific depth and a horizon by a rock mechanical tester;
step 3: calculating the distribution characteristics of key parameters in space according to the logging data in the step 1 by a rock mechanical parameter evaluation method, and carrying out dynamic and static conversion and calibration data by combining the rock mechanical parameters obtained by the logging data in the step 2;
the key logging data comprise longitudinal and transverse wave acoustic time difference, clay content and density, the key dynamic parameters are Young modulus, poisson's ratio and brittleness index, and the specific calculation formula is as follows:
young's modulus E of each fracturing segment n ：
Poisson ratio V of each fracture zone n ：
Comprehensive brittleness index of each fracturing segmentWherein E is max Is the maximum Young's modulus, E min Is the minimum Young's modulus, V max Is the maximum value of Poisson's ratio, V min Is the minimum value of Poisson's ratio, E is the measured value of Young's modulus, V is the measured value of Poisson's ratio, f Brit And (4) for the average brittle mineral content corresponding to each fracturing segment, and the Brit is the rock mechanical brittleness index of each fracturing segment, wherein the step (4) comprises the following steps: according to the dynamic-static conversion relation of the rock mechanical parameters, the spatial distribution characteristics of the rock mechanical parameters in the step 3 are combined, and the three-dimensional spatial rock mechanical characteristic distribution of the land shale stratum subjected to physical experiment correction is obtained;
step 5: data classification is carried out on geological data of the target area according to geological engineering parameters such as shale fracture toughness, poise Yang Canshu, ground stress difference and the like;
step 6: based on a gray correlation analysis algorithm, calculating the correlation degree among various factors according to the data classification in the step 5, sequencing all calculation parameters according to the correlation degree, and analyzing main control parameters affecting the brittleness of the land shale; the main calculation steps are as follows:
taking the on-site n oil and gas well productivity as an evaluation object, taking m geological engineering parameters as evaluation indexes, and taking an evaluation object index data matrix X as follows:
carrying out dimensionless processing on each evaluation index, namely carrying out dimensionless processing on each column of X, and then calculating absolute values, maximum values and minimum values of differences between corresponding elements of each evaluated object index sequence and a reference sequence:
calculating a correlation coefficient:
wherein ρ is a resolution coefficient, 0 < ρ < 1, if ρ is smaller, the larger the difference between the correlation coefficients is, the stronger the distinguishing capability is, and usually 0.5 is removed;
calculating the average value of the association coefficient of the index of each evaluation object and the corresponding element of the reference sequence respectively to reflect the association relation between each evaluation object and the reference sequence, and marking as follows:
step 7: selecting 3 parameters with highest correlation degree as main control parameters of a target area aiming at the geological data in the step 5;
step 8: establishing a compressibility evaluation empirical formula based on step screening parameters, and converting a stratum three-dimensional mechanical characteristic model into three-dimensional brittleness distribution characteristics by a rock-mineral composition method; the main control parameters of the rock mechanics selected in the step 6 are calculated through the following steps, and the shale reservoir is established
The frac evaluation model is as follows:
F c ＝(B·Z)/(X·K c ·Y),
wherein: f (F) c For reservoir frawability, B is brittleness index, X, Y, Z is the preferred master parameter for the target zone, K c Is the average value of fracture toughness of the reservoir type I and the reservoir type II,
normalizing the fracturing property index:
FI＝a·B N +b·Z N +c·X N +d·K C-N +e·Y N ，
wherein: FI is normalized fracking index, B N To normalize the brittleness index, X N ，Y N ，Z N Master parameters, K, preferred for the target area C-N The normalized fracture toughness indexes, a, b, c, d and e are proportionality coefficients, and the recommended values of a, b, c, d and e are 0.4 and can be adjusted according to field requirements. Step 9: based on the method of the step 5, the three-dimensional fracturing property distribution characteristics of the land shale stratum are further obtained, and multi-cluster fracturing favorable areas with low fracture toughness, high Young modulus and low Poisson ratio are determined, so that fracturing characteristic prediction under static conditions is obtained;
step 10: on the basis of acquiring static three-dimensional brittleness distribution characteristics and three-dimensional fracturing characteristic distribution characteristics, determining fracturing engineering desserts by predicting real-time change characteristics of crack morphology in the actual fracturing construction dynamic process;
step 11: on the basis of the step 10, selecting a construction well section with better fracturing property, designing initial multi-cluster hydraulic fracturing parameters including cluster spacing, cluster number and number of jet holes of each cluster, carrying out dynamic crack expansion prediction, and calculating a multi-cluster crack expansion mechanism;
step 12: analyzing the crack expansion occurrence in the step 11, wherein the crack expansion occurrence comprises information such as crack length, crack height, crack width and the like, so as to obtain quantitative evaluation of reservoir transformation effect;
step 13: based on the dynamic fracture expansion prediction method in the step 11, sensitivity parameter analysis is carried out on parameters such as hydraulic fracture segment length, cluster spacing, liquid amount and the like, and optimal yield analysis is carried out, so that the most favorable fracture network segmented clustering and dynamic construction parameters are obtained.
A set of experimental data is provided below to illustrate the beneficial effects of the technical solutions provided in the embodiments of the present application.
According to analysis, the main control factor variables of the target area are fracture toughness, natural fracture development index, compressive strength and confining pressure, and a shale reservoir fracturing evaluation model is established as follows:
F c ＝(B·N)/(σ C ·K c ·P C ),
wherein: f (F) C For reservoir compressibility, mpa -3 ·m -0.5 The method comprises the steps of carrying out a first treatment on the surface of the B is a brittleness coefficient, dimensionless; n is a natural crack development index, and is dimensionless; sigma (sigma) C Compressive strength, mpa; k (K) C Is the average value of fracture toughness of the reservoir layers I and II, mpa.m 0.5 ；P C Is the confining pressure, mpa.
By using the method, the compressibility of the relevant experimental data of two land shale reservoirs of a certain basin is evaluated, wherein the value of each weight coefficient is 0.4, and the calculation result is shown as follows.
TABLE 1 results of evaluation of reservoir compressibility of land shale
According to the embodiment, the method provided by the embodiment of the application comprehensively considers the factors influencing the compressibility of the land shale reservoir, and each parameter in the calculation formula can be obtained through experiments, so that the compressibility degree of the reservoir can be accurately evaluated, and the fracturing transformation process is favorably optimized.
Claims (9)
1. A land shale multi-cluster fracturing characteristic comprehensive evaluation method is characterized by comprising the following steps:
s1: obtaining geological engineering parameter indexes through logging data of logging data, microseism data bodies, fracturing design schemes, fracturing construction parameters and production data;
s2: carrying out triaxial mechanical testing on the land shale rock sample by using a rock mechanical testing machine, and measuring each rock mechanical parameter of the land shale in the target area;
s3: calculating key dynamic parameters of the continental shale according to key logging data of the target well in the step S1 by a rock mechanical parameter evaluation method;
s4: according to the dynamic-static conversion relation of rock mechanical parameters, the three-dimensional space rock mechanical property distribution of the land shale stratum under different depths of different coring wells can be obtained after physical verification;
s5: classifying data of geological data of a target area according to shale geological engineering parameters;
s6: based on a gray correlation analysis algorithm, calculating the correlation degree among various data according to the data classification in the step S5;
s7: sorting the association degree to obtain the evaluation value sorting of each evaluation object, so as to optimize a plurality of main control parameters influencing the compressibility of the land shale;
s8: establishing a shale reservoir fracturing evaluation model based on the plurality of main control parameters screened in the step S7, calculating a fracturing evaluation index, and converting a stratum three-dimensional space rock mechanical property model into three-dimensional brittleness distribution characteristics through a rock-mineral composition method;
s9: based on the method of the step 5, the three-dimensional fracturing property distribution characteristics of the land shale stratum are further obtained, and a multi-cluster fracturing favorable area is determined, so that the fracturing characteristic prediction under the static condition is obtained;
s10: on the basis of acquiring static three-dimensional brittleness distribution characteristics and three-dimensional fracturing characteristic distribution characteristics, determining fracturing engineering desserts by predicting real-time change characteristics of crack morphology in the actual fracturing construction dynamic process;
s11: on the basis of the step S10, selecting a construction well section with better fracturing property, designing initial multi-cluster hydraulic fracturing parameters, developing dynamic crack expansion prediction, and calculating a multi-cluster crack expansion mechanism;
s12: analyzing the crack propagation occurrence in the step S11 to obtain quantitative evaluation of the reservoir reconstruction effect;
s13: based on the dynamic fracture expansion prediction method in the step S11, sensitivity parameter analysis is carried out on hydraulic fracturing parameters, optimal yield analysis is carried out, and the most favorable fracture network subsection clustering and dynamic construction parameters are obtained.
2. The method for comprehensively evaluating the multi-cluster fracturing characteristics of the land shale according to claim 1, wherein the sample data in the step S2 comprises young 'S modulus, poisson' S ratio and compressive strength.
3. The method for comprehensively evaluating the multi-cluster fracturing characteristics of the land shale according to claim 2, wherein in the step S3, the key logging data comprise longitudinal and transverse wave acoustic wave time difference, clay content and density, the key dynamic parameters are Young modulus, poisson' S ratio and brittleness index, and a specific calculation formula is as follows:
young's modulus E of each fracturing segment n ：
Poisson ratio V of each fracture zone n ：
Comprehensive brittleness index C of each fracturing stage n ：
Wherein E is max Is the maximum Young's modulus, E min Is the minimum Young's modulus, V max Is the maximum value of Poisson's ratio, V min Is the minimum value of Poisson's ratio, E is the measured value of Young's modulus, V is the measured value of Poisson's ratio, f Brit The average brittle mineral content corresponding to each fracturing segment is Brit, and the rock mechanical brittleness index of each fracturing segment is given.
4. A method for comprehensively evaluating multi-cluster fracturing characteristics of land shale according to claim 1 or 3, wherein the geological engineering parameters in step S5 comprise shale fracture toughness, poise Yang Canshu and differential ground stress.
5. The method for comprehensively evaluating the multi-cluster fracturing characteristics of the land shale according to claim 3, wherein the correlation degree in the step S6 is calculated as follows:
taking the on-site n oil and gas well productivity as an evaluation object, taking m geological engineering parameters as evaluation indexes, and taking an evaluation object index data matrix X as follows:
carrying out dimensionless processing on each evaluation index, namely carrying out dimensionless processing on each column of X, and then calculating absolute values, maximum values and minimum values of differences between corresponding elements of each evaluated object index sequence and a reference sequence:
calculating a correlation coefficient:
wherein ρ is a resolution coefficient, 0 < ρ < 1, and if ρ is smaller, the difference between the correlation coefficients is larger, and the distinguishing capability is stronger;
calculating the average value of the association coefficient of the index of each evaluation object and the corresponding element of the reference sequence respectively to reflect the association relation between each evaluation object and the reference sequence, and marking as follows:
6. the method for comprehensively evaluating multi-cluster fracturing characteristics of land shale according to claim 5, wherein the shale reservoir fracturing property evaluation model in the step S8 is as follows:
F c ＝(B·Z)/(X·K c ·Y),
wherein: f (F) c For reservoir frawability, B is brittleness index, X, Y, Z is the preferred master parameter for the target zone, K c Is of reservoir type IWith the average value of the II-type fracture toughness,
normalizing the fracturing property index:
FI＝a·B N +b·Z N +c·X N +d·K C-N +e·Y N ，
wherein: FI is normalized fracking index, B N To normalize the brittleness index, X N ，Y N ，Z N Master parameters, K, preferred for the target area C-N The fracture toughness index is normalized, and a, b, c, d and e are proportional coefficients and are adjusted according to field requirements.
7. The method for comprehensively evaluating the multi-cluster fracturing characteristics of the land shale according to claim 1 or 6, wherein the initial multi-cluster hydraulic fracturing parameters in the step S11 comprise cluster spacing, cluster number and perforation per cluster.
8. The method for comprehensively evaluating the multi-cluster fracturing characteristics of the land shale according to claim 1 or 6, wherein the fracture propagation occurrence information in the step S12 comprises a fracture length, a fracture height and a fracture width.
9. The method for comprehensively evaluating multi-cluster fracturing characteristics of land shale according to claim 1 or 6, wherein the hydraulic fracturing parameters in the step S13 comprise hydraulic fracturing segment length, cluster spacing and liquid amount.
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| CN117077573A (en) * | 2023-10-16 | 2023-11-17 | 西安石油大学 | Quantitative characterization method and system for shale oil reservoir laminated fracture network morphology |
| CN117910065A (en) * | 2024-01-16 | 2024-04-19 | 长江大学 | Land shale horizontal well staged multi-cluster fracturing parameter optimization design method |
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| CN117077573A (en) * | 2023-10-16 | 2023-11-17 | 西安石油大学 | Quantitative characterization method and system for shale oil reservoir laminated fracture network morphology |
| CN117077573B (en) * | 2023-10-16 | 2024-01-26 | 西安石油大学 | Quantitative characterization method and system for shale oil reservoir laminated fracture network morphology |
| CN117910065A (en) * | 2024-01-16 | 2024-04-19 | 长江大学 | Land shale horizontal well staged multi-cluster fracturing parameter optimization design method |
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