CN-121995518-A - Quantitative evaluation and analysis method for reservoir heterogeneity

CN121995518ACN 121995518 ACN121995518 ACN 121995518ACN-121995518-A

Abstract

The invention discloses a quantitative evaluation and analysis method for reservoir heterogeneity, which relates to the technical field of geological evaluation of oil and gas field development, combines the current seismic data and logging data which can obtain parameters such as reservoir rock mechanics, reservoir quality, reservoir ground stress and the like, and utilizes the advantages of large coverage area of the seismic data and high logging data precision, meanwhile, the defects of low seismic data precision and small logging data coverage range are overcome, quantitative evaluation of reservoir heterogeneity is realized by combining a long target layer segment, the defects of difficult acquisition, low representativeness, single characterization capability, insufficient dynamic characteristic characterization and the like of a sample for evaluating the reservoir heterogeneity by adopting an experimental method are avoided, and meanwhile, the numerical realization of the full reservoir characteristic is realized. The method provides scientific basis for the segmentation, clustering, perforation and control of the extension path and the form of hydraulic fracture of the three-dimensional fracturing of the oil and gas reservoir, and improves the effectiveness and the accuracy of reservoir reconstruction.

Inventors

YANG HAI
LEI MENG
LIU WEI
LIANG SHUANG
ZHOU WENGAO
GUAN BIN
LI JUNLONG
MAO HU
XIONG YURAN
CHEN JIAN

Assignees

中国石油天然气集团有限公司
中国石油集团川庆钻探工程有限公司

Dates

Publication Date: 20260508
Application Date: 20241105

Claims (14)

1. A method for quantitative evaluation and analysis of reservoir heterogeneity, comprising the steps of: s1, acquiring target reservoir logging data and extracting heterogeneous characteristic parameter data in the logging data; s2, carrying out integrity judgment on the parameter data and carrying out perfect processing on the judged missing data; S3, generating a Lorentz graph by using logging data and parameter data; s4, analyzing the heterogeneity of the reservoir by using the Lorentz curve graph; S5, determining a Gini coefficient by using a Lorentz graph, determining heterogeneous parameters in Weibull distribution by using the Gini coefficient, synthesizing seismic and well logging data, performing reservoir assignment by using the Weibull distribution, and quantitatively evaluating the reservoir heterogeneity.
2. The method for quantitatively evaluating and analyzing the heterogeneity of a reservoir according to claim 1, wherein in the step S1, parameters of a target reservoir, which need to be evaluated for the heterogeneity characteristics, are obtained through logging, and the parameters comprise reservoir rock mechanical parameters, reservoir physical parameters and reservoir ground stress parameters, wherein the reservoir rock mechanical parameters comprise Young modulus, poisson' S ratio and fracture pressure, the reservoir physical parameters comprise porosity, permeability, total organic carbon content and clay content, and the reservoir ground stress parameters comprise maximum level principal stress, minimum level principal stress and vertical stress.
3. The method for quantitative evaluation and analysis of reservoir heterogeneity according to claim 1, wherein step S2 comprises the steps of: s21, calculating the data quantity of each parameter in the parameter data; S22, judging whether the due data quantity of each parameter is equal to the actual logging data quantity, if so, entering a step S26, otherwise, searching and determining a well section where logging data is missing through programming, and entering a step S23; S23, judging whether the well section with missing logging data and the well section without missing logging data belong to the same horizon by combining the drilling and logging data, entering the step S24 if the well section with missing logging data belong to the same horizon, and entering the step S25 if the well section with missing logging data do not belong to the same horizon or are different in lithology; S24, perfecting logging data of a missing well section by an interpolation method, and then entering into a step S26, wherein the interpolation method comprises a linear regression interpolation method, a random forest interpolation method and a multiple interpolation method; S25, calibrating through the seismic data and the parameter characteristics of the same horizon of the adjacent well, taking the calibrated parameter value as the parameter value of the missing well section of the target well, and then entering into the step S26; S26, converting the parameter data into a new data body by adopting a maximum normalization method.
4. A method for quantitative evaluation and analysis of reservoir heterogeneity according to claim 3, wherein step S21 comprises: Num 0 is the data quantity of parameters, L is the total length from the point A to the point B of the horizontal well, m is the data interval of well logging, m is the parameter type, and k is the parameter type, including the rock mechanical parameter R, the reservoir physical parameter P and the ground stress parameter S.
5. A method for quantitative evaluation and analysis of reservoir heterogeneity according to claim 3, wherein the method for normalization at the maximum value of step S26 comprises: Wherein, the Normalized value of the ith data of k-type parameters; The method comprises the steps of obtaining the i-th data of k-class parameters, obtaining all data of k-class parameters by P k , obtaining the maximum value of all data of k-class parameters by Max (P k ), obtaining the minimum value of all data of k-class parameters by Min (P k ), obtaining the type of the k-class parameters, and obtaining the data sequence number by i.
6. The method for quantitative evaluation and analysis of reservoir heterogeneity according to claim 1, wherein step S3 comprises the steps of: s31, calculating the accumulated percentage of the length of the reservoir covered by the logging data S32, calculating the cumulative percentage of the logging parameter duty ratio S33, arranging the cumulative percentages of all the reservoir lengths and the cumulative percentages of the parameter ratios from small to large, and drawing a Lorentz curve Q in a Lorentz curve graph by taking the cumulative percentages of the reservoir lengths as an abscissa and the cumulative percentages of the parameter ratios as an ordinate; S34, drawing a straight line M passing through the points A (0, 0) and B (100 ) in the Lorentz graph.
7. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 6, wherein step S31 comprises: L n is the length of the reservoir well section corresponding to the logging parameter, m, L is the total length of the target reservoir, m; Is the cumulative percentage of the length of the reservoir interval, n is the total amount of logging parameter data.
8. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 6, wherein step S32 comprises: K n is the nth data of the parameter K, wherein K is different parameter types including rock mechanical parameters, reservoir physical parameters and ground stress parameters; is the cumulative percentage of the logging parameters, n is the total data, and k is the parameter type.
9. The method for quantitative evaluation and analysis of reservoir heterogeneity according to claim 6, wherein step S4 comprises programming a linear relationship of fitting Lorentzian curves Q and determining a slope k m for each fitted line, comprising the steps of: S41, counting the total number of data in the lorentz curve as p, and making n=m=i=1, n, m and i as counts; The points in the Lorentzian curve S42 are expressed as The data set is denoted as { X }, n=n+1; S43, judging whether i is equal to 5, if not, jumping to S42, wherein i=i+1, otherwise, entering the next step; s44, performing linear fitting on the data set { X }, and calculating a fitting degree R 2 ; S45, adding one data, i.e. n=n+1, and incorporating new data into the new data set, i.e., { X } = { X n+1 }; S46, performing linear fitting on the data set { X } again and calculating a fitting degree R N 2 ; S47, judging the relative difference ratio of the fitting degree R 2 and the fitting degree R N 2 If the number of the steps is less than 0.1, if yes, jumping to the step S45, otherwise, entering the next step; s48, let i=1, calculate slope k m of curve formed by data set { X }; S49, judging whether all data are analyzed, namely judging whether n is equal to p, if n=p, summarizing all slopes to form a slope data set { k m }, otherwise, m=m+1, and adjusting to S42.
10. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 9, wherein in step S4, using lorentz profiles to analyze reservoir heterogeneity comprises: If the slope k m is closer to 1, it means that the difference between all data corresponding to k m is smaller, i.e., the non-uniformity is weaker; Adjacent slope difference ratio The closer to 0, the smaller the difference between all the data corresponding to k m and k m+1 , i.e., the weaker the inhomogeneity.
11. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 6, wherein step S5 comprises the steps of: S51, calculating a triangle area S1 formed by three points A (0, 0), B (100 ) and C (100, 0) in the Lorentz graph; S52, calculating an area S2 formed by surrounding the curve Q and the straight line M; S53, calculating a Gini coefficient by using the area S1 and the area S2, wherein gini=s2/S1; S54, determining a heterogeneous parameter m in Weibull distribution by utilizing a Gini coefficient; S55, giving the three-dimensional seismic data values into corresponding grids as grid data values by taking the scale of the three-dimensional seismic data as a grid scale; s56, dividing grids of each seismic scale again, wherein the divided scales are based on logging precision or later simulation demand precision, and carrying out parameter assignment by adopting Weibull distribution, wherein the method comprises the steps of taking values in the seismic grids as scale parameters X in the Weibull distribution, taking logging precision as dimensions of a Weibull distribution matrix, taking values of heterogeneous parameters m as shape parameters in the Weibull distribution, carrying out full reservoir assignment, and quantitatively evaluating reservoir heterogeneity.
12. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 11, wherein in step S53, gini coefficient ranges from 0 to 1.0, and the correspondence between Gini coefficient and parameter heterogeneity comprises: When the Gini coefficient is more than or equal to 0 and less than or equal to 0.2, the degree of non-uniformity is extremely weak; when the coefficient of gini is 0.2< 0.3, the degree of heterogeneity is weaker; When the coefficient of gini is 0.3< 0.4, the degree of heterogeneity is moderate; When the coefficient of gini is 0.4< 0.5, the degree of non-homogeneity is stronger; When the coefficient of gini is 0.5< 1.0, the degree of non-uniformity is extremely strong.
13. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 12, wherein step S54 comprises: if each parameter Gini coefficient is less than 0.2, m0=6 based on the minimum Gini coefficient; If each parameter Gini coefficient is greater than 0.2, m0=1.5 is taken based on the maximum Gini coefficient; the non-homogeneous parameters of the remaining parameters are determined according to the ratio of the Gini coefficient corresponding to m0 to the Gini coefficient of the other parameters.
14. The method for quantitative evaluation and analysis of reservoir heterogeneity of claim 11, wherein step S56 comprises: establishing Weibull probability distribution function Wherein X is a parameter value corresponding to each seismic scale grid, X is an assigned parameter, and m is a non-homogeneous parameter; Programming Weibull probability distribution functions, wherein each operation is sampling once, and each sampling obtains a group of grid scales which meet the requirement of re-dividing according to logging or simulation; and taking the sampled data into a rock mechanical simulator, obtaining a rock stress-strain curve under the data condition, comparing the rock stress-strain curve with a rock core stress-strain curve of a corresponding layer obtained through experiments, and if the rock stress-strain curve characteristic under the sampled data condition is larger than the rock core stress-strain curve characteristic under the experimental condition, sampling for multiple times to meet the condition that the mechanical property of the rock core is consistent with that of a real rock core.

Description

Quantitative evaluation and analysis method for reservoir heterogeneity Technical Field The invention relates to the technical field of geological evaluation in oil and gas field development, in particular to a quantitative evaluation and analysis method for reservoir heterogeneity. Background The evaluation of reservoir heterogeneity is the basis of design of an oil and gas reservoir transformation scheme and crack propagation simulation, the permeability or porosity of the reservoir is mainly measured through an indoor core experiment by the existing method, and the reservoir heterogeneity is evaluated by adopting a Lorentz curve, so that the method has the following problems: (1) Coring is difficult. The porosity or permeability of a large number of reservoir cores need to be tested, and most of the wells at present, especially for development blocks, are no longer cored, so that the heterogeneity of the reservoir where the new well is located cannot be evaluated by experimental cores. (2) Representative low. The evaluation method through the indoor experiment is mainly based on coring experiment data, but the coring length and the range are limited, the coring of the horizontal section of the whole reservoir is impossible, and the coring is usually from a straight well section, so that for a reservoir with strong heterogeneity, the coring analysis cannot represent the heterogeneity of the reservoir, the core data outside a shaft cannot be acquired, and the heterogeneity characteristic of the whole reservoir cannot be represented. (3) And (5) single characterization. Non-uniformities in other parameters of the reservoir, such as stress non-uniformities, rock mechanical non-uniformities, etc., cannot be characterized by virtue of porosity and permeability alone. (4) The data is static. The data obtained from the laboratory experiments are static data, and the characteristics of the data may be greatly different from those of the reservoir conditions. (5) The process is complex and the expansibility is low. If the entropy value is obtained by analyzing the logging signals, the degree of heterogeneity of different well sections is qualitatively analyzed by comparing the entropy values of different well sections, the method is complex in process, and only the heterogeneity difference of different well sections can be qualitatively evaluated, so that quantitative analysis cannot be performed. (6) Hysteresis was evaluated. If the empirical mode and the Hilbert spectrum are obtained through the fracturing construction curve, the reservoir heterogeneity is judged, and the reservoir heterogeneity is evaluated through the constructed curve, so that the evaluation is delayed, and support can not be provided for reservoir reconstruction scheme design and fracture numerical simulation. (7) Limited range, difficult data acquisition. The reservoir heterogeneity is calculated, e.g., by permeability data, using an entropy weight algorithm. (8) And cannot be directly used for numerical implementation. All existing methods only stay in evaluating the reservoir heterogeneity, do not establish a relation with the numerical implementation of the reservoir heterogeneity characteristics, and cannot directly apply the heterogeneity characteristics to reservoir transformation scheme design and fracture propagation numerical simulation. Disclosure of Invention In order to overcome the defects in the prior art, the invention discloses a quantitative evaluation and analysis method for reservoir heterogeneity, which realizes quantitative evaluation of the heterogeneity of an oil and gas reservoir and numerical realization of the heterogeneity characteristics of the reservoir, including rock mechanical heterogeneity, reservoir physical heterogeneity, ground stress heterogeneity and the like, and provides scientific basis for segmentation, clustering, perforation and control of the extension path and form of hydraulic fracture of the oil and gas reservoir by a conversion method of seismic data, logging data, lorentz curve, gini coefficient and Weibull distribution. In order to achieve the above purpose, the present invention adopts the technical scheme that: A method for quantitative evaluation and analysis of reservoir heterogeneity, comprising the steps of: 1. Parameter data extraction S1, acquiring target reservoir logging data and extracting heterogeneous characteristic parameter data in the logging data; Preferably, in the step S1, parameters of the target reservoir, which need to be evaluated for heterogeneous characteristics, are obtained through logging, wherein the parameters comprise reservoir rock mechanical parameters, reservoir physical parameters and reservoir ground stress parameters, the reservoir rock mechanical parameters comprise Young modulus, poisson ratio and fracture pressure, the reservoir physical parameters comprise porosity, permeability, total organic carbon content and clay content, and the reservoir ground