Hot dry rock thermal reservoir classification method based on geophysical feature analysis and application

Abstract

The invention provides a hot dry rock thermal reservoir classification method based on geophysical feature analysis, and the method comprises the following steps: evaluating the thermal reservoir quality of a hot dry rock reservoir, and obtaining a rock mass fracture coefficient F1 and a fracture occurrence coefficient omega; evaluating the engineering quality of the hot dry rock reservoir to obtain tensile strength T0, maximum horizontal principal stress sigma H and minimum horizontal principal stress sigma h; a hot dry rock thermal reservoir classification and discrimination model is constructed, and a hot dry rock thermal reservoir classification and discrimination function is obtained; and obtaining the type of the hot dry rock heat reservoir according to the hot dry rock heat reservoir classification discrimination function. The method avoids the influence that a single parameter is easily interfered and the precision cannot be ensured, and is firm in theoretical basis, simple to operate and high in practicability.

Description

Technical Field

[0001] The present invention relates to the technical field of geophysical exploration well logging data evaluation, in particular to a hot dry rock reservoir classification method and application based on geophysical characteristic analysis. Background Art

[0002] Hot dry rocks are generally buried deep in the earth's crust, contain little fluid, and have a rock temperature higher than 150°C. The development of hot dry rock geothermal resources is achieved through the construction of enhanced geothermal systems. The core technical difficulty is to transform the thermal reservoir through hydraulic fracturing to form a "four-way" fracture connection network to improve the heat exchange capacity during the injection and production process.

[0003] Based on the progress of exploration and development of hot dry rock geothermal resources at home and abroad and the geological understanding, hot dry rock thermal reservoirs are divided into two categories, namely typical fractured formations and dense hot dry rock formations. Different types of thermal reservoirs have different geological characteristics, and the subsequent enhanced geothermal system fracturing development and operation methods are also different.

[0004] Due to the late start of research on hot dry rock geothermal resources in China, especially in the classification of thermal reservoirs, it is still in the stage of qualitative understanding, and no specific quantitative research has been conducted, which cannot meet the needs of effective development of geothermal resources. This invention takes the hot dry rocks in the Gonghe Basin of Qinghai as the research target, combines multi-dimensional high-precision imaging logging technology, and for the first time, according to the different geophysical characteristics of the two types of thermal reservoirs, innovatively establishes a mathematical method for quantitative discrimination, strengthens the difference analysis, and realizes the classification and division of geothermal resources in the research block, providing technical support for the selection of fracturing development measures in the later enhanced geothermal system in the region. Summary of the invention

[0005] The present invention aims at the shortcomings of the current logging evaluation technology for hot dry rock geothermal resources, especially for the classification of thermal reservoirs, which is still at the stage of qualitative understanding and has not been specifically quantitatively studied, and cannot meet the needs of effective development of geothermal resources. This invention takes the hot dry rocks in the Gonghe Basin of Qinghai as the research target, combines multi-dimensional high-precision imaging logging technology, and for the first time, according to the different geophysical characteristics of the two types of thermal reservoirs, innovatively establishes a mathematical method for quantitative discrimination, strengthens the difference analysis, and realizes the classification and division of geothermal resources in the research block, providing technical support for the selection of fracturing development measures in the later enhanced geothermal system in the region.

[0006] The classification method of hot dry rock reservoir based on geophysical characteristics analysis includes the following steps:

[0007] Evaluate the thermal storage quality of hot dry rock reservoirs and obtain the rock mass fracture coefficient F1 and fracture occurrence coefficient ω;

[0008] Evaluate the engineering quality of hot dry rock reservoirs and obtain tensile strength T0, maximum horizontal principal stress σ H , minimum horizontal principal stress σ h ;

[0009] Constructing a classification and discrimination model for hot dry rock thermal reservoirs and obtaining a classification and discrimination function for hot dry rock thermal reservoirs;

[0010] The category of hot dry rock thermal reservoir is obtained according to the classification discriminant function of hot dry rock thermal reservoir.

[0011] Furthermore, the classification discriminant function of the hot dry rock reservoir is:

[0012] F=F1*F2*F3

[0013] Where: F is the thermal reservoir classification discriminant function; F2 is the dominant occurrence index, when the trend of the hot dry rock fracture is close to the minimum principal stress direction, F2 = 0; when the trend of the hot dry rock fracture is greatly different from the minimum principal stress direction, F2 = 1; F3 is the ground stress imbalance coefficient, when the horizontal stress difference of the hot dry rock fracture is greater than the tensile strength, the formation can only undergo tensile fracture, F3 = 0; when the horizontal stress difference of the hot dry rock fracture is between the tensile strength and the shear strength, the formation undergoes shear fracture, F3 = 1.

[0014] Furthermore, the method for obtaining the category of the hot dry rock thermal reservoir according to the classification discriminant function of the hot dry rock thermal reservoir is:

[0015] When any one of F1, F2, and F3 is 0, F=0, and the hot dry rock thermal reservoir belongs to a dense hot dry rock formation; when and only when any one of F1, F2, and F3 is not 0, at this time F≠0, the hot dry rock thermal reservoir belongs to a typical fractured hot dry rock formation.

[0016] Furthermore, the rock mass rupture coefficient F1 is:

[0017]

[0018] in, φ is the matrix porosity value evaluated by conventional logging compensated sonic logging; Δt is the compensated sonic time difference; Δt f is the time difference of fluid sound wave; Δt ma is the acoustic time difference of the formation skeleton; Jz is the density of fracture development around the well evaluated by well logging; Jp is the density of fracture development beside the well evaluated by well logging.

[0019] Furthermore, the dominant occurrence index F2 is:

[0020]

[0021] Among them, ω is the crack occurrence coefficient, which represents the angle between the crack strike and the direction of the maximum horizontal principal stress.

[0022] Furthermore, the ground stress imbalance coefficient F3 is:

[0023]

[0024] The fracture occurrence coefficient ω is:

[0025]

[0026] Where: h i f is the crack direction within a certain range in the crack statistical rose diagram; i is the frequency proportion of a certain range in the fracture statistical rose diagram; t is the total share in the fracture statistical rose diagram; α is the direction of the maximum horizontal principal stress evaluated by well logging.

[0027] Furthermore, the tensile strength T0 is:

[0028]

[0029] Maximum horizontal principal stress σ H for:

[0030]

[0031] Minimum horizontal principal stress σ h for:

[0032]

[0033] Where: δ is the internal friction angle of rock, FK1 is the static mode tectonic stress coefficient 1, with an implicit value of 1.0; FK2 is the static mode tectonic stress coefficient 2, with an implicit value of 0.4; PP is the formation pore pressure; PO is the overburden pressure; α is the Boit constant; ν is the Poisson's ratio, and: ν P is the P-wave velocity extracted from the cross-dipole array acoustic logging; ν S Shear wave velocity extracted for a crossed-dipole array sonic log.

[0034] Based on the application of the classification method of hot dry rock reservoirs based on geophysical characteristic analysis, a quantitative discrimination method is used to classify and divide the geothermal resources in the study area, thereby determining the selection of fracturing development measures in the later enhanced geothermal system in the region.

[0035] The advantages and positive effects of the present invention are:

[0036] 1. The present invention makes full use of multi-dimensional high-precision imaging logging technology information to quantitatively characterize the degree of fracture development, fracture orientation, and horizontal stress differences, improves the geophysical evaluation system of hot dry rock geothermal resources, deepens the understanding of geological background, and the method research is targeted;

[0037] 2. The present invention is the first to adopt multi-parameter comprehensive analysis based on the different geophysical characteristics of the two types of thermal reservoirs, starting from the two aspects of thermal reservoir quality and engineering quality, to strengthen the difference characteristics, and innovatively establish a mathematical method for quantitative discrimination and classification, avoiding the influence of a single parameter that is easily disturbed and cannot ensure accuracy. It has a solid theoretical basis, simple operation, and strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a diagram of the evaluation results of the hot dry rock reservoir classification method based on geophysical characteristic analysis in Example 2 of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical scheme and advantages of the implementation of the present invention clearer, the technical scheme in the embodiment of the present invention will be described in more detail below in conjunction with the drawings in the embodiment of the present invention. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of the present invention, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limitations on the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0040] The embodiments of the present invention are described in detail below.

[0041] Example 1

[0042] The classification method of hot dry rock reservoir based on geophysical characteristics analysis includes the following steps:

[0043] Evaluate the thermal storage quality of hot dry rock reservoirs and obtain the rock mass fracture coefficient F1 and fracture occurrence coefficient ω;

[0044] Evaluate the engineering quality of hot dry rock reservoirs and obtain tensile strength T0, maximum horizontal principal stress σ H , minimum horizontal principal stress σ h ;

[0045] Constructing a classification and discrimination model for hot dry rock thermal reservoirs and obtaining a classification and discrimination function for hot dry rock thermal reservoirs;

[0046] The category of hot dry rock thermal reservoir is obtained according to the classification discriminant function of hot dry rock thermal reservoir.

[0047] The classification discriminant function of the hot dry rock reservoir is:

[0048] F=F1*F2*F3

[0049] Where: F is the thermal reservoir classification discriminant function; F2 is the dominant occurrence index, when the trend of the hot dry rock fracture is close to the minimum principal stress direction, F2 = 0; when the trend of the hot dry rock fracture is greatly different from the minimum principal stress direction, F2 = 1; F3 is the ground stress imbalance coefficient, when the horizontal stress difference of the hot dry rock fracture is greater than the tensile strength, the formation can only undergo tensile fracture, F3 = 0; when the horizontal stress difference of the hot dry rock fracture is between the tensile strength and the shear strength, the formation undergoes shear fracture, F3 = 1.

[0050] The method for obtaining the category of hot dry rock thermal reservoirs according to the classification discriminant function of hot dry rock thermal reservoirs is:

[0051] When any one of F1, F2, and F3 is 0, F=0, and the hot dry rock thermal reservoir belongs to a dense hot dry rock formation; when and only when any one of F1, F2, and F3 is not 0, at this time F≠0, the hot dry rock thermal reservoir belongs to a typical fractured hot dry rock formation.

[0052] When evaluating the thermal storage quality of hot dry rock reservoirs, microresistivity scanning imaging logging technology (FMI) can be used to evaluate the degree of development of rock fractures in the near-wellbore area, and remote detection sonic logging technology can be used to evaluate the development of far-end fractures near the wellbore in the formation within a radius of 40m with the wellbore as the center; the greater the porosity, the higher the density of natural fractures, and the higher the degree of rock fragmentation. The present invention comprehensively uses reservoir porosity, wellbore periphery and wellbore fracture density to quantitatively characterize the degree of rock fracture in the thermal reservoir;

[0053] The rock mass rupture coefficient F1 is:

[0054]

[0055] in, φ is the matrix porosity value evaluated by conventional logging compensated sonic logging, %; Δt is the compensated sonic time difference, us / m; Δt f is the time difference of fluid sound wave; Δt ma is the formation skeleton acoustic wave time difference, us / m; Jz is the density of fracture development around the well evaluated by well logging, 1 / m; Jp is the density of fracture development beside the well evaluated by well logging, 1 / m;

[0056] The fracture occurrence coefficient ω is:

[0057]

[0058] Where: h iis the crack direction within a certain range in the crack statistics rose diagram, deg; f i is the frequency proportion of a certain range in the fracture statistical rose diagram, %; t is the total share in the fracture statistical rose diagram; α is the direction of the maximum horizontal principal stress evaluated by well logging, deg;

[0059] When evaluating the engineering quality of hot dry rock reservoirs, the engineering quality mainly includes formation mechanical parameters, geostress and anisotropy evaluation. The cross-dipole array acoustic logging (XMAC) is mainly used to analyze the mechanical strength of rocks through three-wave time difference (P-wave time difference, S-wave time difference, Stoneley wave time difference), combined with conventional logging responses and comprehensive evaluation results, to provide basic mechanical parameters for the development and transformation of geothermal systems; among which:

[0060] The tensile strength T0 is:

[0061]

[0062] Maximum horizontal principal stress σ H for:

[0063]

[0064] Minimum horizontal principal stress σ h for:

[0065]

[0066] Young's modulus E is:

[0067]

[0068] Shear strength S o for:

[0069]

[0070] Where: δ is the internal friction angle of rock, FK1 is the static mode tectonic stress coefficient 1, with an implicit value of 1.0; FK2 is the static mode tectonic stress coefficient 2, with an implicit value of 0.4; PP is the formation pore pressure; PO is the overburden pressure; α is the Boit constant; ν is the Poisson's ratio, and: ν P is the P-wave velocity extracted from the cross-dipole array acoustic logging; ν S is the shear wave velocity extracted from the cross-dipole array acoustic logging; CB is the volume compression coefficient, SH is the mud content, %.

[0071] The method for constructing a classification and discrimination model for hot dry rock thermal reservoirs, obtaining a classification and discrimination function for hot dry rock thermal reservoirs, and obtaining the category of hot dry rock thermal reservoirs according to the classification and discrimination function for hot dry rock thermal reservoirs is as follows:

[0072] There are two types of hot dry rock reservoirs. One type is the typical fractured hot dry rock formation. This type of formation has well-developed natural fractures and the rock mass itself is highly fragmented. The reservoir transformation of the enhanced geothermal system is to use water fracturing to cause a certain degree of shear displacement on the fracture surface, thereby increasing the fracture seepage capacity.

[0073] The other type is dense hot dry rock formation, which can be divided into three types:

[0074] 1) Intact rock mass without natural fractures; this reservoir type can be quantitatively characterized by combining the rock fracture coefficient in thermal reservoir quality analysis. The smaller F1 is, the lower the degree of rock fracture is and the more intact the rock mass is.

[0075] 2) Natural fractures are developed, and the fracture development direction is along the direction of minimum principal stress. This type of reservoir can be identified by defining a dominant occurrence index in combination with the fracture occurrence coefficient proposed in step 1 of the thermal reservoir quality analysis.

[0076] The dominant occurrence index F2 is:

[0077]

[0078] Among them, ω is the crack occurrence coefficient, which represents the angle between the crack strike and the direction of the maximum horizontal principal stress.

[0079] 3) Natural fractures are developed, but the horizontal stress difference is greater than the tensile strength. This reservoir type can be characterized by defining the geostress imbalance coefficient using the mechanical parameters for engineering quality evaluation in step 2:

[0080] The ground stress imbalance coefficient F3 is:

[0081]

[0082] Combining the above different types of geological characteristics analysis, a thermal reservoir classification discriminant function is constructed:

[0083] F=F1*F2*F3

[0084] Where: F is the classification discriminant function of the thermal reservoir; it can be seen from the formula that when any one of F1, F2, and F3 is 0, F=0, indicating that it belongs to a dense hot dry rock formation; at this time, the construction of the later enhanced geothermal system is mainly based on fracturing to form horizontal pancake-shaped tensional fractures; and only when any one of F1, F2, and F3 is not 0, it means that the characteristics of the thermal reservoir do not meet any of the conditions of the dense hot dry rock formation. At this time, F≠0, the thermal reservoir belongs to a typical fractured hot dry rock formation; due to the development of natural fractures and the high degree of rock fragmentation, the construction of the later enhanced geothermal system is a natural fracture network, and the use of clean water fracturing causes shear displacement of the fracture surface to increase the heat exchange capacity.

[0085] Example 2

[0086] This example is based on the well logging data of Well J in Gonghe Basin, Qinghai Province. Figure 1 , the present invention is further described as follows: Well J is a hot dry rock evaluation well in the Gonghe Basin of Qinghai. Figure 1 This is an evaluation result diagram of the classification method of hot dry rock reservoirs based on geophysical characteristic analysis; it can be seen from the figure that at 1800-3240m, the degree of rock fracture is strong, the fracture direction is quite different from the minimum principal stress direction, and the horizontal stress difference is between the tensile strength and the shear strength, and the comprehensive evaluation index F≠0, so the formation is a fracture-type EGS system; at 3240-4000m, the degree of rock fracture is low, the fracture direction is close to the minimum principal stress direction, and the horizontal stress difference is greater than the tensile strength, and the comprehensive evaluation index F=0, at this time the formation is a dense EGS system.

[0087] The application of the hot dry rock reservoir classification method based on geophysical characteristic analysis of the present invention adopts a quantitative discrimination method to realize the classification and division of geothermal resources in the research block, thereby determining the selection of fracturing development measures in the regional later enhanced geothermal system.

[0088] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, a person skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A classification method for hot dry rock reservoirs based on geophysical characteristics analysis, characterized in that: The steps include: Evaluate the thermal storage quality of hot dry rock reservoirs and obtain the rock mass fracture coefficient F1 and fracture occurrence coefficient ω; Evaluate the engineering quality of hot dry rock reservoirs and obtain tensile strength T0, maximum horizontal principal stress σ H , minimum horizontal principal stress σ h ; Constructing a classification and discrimination model for hot dry rock thermal reservoirs and obtaining a classification and discrimination function for hot dry rock thermal reservoirs; The category of hot dry rock thermal reservoir is obtained according to the classification discriminant function of hot dry rock thermal reservoir.

2. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 1 is characterized in that: The classification discriminant function of the hot dry rock reservoir is: F=F1*F2*F3 Where: F is the thermal reservoir classification discriminant function; F2 is the dominant occurrence index, when the trend of the hot dry rock fracture is close to the minimum principal stress direction, F2 = 0; when the trend of the hot dry rock fracture is greatly different from the minimum principal stress direction, F2 = 1; F3 is the ground stress imbalance coefficient, when the horizontal stress difference of the hot dry rock fracture is greater than the tensile strength, the formation can only undergo tensile fracture, F3 = 0; when the horizontal stress difference of the hot dry rock fracture is between the tensile strength and the shear strength, the formation undergoes shear fracture, F3 = 1.

3. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 2 is characterized in that: The method for obtaining the category of hot dry rock thermal reservoirs according to the classification discriminant function of hot dry rock thermal reservoirs is: When any one of F1, F2, and F3 is 0, F=0, and the hot dry rock thermal reservoir belongs to a dense hot dry rock formation; when and only when any one of F1, F2, and F3 is not 0, at this time F≠0, the hot dry rock thermal reservoir belongs to a typical fractured hot dry rock formation.

4. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 1, characterized in that: The rock mass rupture coefficient F1 is: in, φ is the matrix porosity value evaluated by conventional logging compensated sonic logging; Δt is the compensated sonic time difference; Δt f is the time difference of fluid sound wave; Δt ma is the acoustic time difference of the formation skeleton; Jz is the density of fracture development around the well evaluated by well logging; Jp is the density of fracture development beside the well evaluated by well logging.

5. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 2, characterized in that: The dominant occurrence index F2 is: Among them, ω is the crack occurrence coefficient, which represents the angle between the crack strike and the direction of the maximum horizontal principal stress.

6. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 2, characterized in that: The ground stress imbalance coefficient F3 is: Where T0 is the tensile strength; σ H is the maximum horizontal principal stress: σ h is the minimum horizontal principal stress.

7. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 5, characterized in that: The fracture occurrence coefficient ω is: Where: h i f is the crack direction within a certain range in the crack statistical rose diagram; i is the frequency proportion of a certain range in the fracture statistical rose diagram; t is the total share in the fracture statistical rose diagram; α is the direction of the maximum horizontal principal stress evaluated by well logging.

8. The method for classifying hot dry rock reservoirs based on geophysical characteristic analysis according to claim 6, characterized in that: The tensile strength T0 is: Maximum horizontal principal stress σ H for: Minimum horizontal principal stress σ h for: Where: δ is the internal friction angle of rock, FK1 is the static mode tectonic stress coefficient 1, with an implicit value of 1.0; FK2 is the static mode tectonic stress coefficient 2, with an implicit value of 0.4; PP is the formation pore pressure; PO is the overburden pressure; α is the Boit constant; ν is the Poisson's ratio, and: ν P is the P-wave velocity extracted from the cross-dipole array acoustic logging; ν S Shear wave velocity extracted for a crossed-dipole array sonic log.

9. Application of the classification method of hot dry rock reservoirs based on geophysical characteristics analysis, characterized in that: A quantitative identification method is used to classify the geothermal resources in the study area, thereby determining the selection of fracturing development measures in the later enhanced geothermal system in the region.

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