WO2016041189A1

WO2016041189A1 - Method for evaluating shale gas reservoir and seeking desert area

Info

Publication number: WO2016041189A1
Application number: PCT/CN2014/086906
Authority: WO
Inventors: 杨顺伟
Original assignee: 杨顺伟
Priority date: 2014-09-19
Filing date: 2014-09-19
Publication date: 2016-03-24
Also published as: CN104853822A

Abstract

Disclosed is a method for evaluating a shale gas reservoir and seeking a desert area, comprising the following steps: drilling core columns in different directions, measuring dynamic and static parameters of a saturated core column to obtain a conversion relational expression of dynamic and static elastic modulus, physically simulating anisotropic rocks, and calculating and intersecting elastic parameters; according to the intersection result, obtaining a corresponding correlation between a sensitive elastic parameter or a combination of sensitive elastic parameters and parameters of a shale gas desert area, and solving and predicting the parameters or combination of parameters of the shale gas desert area; correcting log data, and acquiring an optimal logging curve; employing a multi-mineral analysis method and a core test analysis method to obtain models, and serializing the obtained models; inverting three-dimensional high-resolution post-stack earthquake data; and integrating various acquired favourable parameters of the shale gas reservoir in combination with an accurate burial depth, thickness, occurrence and plane distribution of the shale gas reservoir to obtain a gas containing prospect of the shale gas reservoir and to circle the desert area for shale gas exploitation and development.

Description

Method for evaluating shale gas reservoir and searching for dessert zone

Technical field

The invention belongs to an applied geophysical exploration method, and is a comprehensive geophysical exploration technology such as petrophysical, well logging data, omnidirectional or wide-azimuth 3D seismic data for shale gas reservoir evaluation and searching for shale gas exploration and development dessert. District method.

Background technique

The shale gas resources are abundant, and shale gas exploration and development is expected to alleviate the energy crisis. However, shale gas is an oil and gas resource. Although its accumulation model is different from conventional oil and gas reservoirs, exploration and development are in the exploration stage, mainly concentrated on the page. The research on the accumulation model and geological characteristics of rock gas, the role of geophysical technology in the exploration and development of shale gas has yet to be developed. Although rock geophysics, geophysical logging and seismic exploration play a vital role in conventional oil and gas exploration, shale gas reservoirs are concentrated only in shale accumulation models and geological features, and are rarely used in shale. A comprehensive geophysical exploration method for gas, geophysical technology is marginalized in shale gas exploration and development research.

At present, the research on shale gas is mostly concentrated on the basic theory. The application of geophysical data to the study of shale gas is still in the exploration stage. Li Zhirong et al., “New Progress in Seismic Exploration of Shale Gas in the Southern Sichuan Basin” (Natural Gas Industry, 2011, 31(4): 40-43), based on the analysis of geological and geophysical response characteristics of the shale interval in the southern Sichuan Basin. In the above, through the seismic data acquisition, processing and interpretation of technical breakthroughs, a relatively complete set of shale gas geophysical exploration ideas and technical processes have been formed, and new progress in shale gas seismic exploration has been achieved; Qi Baoquan et al. Evaluation of shale gas reservoirs in the southern Sichuan Basin (Natural Gas Industry, 2011, 31(4): 44-47), applying the ΔlogR method to shale gas reservoir evaluation in the southern Sichuan Basin, using porosity and resistivity The curve overlap method recognizes the influence of overlapping baseline selection and lithological changes when identifying shale gas, and explores the logging interpretation mode of shale gas. Luo Rong et al. In the article "Shale Gas Logging Evaluation and Earthquake Prediction and Monitoring Technology" (Natural Gas Industry, 2011, 31(4): 34-39), the geophysical exploration technology is discussed for the difference between shale gas and conventional reservoirs. In the application of shale gas exploration and development, and proposed to develop three-dimensional geophysical exploration, monitoring and development technology specifically for shale gas; Liu Shuanglian and Lu Huangsheng in "Shale gas logging evaluation technology characteristics and evaluation methods" (logging) Technology, 35(2): 113-116) In this paper, from the investigation of successful exploration and development examples of shale gas in North America, based on the study of reservoir geological background, the shale gas and conventional oil and gas reservoir logging evaluation methods are analyzed. The main difference. According to the shale gas exploration and development needs, the selection basis and logging evaluation technology of China's shale gas logging series are discussed. It is proposed that the shale mineral composition and reservoir structure evaluation, the establishment of shale reservoir standards, the identification of fracture types and the evaluation of rock mechanics parameters can be used as the focus of shale gas logging technology evaluation; Fu Yongqiang et al. In the article: Key Techniques for Experimental Evaluation of Fracture in Shale Gas Reservoirs (Natural Gas Industry, 2011, 31(4): 51-54), the tight sandstone gas and shale gas reservoirs are analyzed and compared from the perspective of rock elastic parameters. The characteristics of mechanical properties, the key techniques for experimental evaluation of shale rock brittleness and reservoir core sensitivity, and a large number of experimental evaluation studies, and the results of on-site pressure crack high tracer monitoring and ground microseismic fracturing monitoring results. Comparative analysis is of great significance for the development of shale gas; Liu Zhenwu et al., in the article “Requirements for geophysical technology for shale gas exploration and development” (Petroleum Geophysical Exploration, 2011, 46(5): 810-818), Demand analysis of shale gas geophysical technology and prospects for future development, clearly pointing out that geophysical technology as a key technology for shale gas reservoir evaluation and stimulation transformation will be on the page The role of gas exploration and development plays an important role; Nie et al. in the application of logging technology in the evaluation of mechanical properties of shale gas reservoirs (Journal of Engineering Geophysics, 2012, 9(4): 433-439) The application and significance of several logging methods such as acoustic, electrical imaging and array acoustic waves in the evaluation of mechanical properties of shale gas reservoirs are summarized. The limitations and applicable conditions of various logging methods are analyzed. Several logging methods can effectively evaluate the mechanical properties of shale gas reservoirs; Hao Jianfei et al. in Review of Geophysical Logging Evaluation of Shale Gas (Progress in Geophysics, 2012, 27(4): 1624-1632) One article In this paper, extensive literature research on the current status of shale gas exploration and development in foreign countries, especially in the United States, is carried out to review the current development status of foreign shale gas geophysical logging technology, and introduce common gas-containing pages for different stages of exploration and development. The rock logging series, then summarizes the shale gas logging response characteristics, and discusses in detail the important parameters of shale gas reservoir evaluation methods and reservoir evaluation, including organic carbon content, rock mineral composition and content, porosity, Gas content and rock mechanics parameters, and finally the problems and development trends of shale gas geophysical logging research.

In summary, in the current shale gas exploration, only the exploration and logging or seismic exploration techniques are applied, and the comprehensive geophysical exploration technology has not been applied to evaluate the gas bearing prospects of shale gas reservoirs and to seek exploration and development. The shale gas dessert area does not disclose the detailed description and specific details of how to apply geophysical exploration techniques in shale gas reservoir evaluation.

Summary of the invention

In view of the problems existing in the prior art, the present invention provides a method for comprehensively applying petrophysical, well logging data, omnidirectional or wide-azimuth three-dimensional seismic data for evaluating shale gas reservoirs and finding a dessert zone.

The invention is achieved by the following steps:

1) Drilling core columns of different directions on the core columns of different drilling depths in the exploration area, vacuuming the core columns and pressure-saturating them with mineralized water having the same resistivity as the mineralized water of the formation;

The different directions are perpendicular to the formation of the formation, horizontal and at an angle of 45 degrees.

The core column is 2.5 cm in diameter and 5 cm in length.

2) Under the conditions of laboratory simulation of underground confining pressure and pore pressure, measure the dynamic and static elastic parameters of the saturated core column, the elastic wave attenuation coefficient, the dispersion effect and the anisotropy coefficient of the longitudinal and transverse wave velocity, and obtain the core dynamic and static. The transformation relationship of elastic modulus, anisotropic rock physics simulation and elastic parameter calculation and intersection;

According to the results of the rendezvous, the combination of sensitive elastic parameters or sensitive elastic parameters and shale gas dessert zone parameters are obtained. Corresponding correlations, obtaining and predicting parameters or parameter combinations of shale gas dessert zones;

3) Obtain all logging data in the exploration area, correct the logging data of all boreholes in the survey area, and eliminate factors such as wellbore environment, well deviation, well fluid change, well temperature change and logging instrument error. For the influence of the logging curve, obtain the optimal logging curve that can truly reflect the changes in the physical properties of the formation;

The multi-mineral analysis method and the core test analysis method are used to calculate the mineral composition and content of the formation, the formation density, the longitudinal and transverse wave velocity and the porosity, and establish a petrophysical model from the surface to the bottom of the well according to the geophysical logging curve of the whole well;

The optimal logging curve is to eliminate the variation of the bore diameter, the well deviation, the well fluid change, the well temperature change, the logging speed is uneven, the downhole instrument is stuck, the non-uniform rotation and the logging instrument error factors. The optimal logging curve that reflects changes in the physical properties of the formation.

4) performing attribute substitution disturbance analysis on fluid, porosity and lithology data of the corrected logging curve;

The disturbance analysis is a corresponding logging curve obtained by changing the formation fluid, porosity or lithology, and finds the variation law of the corresponding logging curve.

5) Using the optimal logging principle and the matrix solution method for the optimal logging curve to analyze the mineral composition, obtain the mineral content and distribution law of the whole well segment, and calculate the mineral composition and total saturation of the formation;

The minerals are minerals such as clay, calcite, quartz, pyrite, total organic carbon content (TOC) and dolomite.

The optimal logging curve is a clay mineral curve, a bulk density curve, a formation uranium content curve, a neutron porosity curve, a resistivity curve, a longitudinal wave time difference curve and a transverse wave time difference curve in the log data.

6) Establish a rock physics model for the whole well, and compare the longitudinal wave velocity, shear wave velocity, density, longitudinal and transverse wave impedance and Poisson's ratio curve predicted by the rock physics model with the measured logging curve to predict Verify the reliability and rationality of the petrophysical model by matching the measured curves;

7) The dynamic and static elastic parameters measured by the core column of step 2), the elastic wave attenuation coefficient, the dispersion effect and the anisotropy coefficient of the longitudinal and transverse wave velocity are calibrated to calculate or predict the result through the logging curve;

8) Perform analysis on the rock component of the total organic carbon content, quartz, clay minerals, etc. for the well logging data;

The rock component disturbance analysis is to calculate the corresponding logging curve by changing the percentage of different minerals in the rock physics model, and find the most sensitive property of the corresponding mineral change according to the calculated variation of the logging curve. A combination of parameters or sensitive attribute parameters.

9) Performing a plurality of attribute intersections on various reservoir attribute parameters, and obtaining the attribute characteristics of the favorable shale interval according to the result of the intersection diagram, and determining parameters or parameter combinations used for predicting the shale gas dessert area;

The parameter or parameter combination is elastic modulus, Young's modulus of elasticity, density, shear modulus, product of elastic modulus and density, product of shear modulus and density, and Young's modulus of elasticity. The product of the density.

10) Using the rock physics model of the whole well established in step 6), obtain the synthetic records or gathers of the original logging model and the petrophysical model, perform the well seismic calibration process, and perform AVO near the shale reservoir depth (amplitude Aircraft offset variation) and AVA (amplitude versus azimuth variation) analysis;

11) Collecting omnidirectional or wide-azimuth 3D seismic data in the exploration area;

12) Collect two-dimensional Walkaway VSP (moving offset vertical seismic profile) or three-dimensional VSP (vertical seismic profile) data in the well of the exploration area; or acquire two-dimensional Walkaway VSP synchronously with ground three-dimensional seismic data (moving offset vertical seismic) Profile) or 3D VSP (Vertical Seismic Profile) data;

13) The 2D or 3D VSP (Vertical Seismic Profile) data in the exploration area is obtained according to the depth of the downhole detector and the travel time of the seismic wave from the ground to the downhole detector for velocity analysis, migration imaging and inversion to obtain accurate formation velocity. , formation attenuation coefficient (Q value) and anisotropic parameters of the velocity of each layer;

14) High-precision surface layer comprehensive modeling of ground omnidirectional or wide-azimuth 3D seismic data, calculation Static correction, static correction processing; use well constraints and well seismic data to process ground seismic data, improve the resolution and accuracy of ground seismic data, then perform fine and iterative speed calculations, complete velocity modeling and 3D stacking Time offset and three-dimensional prestack depth migration imaging processing;

The surface integrated modeling static correction is: static correction processing, prestack denoising, amplitude compensation, Q value (formation attenuation) compensation, surface consistent deconvolution, and predicted deconvolution amplitude relative fidelity processing.

15) improving the resolution processing of the data after the three-dimensional prestack depth migration imaging processing;

16) Seismic high-resolution processing method based on statistical adaptive signal theory for non-parametric spectrum analysis and high-resolution subsurface reflection information estimation method with fidelity, high resolution of 3D prestack depth migration processed data Rate processing.

The method for estimating reflection information is based on statistical signal adaptive processing, using a non-parametric spectrum analysis method and a high-resolution subsurface reflection information estimation method with fidelity to maximize the original seismic data information and not lose the original Under the premise of micro geological information in the data, a high-resolution complex seismic gather is obtained.

The reflection information estimation method adaptively processes the non-parametric spectrum analysis theory based on the statistical signal, and adaptively estimates the reflection amplitude of different time positions stably and accurately by simulating the statistical characteristics of the relative interference, thereby improving the section resolution and widening. The frequency band can maximize the original seismic data information and not lose the micro geological information in the original data, and obtain the complex seismic gathers with high fidelity.

17) Extracting the exact depth, thickness, occurrence and plane distribution of shale reservoirs from three-dimensional high-resolution seismic data;

18) Inverting three-dimensional high-resolution post-stack seismic data to obtain post-stack inversion seismic attribute data body for explaining faults and cracks;

19) Describe and characterize subsurface faults, fracture fissures and structures using coherence and related properties (similarity, eigenvalue similarity) dip and dip azimuth properties, maximum and minimum curvature, positive curvature and negative curvature properties Distribution characteristics of the boundary;

20) Using KSOM (unsupervised adaptive statistical model) neural network calculation method, automatically classify six attributes such as coherence, minimum and maximum curvature, curvature shape index, instantaneous dip angle and dip azimuth by nonlinear method, according to crack density The distribution characteristics are used to determine the seismic facies, establish the seismic fault facies, and map the fault and fault zone distribution data to characterize the seismic facies and fracture zones;

21) Perform automatic tomographic picking using post-stack attribute data (automatic calculation of sections based on coherence, eigenvalue similarity or curvature, and determination of macroscopic cracks and small faults);

The fault picking is to automatically calculate the section based on the coherence body, the eigenvalue similarity or the curvature body, and determine the macro crack and the small fault.

22) Perform optimization, denoising, stretching correction and leveling treatment of prestack seismic traces;

23) Perform elliptic velocity inversion of prestack seismic data, and determine formation pressure and delineate the high pressure zone in the shale reservoir according to the variation and difference of the middle velocity of the shale reservoir;

The elliptical velocity inversion is an elliptical velocity analysis of the azimuth data volume of the RMS (root mean square) velocity, and the crack orientation and longitudinal anisotropy parameters are obtained.

24) Perform AVO (amplitude variation with offset) and longitudinal and transverse wave synchronous wave impedance inversion of 3D prestack seismic data; the longitudinal and transverse wave synchronous wave impedance inversion is to calculate the gradient of AVO (amplitude varies with offset) Attributes, and inversion angles are superimposed on seismic data, and longitudinal wave impedance, shear wave impedance and other derived elastic properties are obtained synchronously, especially λρ (product of elastic modulus and density, μρ (product of shear elastic modulus and density), Eρ ( The product of Young's modulus of elasticity and density).

25) performing an elliptical inversion of the anisotropic parameters of the three-dimensional prestack seismic data;

The ellipse inversion is an ellipse inversion of the azimuth gradient and velocity to obtain the Thomsen parameter, and transform the Thomson parameter into the geomechanical anisotropy parameter of the target layer by rock physics transformation, such as Yang. Modulus, Poisson's ratio;

26) Perform the elliptical inverse of the elastic modulus λρ (the product of the elastic modulus and the density), μρ (the product of the shear elastic modulus and the density), and Eρ (the product of the Young's modulus of elasticity and the density) of the prestack seismic data. Performing an anisotropic elastic modulus, and transforming the anisotropic elastic modulus into a reservoir parameter of the target layer by petrophysical analysis;

The reservoir parameters are rock brittleness, lithology, porosity, fluid, high total organic carbon (TOC) content, and the like.

27) Joint geological interpretation and calibration of various seismic attributes characterizing faults and fractures;

The joint geological interpretation and calibration of the reservoir rock characteristic parameters are calibrated with logging curves, the fractures are calibrated with wellbore imaging data and/or core analysis data, and the fracturing microseismic monitoring results and wellbore imaging data for large-scale faults and micro-faults are used. Calibration, stress anisotropy is partially calibrated using fracturing microseismic monitoring results. The calibration process compares the calculated value with the measured result, finds the difference value or correlation coefficient between the two, and then systematically corrects or corrects the calculated value to ensure that the calculated value of the measured part in the underground is consistent with the measured result. .

28) Determine the possible completion formation damage zone and the possibility of fracturing fluid interfering with adjacent wells based on the shale formation fracture conditions;

29) converting the dynamic elastic modulus obtained by the anisotropic elastic wave synchronous inversion of the three-dimensional prestack seismic data into a static elastic modulus according to the conversion relationship between the core dynamics and the static elastic modulus of step 2);

30) Using the correlation between static elastic modulus and rock brittleness, determine the distribution and characteristics of brittleness (breakability) of shale reservoirs, and optimize the completion and fracturing scheme design of horizontal wells;

The completion and fracturing scheme of the optimized horizontal well is designed to lay horizontal wells in shale with high total organic carbon which is brittle and easy to fracturing, and optimize the spacing of each fracturing section.

31) Using the distribution law of static elastic modulus or derived static elastic modulus in shale reservoirs, delineating the high total organic carbon (TOC) content shale zone in shale reservoirs, and determining the brittle characteristics of shale reservoirs , Obtain the azimuth and intensity of local geostress, determine the azimuthal strike and intensity of shale reservoir discontinuities, fractures and fissures, and predict high total organic carbon (TOC) content in shale reservoirs and high in shale reservoirs. Formation pressure zone;

32) Comprehensively obtained various favorable parameters of shale gas reservoirs, combined with accurate burial depth, thickness, occurrence and planar distribution of shale reservoirs, obtain gas bearing prospects of shale gas reservoirs and define shale Dessert area developed by gas exploration.

The advantageous parameters include, but are not limited to, high total organic carbon content of shale, brittleness of shale reservoirs, azimuth and density of faults, cracks and fissures, orientation and strength of local geostress, local high pressure zone and porosity distributed.

The invention can analyze the relationship between reservoir parameters and rock geophysical properties, accurately determine the exact depth, thickness, occurrence and plane distribution of shale reservoirs, and accurately evaluate the total organic carbon content in shale gas reservoirs. Or the distribution of organic matter abundance, predicting the development degree of fault fissures in the exploration area, the macroscopic and microscopic azimuthal distribution of geostress, calculating the brittleness and toughness characteristics of the strata, and predicting local pressure anomalies and porosity in shale reservoirs. Distribution, comprehensive evaluation of the gas-bearing prospects of shale gas reservoirs and delineation of the shale gas exploration and development of dessert areas, the use of integrated geophysical results for horizontal well trajectory design and fracturing scheme optimization for large-scale exploration of shale gas And successful development provides important geophysical results.

The invention according to the characteristics of accurate burial depth, thickness, occurrence, plane spread, TOC (total organic carbon content) or organic abundance distribution, development degree of fault cracks and the like, etc. Evaluate the gas-bearing prospects of shale gas reservoirs and predict the distribution of sweet spots, guide the design of shale gas horizontal well trajectory and optimize the fracturing scheme, and provide important geophysical technical support for large-scale exploration and development of shale gas.

The above and other objects, features, and advantages of the present invention will become more apparent and understood by the appended claims appended claims

DRAWINGS

Figure 1 is a schematic flow chart of a method for evaluating shale gas reservoirs and searching for dessert zones using integrated geophysical exploration techniques.

detailed description

The invention will be described in detail below with reference to the accompanying drawings.

The invention is implemented by the following steps (shown in Figure 1):

1) Drilling core columns of different directions on the core columns of different drilling depths in the exploration area, vacuuming the core columns and pressure-saturating them with mineralized water with the same resistivity of the mineralized water of the formation. The different directions are perpendicular to the formation of the formation, horizontal and at an angle of 45 degrees. The core column is 2.5 cm in diameter and 5 cm in length.

2) Under the conditions of laboratory simulation of underground confining pressure and pore pressure, measure the dynamic and static elastic parameters of the saturated core column, the elastic wave attenuation coefficient, the dispersion effect and the anisotropy coefficient of the longitudinal and transverse wave velocity, and obtain the core dynamic and static. The transformation relationship of elastic modulus, anisotropic rock physics simulation and elastic parameter calculation and intersection. According to the results of the rendezvous, the corresponding correlation between the sensitive elastic parameters or the sensitive elastic parameters and the parameters of the shale gas dessert zone are obtained, and the parameters or parameter combinations of the shale gas dessert zone are obtained and predicted.

Steps 1) and 2) are the measurement and analytical calculations of the core dynamic and static elastic parameters on the left side of Figure 1. 3) Obtain all logging data in the exploration area, correct the logging data of all boreholes in the survey area, and eliminate factors such as wellbore environment, well deviation, well fluid change, well temperature change and logging instrument error. For the influence of the logging curve, obtain the optimal logging curve that can truly reflect the changes in the physical properties of the formation. The multi-mineral analysis method and core test analysis method were used to calculate the mineral composition and content of the formation, the formation density, the longitudinal and transverse wave velocity and the porosity, and the rock physical model from the surface to the bottom of the well was established based on the geophysical logging curve of the whole well. The optimal logging curve is to eliminate the variation of bore diameter, well deviation, well fluid change, well temperature change, uneven logging speed, stuck downhole instrument, non-uniform rotation and logging instrument error factors. The optimal logging curve that reflects changes in the physical properties of the formation.

4) Perform attribute substitution disturbance analysis on fluid, porosity and lithology data of the corrected logging curve.

Disturbance analysis is to find the corresponding logging curve by changing the corresponding logging curve obtained by the formation fluid, porosity or lithology.

5) For the optimal logging curve, the optimized logging principle and the matrix solving method are used to analyze the mineral composition, and the mineral content and distribution law in the whole well are obtained, and the mineral composition and total saturation of the formation are calculated. Minerals are minerals such as clay, calcite, quartz, pyrite, total organic carbon (TOC) and dolomite. The optimal logging curve is the clay mineral curve, volume density curve, formation uranium content curve, neutron porosity curve, resistivity curve, longitudinal wave time difference curve and transverse wave time difference curve in the logging data.

6) Establish a rock physics model for the whole well, and compare the longitudinal wave velocity, shear wave velocity, density, longitudinal and transverse wave impedance and Poisson's ratio curve predicted by the rock physics model with the measured log curve to predict the coincidence with the measured curve. To verify the reliability and rationality of the rock physics model.

7) The dynamic and static elastic parameters measured by the core column of step 2), the elastic wave attenuation coefficient, the dispersion effect, and the longitudinal and transverse wave velocity anisotropy coefficients are calibrated to calculate or predict the results through the well log.

8) Analysis of rock component perturbation of total organic carbon content, quartz, clay minerals, etc. The rock component disturbance analysis is to calculate the corresponding logging curve by changing the percentage of different minerals in the rock physics model. According to the calculated variation of the logging curve, find the most sensitive attribute parameter or sensitivity of the corresponding mineral change. A combination of attribute parameters.

9) Perform a variety of attribute intersections on various reservoir attribute parameters, and obtain the attributes of the favorable shale interval according to the results of the intersection diagram, and determine the parameters or parameter combinations used to predict the shale gas dessert area. The parameter or parameter combination is the product of elastic modulus, Young's modulus of elasticity, density, shear modulus, product of elastic modulus and density, product of shear modulus and density, and product of Young's modulus of elasticity and density. .

10) Using the rock physics model of the whole well established in step 6), obtain the synthetic records or gathers of the original logging model and the petrophysical model, perform the well seismic calibration process, and perform AVO near the shale reservoir depth (amplitude The offset of the offset is analyzed) and the AVA (amplitude varies with azimuth).

Steps 3) through 10) are the calibration of logging data, mineral composition calculations, geophysical logging data analysis and petrophysical modeling, rock composition and attribute replacement disturbance analysis, synthetic recording and AVO/ AVA gather analysis and other work.

11) Collect omnidirectional or wide-azimuth 3D seismic data in the exploration area.

12) Collect two-dimensional Walkaway VSP (moving offset vertical seismic profile) or three-dimensional VSP (vertical seismic profile) data in the well of the exploration area; or acquire two-dimensional Walkaway VSP synchronously with ground three-dimensional seismic data (moving offset vertical seismic) Profile) or 3D VSP (Vertical Seismic Profile) data.

13) The 2D or 3D VSP (Vertical Seismic Profile) data in the exploration area is obtained according to the depth of the downhole detector and the travel time of the seismic wave from the ground to the downhole detector for velocity analysis, migration imaging and inversion to obtain accurate formation velocity. , formation attenuation coefficient (Q value) and anisotropy parameters of the velocity of each layer.

14) Perform high-precision surface comprehensive modeling on ground omnidirectional or wide-azimuth 3D seismic data, calculate static correction amount, perform static correction processing; use well constraint and well seismic data to process ground seismic data and improve ground seismic data resolution And precision, then fine cut and iterative speed calculation, and then complete the speed modeling and 3D prestack time migration and 3D prestack depth migration imaging processing. The surface integrated modeling static correction is: static correction processing, prestack denoising, amplitude compensation, Q value (formation attenuation) compensation, surface consistent deconvolution, and predicted deconvolution amplitude relative fidelity processing.

Steps 11) to 14) are to collect omnidirectional or wide-azimuth 3D seismic data and 2D moving offset vertical seismic profile or 3D vertical seismic profile data, and process vertical seismic profile data and use well constraints and well seismic data. Drive to process ground seismic data processing.

15) Improve the resolution processing of the data after the three-dimensional prestack depth migration imaging processing.

16) Seismic high-resolution processing method based on statistical adaptive signal theory for non-parametric spectrum analysis and high-resolution subsurface reflection information estimation method with fidelity, high resolution of 3D prestack depth migration processed data Rate processing. The reflection information estimation method is based on statistical signal adaptive processing, using non-parametric spectrum analysis method and high-resolution subsurface reflection information estimation method with fidelity to minimize the original seismic data information and not lose the original data. Under the premise of geological information, a high-resolution complex seismic gather is obtained. The reflection information estimation method is based on the statistical signal adaptive processing non-parametric spectrum analysis theory. By simulating the statistical characteristics of relative interference, the reflection amplitude of different time positions can be adaptively estimated stably and accurately, thereby improving the profile resolution and broadening the frequency band. Maximize the original seismic data information and not lose the micro geological information in the original data, and obtain the complex seismic gathers with high fidelity.

17) Extract the exact depth, thickness, occurrence and plane distribution of shale reservoirs from three-dimensional high-resolution seismic data.

Steps 15) to 17) are to improve the resolution processing of the data after the three-dimensional prestack depth migration imaging process and to construct the shale reservoir, to extract the exact depth, thickness, and occurrence of the shale reservoir. Information such as plane spreads.

18) Inverting the three-dimensional high-resolution post-stack seismic data to obtain the post-stack inversion seismic attribute data body for explaining faults and cracks.

19) Using coherence and related properties (similarity, eigenvalue similarity) dip and dip azimuth properties, maximum and minimum curvature, positive curvature and negative curvature properties to describe and characterize the distribution characteristics of subsurface faults, fracture fissures and structural boundaries.

20) Using KSOM (unsupervised adaptive statistical model) neural network calculation method, automatically classify six attributes such as coherence, minimum and maximum curvature, curvature shape index, instantaneous dip angle and dip azimuth by nonlinear method, according to crack density Distribution characteristics to determine (known techniques) seismic facies, The seismic fault facies are established, and the fault and fault zone distribution data bodies are drawn to characterize the seismic phase anomalies and fracture zones.

21) Automatic tomographic picking using post-stack attribute data (automatic calculation of sections based on coherence, eigenvalue similarity or curvature) to determine macroscopic cracks and small faults). Fault picking is the automatic calculation of sections based on coherence, eigenvalue similarity or curvature, to determine macroscopic cracks and small faults.

Steps 18) to 21) are the inversion processing of the three-dimensional high-resolution post-stack seismic data, the neural network calculation, and then the distribution features of the subsurface fault, the fracture fissure and the structural boundary.

22) Perform optimization, denoising, stretching correction and leveling of prestack seismic traces. It includes processing steps such as sub-azimuth velocity analysis, sub-azimuth, sub-angle and full-angle superposition.

23) Perform elliptic velocity inversion of prestack seismic data, and determine formation pressure and delineate high pressure zones in shale reservoirs based on changes and differences in shale reservoir mid-layer velocity. The elliptical velocity inversion is an elliptical velocity analysis of the azimuth data volume of the RMS (root mean square) velocity, and the crack orientation and longitudinal anisotropy parameters are obtained.

24) AVO (amplitude varies with offset) and longitudinal and transverse wave synchronous wave impedance inversion for 3D prestack seismic data. The longitudinal and transverse wave synchronous wave impedance inversion is to calculate the gradient property of AVO (the amplitude varies with the offset), and invert the angular superimposed seismic data to obtain the longitudinal wave impedance, the shear wave impedance and other derived elastic properties, especially λρ (elastic modulus). The product of the density, μρ (the product of the shear elastic modulus and the density), and Eρ (the product of the Young's modulus of elasticity and the density).

25) Ellipse inversion of anisotropic parameters of three-dimensional prestack seismic data. Ellipse inversion is an ellipse inversion of the azimuthal gradient and velocity to obtain the Thomsen parameter, which converts the Thomson parameter into the geomechanical anisotropy parameter of the target layer, such as Young's modulus. ,Poisson's ratio.

26) Perform the elastic modulus λρ (the product of the elastic modulus and the density) of the prestack seismic data, μρ (shear An elliptical inversion of the product of the elastic modulus and density, and the product of Eρ (the product of Young's modulus of elasticity and density), the anisotropic elastic modulus is obtained, and the anisotropic elastic modulus is converted into a purpose by petrophysical analysis. Reservoir parameters of the layer. Reservoir parameters are rock brittleness, lithology, porosity, fluid, and high total organic carbon (TOC) content.

Step 22) to step 26) are to optimize and invert the prestack seismic trace set, and convert the elastic modulus obtained by the inversion into reservoir parameters of the target layer, such as rock brittleness, lithology, porosity, fluid, High total organic carbon (TOC) content, etc.

27) Joint geological interpretation and calibration of various seismic attributes characterizing faults and fractures. Joint geological interpretation and calibration of reservoir rock characteristic parameters are calibrated with logging curves, fractures are verified by wellbore imaging data and/or core analysis data, large-scale faults and micro-faults are measured by fracturing microseismic monitoring results and wellbore imaging data, stress Anisotropic fracturing microseismic monitoring results were used for local calibration. The calibration process compares the calculated value with the measured result, finds the difference value or correlation coefficient between the two, and then systematically corrects or corrects the calculated value to ensure that the calculated value of the measured part in the underground is consistent with the measured result. .

28) Determine the possible completion formation damage zone and the possibility of fracturing fluid interfering with adjacent wells based on the shale formation fracture conditions.

29) According to the conversion relationship between the core dynamics and the static elastic modulus of step 2), the dynamic elastic modulus obtained by the anisotropic elastic wave synchronous inversion of the three-dimensional prestack seismic data is converted into the static elastic modulus.

30) Using the correlation between static elastic modulus and rock brittleness, determine the distribution and characteristics of brittleness (breakability) of shale reservoirs, and optimize the completion and fracturing scheme design of horizontal wells. The completion and fracturing schemes for optimizing horizontal wells are designed to lay horizontal wells in shale with high total organic carbon that is brittle and prone to fracturing, and optimize the spacing of each fracturing section.

31) Using the distribution law of static elastic modulus or derived static elastic modulus in shale reservoirs, delineating the high total organic carbon (TOC) content shale zone in shale reservoirs, and determining the brittle characteristics of shale reservoirs , Obtain the azimuth and intensity of local geostress, determine the azimuthal strike and intensity of shale reservoir discontinuities, fractures and fissures, and predict high total organic carbon (TOC) content in shale reservoirs and high in shale reservoirs. Formation pressure zone.

Steps 27) through 32) are joint geological interpretations and calibrations of various seismic attributes that characterize faults and fractures. Through comprehensive interpretation, we obtain various favorable parameters of shale gas reservoirs in shale gas reservoirs, and finally determine the gas-bearing prospects and delineate the shale gas exploration and development of dessert areas (see the quantitative analysis process below in Figure 1).

The principles and embodiments of the present invention have been described in connection with the specific embodiments of the present invention. The description of the above embodiments is only for the understanding of the method of the present invention and the core idea thereof. At the same time, for those skilled in the art, according to the present invention The present invention is not limited by the scope of the present invention.

Claims

A method for evaluating a shale gas reservoir and finding a dessert zone, which is characterized by the following steps:

1) Drilling core columns of different directions on the core columns of different drilling depths in the exploration area, vacuuming the core columns and pressure-saturating them with mineralized water having the same resistivity as the mineralized water of the formation;

2) Under the conditions of laboratory simulation of underground confining pressure and pore pressure, measure the dynamic and static elastic parameters of the saturated core column, the elastic wave attenuation coefficient, the dispersion effect and the anisotropy coefficient of the longitudinal and transverse wave velocity, and obtain the core dynamic and static. The transformation relationship of elastic modulus, anisotropic rock physics simulation and elastic parameter calculation and intersection;

According to the results of the rendezvous, the corresponding correlation between the sensitive elastic parameters or the sensitive elastic parameters and the parameters of the shale gas dessert zone are obtained, and the parameters or parameter combinations of the shale gas dessert zone are obtained and predicted;

3) Obtain all logging data in the exploration area, correct the logging data of all boreholes in the survey area, and eliminate factors such as wellbore environment, well deviation, well fluid change, well temperature change and logging instrument error. For the influence of the logging curve, obtain the optimal logging curve that can truly reflect the changes in the physical properties of the formation;

The multi-mineral analysis method and the core test analysis method are used to calculate the mineral composition and content of the formation, the formation density, the longitudinal and transverse wave velocity and the porosity, and establish a petrophysical model from the surface to the bottom of the well according to the geophysical logging curve of the whole well;

4) performing attribute substitution disturbance analysis on fluid, porosity and lithology data of the corrected logging curve;

5) Using the optimal logging principle and the matrix solution method for the optimal logging curve to analyze the mineral composition, obtain the mineral content and distribution law of the whole well segment, and calculate the mineral composition and total saturation of the formation;

6) Establish a rock physics model for the whole well, and predict the longitudinal wave velocity and shear wave according to the rock physics model. The velocity, density, longitudinal and transverse wave impedance and Poisson's ratio curve are compared with the measured log curves. The reliability and rationality of the petrophysical model are verified by the degree of agreement between the predicted and measured curves.

7) The dynamic and static elastic parameters measured by the core column of step 2), the elastic wave attenuation coefficient, the dispersion effect and the anisotropy coefficient of the longitudinal and transverse wave velocity are calibrated to calculate or predict the result through the logging curve;

8) Perform analysis on the rock component of the total organic carbon content, quartz, clay minerals, etc. for the well logging data;

9) Performing a plurality of attribute intersections on various reservoir attribute parameters, and obtaining the attribute characteristics of the favorable shale interval according to the result of the intersection diagram, and determining parameters or parameter combinations used for predicting the shale gas dessert area;

10) Using the rock physics model of the whole well established in step 6), obtain the synthetic records or gathers of the original logging model and the petrophysical model, perform the well seismic calibration, and perform amplitude detection along the shale reservoir depth. Distance change and amplitude as azimuth change analysis;

11) Collecting omnidirectional or wide-azimuth 3D seismic data in the exploration area;

12) collecting two-dimensional moving offset vertical seismic section or three-dimensional vertical seismic section data in the well of the exploration area; or acquiring two-dimensional moving offset vertical seismic section or three-dimensional vertical seismic section data simultaneously with the ground three-dimensional seismic data;

13) The 2D or 3D vertical seismic section data in the exploration area is obtained according to the depth of the downhole detector and the velocity analysis, offset imaging and inversion of the seismic wave from the ground to the downhole detector to obtain accurate formation velocity and formation attenuation. Coefficient and anisotropic parameters of the velocity of each layer;

14) Perform high-precision surface comprehensive modeling on ground omnidirectional or wide-azimuth 3D seismic data, calculate static correction amount, perform static correction processing; use well constraint and well seismic data to process ground seismic data and improve ground seismic data resolution And precision, then perform fine cut and iterative speed calculations, then complete speed modeling and 3D prestack time migration and 3D prestack depth migration imaging processing;

15) improving the resolution processing of the data after the three-dimensional prestack depth migration imaging processing;

16) Seismic high-resolution processing method based on statistical adaptive signal theory for non-parametric spectrum analysis and high-resolution subsurface reflection information estimation method with fidelity, high resolution of 3D prestack depth migration processed data Rate processing.

17) Extracting the exact depth, thickness, occurrence and plane distribution of shale reservoirs from three-dimensional high-resolution seismic data;

18) Inverting three-dimensional high-resolution post-stack seismic data to obtain post-stack inversion seismic attribute data body for explaining faults and cracks;

19) Descriptive and characterizing the distribution characteristics of underground faults, fracture fissures and structural boundaries using coherence and related attribute dip and dip azimuth properties, maximum and minimum curvature, positive curvature and negative curvature properties;

20) Using the unsupervised adaptive statistical model neural network calculation method, the coherence, minimum and maximum curvature, curvature shape index, instantaneous dip and dip azimuth attributes are automatically classified by nonlinear method, and the earthquake is determined according to the distribution characteristics of the crack density. Phase body, establish seismic fault facies, draw fault and distribution data of fault zone, used to characterize seismic phase anomalies and fracture zones;

21) performing automatic tomographic picking using post-stack attribute data;

22) Perform optimization, denoising, stretching correction and leveling treatment of prestack seismic traces;

23) Perform elliptic velocity inversion of prestack seismic data, and determine formation pressure and delineate the high pressure zone in the shale reservoir according to the variation and difference of the middle velocity of the shale reservoir;

24) Performing the amplitude of the three-dimensional prestack seismic data with the offset of the offset and the inversion of the longitudinal and transverse wave synchronous wave impedance;

25) performing an elliptical inversion of the anisotropic parameters of the three-dimensional prestack seismic data;

26) Elliptic inversion of the product of the elastic modulus λρ elastic modulus and density of the prestack seismic data, the product of the μρ shear elastic modulus and the density, and the product of the Eρ Young's modulus of elasticity and the density The modulus of elasticity, through the petrophysical analysis, converts the anisotropic elastic modulus into the reservoir parameters of the target layer;

27) Joint geological interpretation and calibration of various seismic attributes characterizing faults and fractures;

28) Determine the possible completion formation damage zone and the possibility of fracturing fluid interfering with adjacent wells based on the shale formation fracture conditions;

29) converting the dynamic elastic modulus obtained by the anisotropic elastic wave synchronous inversion of the three-dimensional prestack seismic data into a static elastic modulus according to the conversion relationship between the core dynamics and the static elastic modulus of step 2);

30) Using the correlation between static elastic modulus and rock brittleness, determine the brittle distribution law and characteristics of shale reservoirs, and optimize the completion and fracturing scheme design of horizontal wells;

31) Using the distribution law of static elastic modulus or derived static elastic modulus in shale reservoirs, delineating the high total organic carbon content shale zone in shale reservoirs, determining the brittle characteristics of shale reservoirs, and obtaining local The orientation and strength of the in-situ stress determine the azimuthal strike and intensity of the shale reservoir discontinuities, fractures and fissures, and predict the high total organic carbon content in the shale reservoir and the high formation pressure zone in the shale reservoir;

32) Comprehensively obtained various favorable parameters of shale gas reservoirs, combined with accurate burial depth, thickness, occurrence and planar distribution of shale reservoirs, obtain gas bearing prospects of shale gas reservoirs and define shale Dessert area developed by gas exploration.
The method of claim 1 wherein the different directions of step 1) are perpendicular to the formation of the formation, horizontally and at an angle of 45 degrees.
The method of claim 1 wherein the core column of step 1) is 2.5 cm in diameter and 5 cm in length.
The method according to claim 1, wherein the optimal logging curve of step 3) is to eliminate borehole diameter change, well deviation change, well fluid change, well temperature change, log speed unevenness, downhole instrument being After the stuck, non-uniform rotation and logging instrument error factors, the optimal logging curve reflecting the physical properties of the formation is reflected.
The method according to claim 1, wherein the disturbance analysis in step 4) is to determine a corresponding log curve by changing a corresponding log curve obtained by changing formation fluid, porosity or lithology.
The method of claim 1 wherein the mineral of step 4) is a mineral such as clay, calcite, quartz, pyrite, total organic carbon content (TOC) and dolomite.
The method according to claim 1, wherein the optimal logging curve of step 4) is a clay mineral curve, a bulk density curve, a formation uranium content curve, a neutron porosity curve, and a resistivity curve in the log data. , longitudinal wave time difference curve and transverse wave time difference curve.
The method of claim 1 wherein the rock component disturbance analysis of step 8) is performed by changing the percentage of different minerals in the rock physics model to calculate a corresponding well log, based on the calculated log curve change. The size of the quantity, find the combination of the most sensitive attribute parameters or sensitive attribute parameters of the corresponding mineral change.
The method of claim 1 wherein the parameter or combination of parameters of step 9) is a product of elastic modulus, Young's modulus of elasticity, density, shear modulus of elasticity, modulus of elasticity and density, shearing. The product of the modulus of elasticity and the density and the product of Young's modulus of elasticity and density.
The method of claim 1 wherein the surface integrated modeling static correction of step 14) is: static correction processing, prestack denoising, amplitude compensation, Q value compensation, surface consistency deconvolution, and prediction inverse The convolution amplitude is relatively fidelity processed.
The method according to claim 1, wherein the method for estimating reflection information according to step 16) is based on statistical signal adaptive processing, using a non-parametric spectral analysis method and a high-resolution subsurface reflection information estimation method with fidelity. Under the premise of maximally maintaining the original seismic data information and not losing the micro geological information in the original data, a high-resolution complex seismic gather is obtained.
The method according to claim 1, wherein the method for estimating reflection information according to step 16) adaptively processes non-parametric spectrum analysis theory based on statistical signals, and adaptively reflects reflections at different time positions by simulating statistical features of relative interference. The amplitude is stably and accurately estimated, thereby improving the resolution of the section and broadening the frequency band, thereby maximally maintaining the original seismic data information and not losing the minute geological information in the original data, and obtaining the complex seismic gather with high fidelity.
The method of claim 1 wherein said step 21) is to automatically calculate a section based on a coherence body, an eigenvalue similarity or a curvature body to determine macroscopic cracks and small faults.
The method of claim 1 wherein the elliptic velocity inversion of step 23) is performed by performing an elliptical velocity analysis on the azimuth data volume of the root mean square velocity to obtain a crack strike orientation and a longitudinal anisotropy parameter.
The method according to claim 1, wherein the longitudinal and transverse wave synchronous wave impedance inversion of step 24) is to calculate a gradient property of the amplitude with the offset of the offset, and inversely integrate the seismic data with the angle, and obtain the longitudinal wave impedance and the transverse wave synchronously. Impedance and other derived elastic properties, especially the product of λρ elastic modulus and density, the product of μρ shear modulus and density, and the product of Eρ Young's modulus of elasticity and density.
The method of claim 1 wherein the ellipse inversion of step 25) is an ellipse inversion of the azimuthal gradient and velocity to obtain a Thomson parameter, and the Thomson parameter is converted to a purpose by a petrophysical transformation. Geomechanical anisotropy parameters of the layer, such as Young's modulus, Poisson's ratio.
The method of claim 1 wherein the reservoir parameters of step 26) are rock brittleness, lithology, porosity, fluid, high total organic carbon content, and the like.
The method according to claim 1, wherein the joint geological interpretation of step 27) and the calibration of the characteristic parameters of the reservoir rock are calibrated with a logging curve, and the fracture is calibrated with wellbore imaging data and/or core analysis data, large-scale faults. The micro-faults are measured by fracturing microseismic monitoring results and wellbore imaging data, and the stress anisotropy is locally calibrated by fracturing microseismic monitoring results. The calibration process uses the calculated value and the real The test results are compared to find the difference value or correlation coefficient between the two, and then the calculated value is systematically corrected or corrected to ensure that the calculated value of the measured part in the underground is consistent with the measured result.
The method of claim 1 wherein the completion and fracturing scheme of the optimized horizontal well of step 30) is designed to lay horizontal wells on shale containing high total organic carbon that is relatively brittle and prone to fracturing. Medium, and optimize the design of the spacing of each fracturing section.
The method of claim 1 wherein said advantageous parameters of step 32) include, but are not limited to, high total organic carbon content of shale, brittleness of shale reservoirs, orientation and density of faults, fractures and fractures, Azimuth and strength of local geostress, local high pressure zone and porosity distribution.