Fractured carbonate rock heat storage area selection evaluation method and system

Abstract

The invention discloses a fractured carbonate rock heat storage area selection evaluation method and a fractured carbonate rock heat storage area selection evaluation system. The heat storage selected area evaluation method comprises the following steps: predicting fractured carbonate rock heat storage key factors of a target area to obtain parameter data of each heat storage key factor; the heat storage key factors comprise heat storage burial depth, fracture development, water-rich characteristics and temperature distribution; determining an optimal evaluation area based on the parameter data of the heat storage burial depth; performing quantitative processing on parameter data of fracture development, water-rich characteristics and temperature distribution of the optimal evaluation area, and setting weight coefficients of the fracture development, the water-rich characteristics, the temperature distribution and the parameters; and based on a quantitative processing result, a weight coefficient and an evaluation standard, carrying out crack type carbonate rock heat storage comprehensive evaluation on the optimal evaluation region. The method can rapidly, effectively and accurately complete heat storage selection area evaluation, improves evaluation efficiency, improves the success rate of geothermal well drilling, and has the characteristics of prominent key parameters, simple calculation, convenience and rapidness.

Description

Technical Field

[0001] This invention belongs to the field of geothermal resource exploration and development technology, and more specifically, relates to a method and system for evaluating fractured carbonate reservoirs. Background Technology

[0002] In recent years, with the introduction of dual-carbon targets, the geothermal industry has experienced rapid development. my country is rich in geothermal resources, primarily used for urban geothermal heating in the eastern region, with the main developed reservoirs being Cambrian-Ordovician fractured carbonate reservoirs. However, these reservoirs are highly heterogeneous due to factors such as fracture structures, resulting in significant variations in single-well productivity, which severely impacts the efficient and economical development and utilization of geothermal resources. Therefore, it is necessary to conduct site selection evaluations for fractured carbonate reservoirs to provide a scientific basis for geothermal well deployment, improve drilling success rates, and enhance the economic benefits of geothermal heating.

[0003] In oil and gas exploration, quantitative description of carbonate geothermal reservoirs is mainly based on geophysical data such as well logging and seismic data to guide reservoir selection and evaluation. However, the evaluation technology for geothermal reservoirs, especially fractured carbonate geothermal reservoirs, is limited by the application of geophysical data such as seismic data. Its evaluation methods and parameters differ significantly from those for oil and gas reservoirs, and therefore cannot be directly used to guide geothermal resource exploration and development.

[0004] Based on the exploration experience of fractured carbonate reservoirs, studies suggest that reservoir depth, fracture development, water-bearing characteristics, and temperature distribution are important factors for geothermal well deployment. However, there is currently no unified technical solution for evaluating and comprehensively analyzing these factors as key elements, nor is there a quantitative method for evaluating the selection of fractured carbonate reservoirs.

[0005] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to propose a method and system for evaluating fractured carbonate reservoirs, which uses reservoir depth, fracture development, water-bearing characteristics, and temperature distribution as key factors to quantitatively evaluate fractured carbonate reservoirs. This provides a more comprehensive decision-making reference for the development and utilization of geothermal resources, can comprehensively evaluate the risks in geothermal resource exploration and development, and improve the success rate of geothermal well drilling.

[0007] To achieve the above objectives, this invention proposes a method and system for evaluating fractured carbonate reservoir geothermal areas.

[0008] According to a first aspect of the present invention, a method for evaluating fractured carbonate reservoir geothermal areas is proposed, comprising:

[0009] The key factors of fractured carbonate reservoirs in the target area are predicted to obtain parameter data for each of the key reservoir factors.

[0010] Key factors for geothermal reservoirs include: reservoir depth, fault development, water-rich characteristics, and temperature distribution.

[0011] The optimal evaluation area is determined based on the parameter data of the geothermal reservoir burial depth;

[0012] The parameter data of the fracture development, water-bearing characteristics and temperature distribution in the optimal evaluation region are quantified, and the weight coefficients of the fracture development, water-bearing characteristics and temperature distribution and each parameter are set.

[0013] Based on the quantitative processing results, the weighting coefficients, and the evaluation criteria, a comprehensive evaluation of the fractured carbonate reservoir in the optimal evaluation area is conducted.

[0014] Optionally, the prediction of key factors for fractured carbonate reservoirs in the target area includes:

[0015] Predict the burial depth of the target area's thermal reservoir based on the plan view of the top surface burial depth of the carbonate reservoir;

[0016] Predict the fracture development in the target region based on the fracture development zone and crack development zone of the target region;

[0017] Predict the water-rich characteristics of the target region based on resistivity and radioactivity curves;

[0018] The average temperature in the middle of the reservoir is calculated based on the plan view of the burial depth of the top surface of the carbonate reservoir, and the temperature distribution of the target area is predicted based on the average temperature in the middle of the reservoir.

[0019] Optionally, the expression for calculating the average temperature in the middle of the thermal reservoir is:

[0020] T=T0+△t1×(H-H0) / 100+△t2×Hm / 100;

[0021] Where T is the temperature in the middle of the reservoir, in °C; T0 is the temperature of the isothermal layer, in °C; H0 is the depth of the isothermal layer, in meters; H is the burial depth of the top surface of the reservoir, in meters; Δt1 is the average geothermal gradient of the caprock, in °C / 100m; Δt2 is the average geothermal gradient of the reservoir, in °C / 100m; and Hm is half the thickness of the reservoir, in meters.

[0022] Optionally, the setting of the fracture development, water-rich characteristics, temperature distribution, and weighting coefficients for each parameter includes:

[0023] The weighting coefficients for the fracture development, the water-rich characteristics, and the temperature distribution are set to 0.4, 0.3, and 0.3, respectively.

[0024] The parameters for fracture development include fracture development state and crack development degree, with weighting coefficients of 0.6 and 0.4 for the fracture development state and crack development degree, respectively.

[0025] The parameters of the water-rich characteristics include resistivity and radioactivity, and the weighting coefficients for resistivity and radioactivity are set to 0.8 and 0.2, respectively.

[0026] The parameters of the temperature distribution include setting the average temperature in the middle of the thermal reservoir, with a weighting coefficient of 1 for the average temperature in the middle of the thermal reservoir.

[0027] Optionally, determining the optimal evaluation area based on the parameter data of the geothermal reservoir burial depth includes:

[0028] The target area is divided into four regions based on the burial depth of the top surface of the thermal storage.

[0029] The area with a top surface of the thermal reservoir buried at a depth of 800-2000m is designated as the first area, the area with a top surface of the thermal reservoir buried at a depth of 2000-2500m is designated as the second area, the area with a top surface of the thermal reservoir buried at a depth of 2500-3000m is designated as the third area, and the area with a top surface of the thermal reservoir buried at a depth of more than 3000m is designated as the fourth area.

[0030] The first region is the optimal evaluation region.

[0031] Optionally, the quantification of the parameter data of fracture development, water-rich characteristics, and temperature distribution in the optimal evaluation region includes:

[0032] The fracture development status is quantified as follows: fracture fracture zone is quantified as 1, fracture and large-scale crack development is quantified as 0.6, few fractures and no large-scale crack development is quantified as 0.3, and fracture and large-scale crack development is quantified as 0.1.

[0033] The degree of crack development is quantified as follows: well-developed is quantified as 1, moderately developed is quantified as 0.6, moderately developed is quantified as 0.3, and no development is quantified as 0.1.

[0034] The resistivity is quantified as follows: obvious low resistance anomaly is quantified as 1, relatively obvious low resistance anomaly is quantified as 0.6, generally obvious low resistance anomaly is quantified as 0.3, and inconspicuous low resistance anomaly is quantified as 0.1.

[0035] The radioactivity is quantified as follows: a significant high radioactivity anomaly is quantified as 1, a relatively high radioactivity anomaly is quantified as 0.6, a moderate radioactivity anomaly is quantified as 0.3, and a low radioactivity anomaly is quantified as 0.1.

[0036] The average temperature in the middle of the thermal reservoir is quantified as follows: greater than 65℃ is quantified as 1, greater than 55℃ and less than or equal to 65℃ is quantified as 0.6, greater than 40℃ and less than or equal to 55℃ is quantified as 0.3, and less than or equal to 40℃ is quantified as 0.1.

[0037] Optionally, the comprehensive evaluation of the fractured carbonate reservoir in the optimal evaluation area based on the quantification results, the weighting coefficients, and the evaluation conditions includes:

[0038] Based on the quantification results of each parameter and the weighting coefficients of each parameter, the scores of the fracture development, water-rich characteristics and temperature distribution at each location within the optimal evaluation area are calculated.

[0039] The comprehensive evaluation factor for each of the aforementioned locations is calculated based on the scores and corresponding weighting coefficients for fracture development, water-rich characteristics, and temperature distribution.

[0040] The thermal storage is rated based on the comprehensive evaluation factors and evaluation criteria for each location.

[0041] Optionally, the expression for calculating the comprehensive evaluation factor is:

[0042] A = aX1 + bX2 + cX3;

[0043] Where A is the comprehensive evaluation factor, a is the weighting coefficient corresponding to fracture development, b is the weighting coefficient corresponding to water-rich characteristics, c is the weighting coefficient corresponding to temperature distribution, X1 is the quantitative result of the parameters of fracture development, X2 is the quantitative result of the parameters of water-rich characteristics, and X3 is the quantitative result of the parameters of temperature distribution.

[0044] Optionally, the evaluation criteria include:

[0045] When A > 0.7, the thermal storage area is rated as Class I.

[0046] When 0.7 ≤ A < 0.3, the thermal storage area is rated as Class II.

[0047] When 0.3≤A≤0.1, the thermal storage area is rated as Class III.

[0048] Among them, Zone I is the optimal well location deployment area.

[0049] According to a second aspect of the present invention, a system for evaluating fractured carbonate reservoir geothermal areas is proposed, comprising:

[0050] The prediction module is used to predict the key factors of fractured carbonate reservoirs in the target area in order to obtain parameter data of each of the key factors of the reservoir.

[0051] Key factors for geothermal reservoirs include: reservoir depth, fault development, water-rich characteristics, and temperature distribution.

[0052] The determination module is used to determine the optimal evaluation area based on the parameter data of the geothermal storage burial depth;

[0053] The quantization processing and setting module quantifies the parameter data of the fracture development, water-rich characteristics and temperature distribution in the optimal evaluation area, and sets the weight coefficients of the fracture development, water-rich characteristics and temperature distribution and each parameter.

[0054] The comprehensive evaluation module is used to conduct a comprehensive evaluation of the fractured carbonate reservoir in the optimal evaluation area based on the quantitative processing results, the weighting coefficients, and the evaluation criteria.

[0055] The beneficial effects of this invention are as follows: This invention uses reservoir burial depth, fracture development, water-bearing characteristics, and temperature distribution as key factors for evaluating fractured carbonate reservoirs. It obtains parameter data for these four key factors in the target area through prediction; it determines the optimal evaluation area using the reservoir burial depth parameter data, thus narrowing the evaluation scope and reducing the workload; it quantifies the parameter data of fracture development, water-bearing characteristics, and temperature distribution in the optimal evaluation area to eliminate differences in attributes between different key factors and corresponding parameters, making the results more comparable; and it sets corresponding weighting coefficients based on the correlation between fracture development, water-bearing characteristics, temperature distribution, and corresponding parameters with the reservoir, thereby comprehensively evaluating the optimal evaluation area and obtaining recommended well locations. This invention enables rapid, effective, and accurate reservoir selection evaluation, comprehensively assesses risks in geothermal resource exploration and development, improves the success rate of geothermal well drilling, and provides more comprehensive decision-making references for geothermal field resource development and utilization. Furthermore, this invention features prominent key parameters, simple calculation, and convenient and rapid operation.

[0056] The system of the present invention has other features and advantages that will be apparent from or will be set forth in detail in the accompanying drawings and following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0057] The above and other objects, features and advantages of the present invention will become more apparent from the accompanying drawings, in which like reference numerals generally denote like parts.

[0058] Figure 1A flowchart illustrating the steps of a method for evaluating fractured carbonate reservoirs according to the present invention is shown.

[0059] Figure 2 A schematic diagram of the burial depth zoning of fractured carbonate reservoirs according to Embodiment 1 of the present invention is shown.

[0060] Figure 3 A schematic diagram of the fracture development evaluation of fractured carbonate reservoirs according to Embodiment 1 of the present invention is shown.

[0061] Figure 4 A resistivity inversion profile and a schematic diagram of suggested well locations are shown according to Embodiment 1 of the present invention.

[0062] Figure 5 A schematic diagram of a fractured carbonate reservoir selection evaluation system according to Embodiment 2 of the present invention is shown. Detailed Implementation

[0063] The invention will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0064] like Figure 1 As shown, a method for evaluating fractured carbonate reservoir geothermal reservoirs according to the present invention includes:

[0065] The key factors of fractured carbonate reservoirs in the target area are predicted to obtain parameter data for each key factor. The key factors include: reservoir depth, fault development, water-bearing characteristics, and temperature distribution.

[0066] The optimal evaluation area is determined based on parameter data of the geothermal reservoir burial depth;

[0067] The parameter data of fracture development, water-bearing characteristics and temperature distribution in the optimal evaluation area are quantified, and the weight coefficients of fracture development, water-bearing characteristics and temperature distribution and each parameter are set.

[0068] A comprehensive evaluation of fractured carbonate reservoirs was conducted based on the quantitative processing results, weighting coefficients, and evaluation criteria.

[0069] Specifically, based on the comprehensive exploration practice of fractured carbonate reservoirs, this study considers reservoir depth, fracture development, water-bearing characteristics, and temperature distribution to be important bases and references for geothermal well deployment. Therefore, this invention selects reservoir depth, fracture development, water-bearing characteristics, and temperature distribution as key factors for fractured carbonate reservoirs to conduct reservoir site selection evaluation in target areas. This invention uses geophysical and geological data to predict the key factors of fractured carbonate reservoirs in target areas, and obtains parameter data of each key factor based on the prediction results. For example, using non-seismic exploration methods and combining existing geological borehole data, the reservoir depth in the target area is described, resulting in a plan view of the top surface depth of the carbonate reservoir, and obtaining parameter data of the reservoir depth in the target area, i.e., the top surface depth data of the reservoir. Then, the optimal evaluation area is determined based on the parameter data of the reservoir burial depth. For example, the area with a burial depth of 800-2000m above the reservoir top surface is set as the optimal evaluation area. Determining the optimal evaluation area from the target area based on the reservoir burial depth before conducting a comprehensive evaluation eliminates the need for a comprehensive evaluation of the entire target area, significantly reducing the workload and improving efficiency. After determining the optimal evaluation area, the parameter data of fault development, water-bearing characteristics, and temperature distribution within that area are quantified, and weighting coefficients are set for these parameters. For example, the weights for fault development, water-bearing characteristics, and temperature distribution are set to 0.4, 0.3, and 0.3, respectively. Quantification eliminates differences in these parameters due to varying properties, making the results more comparable. Finally, based on the quantitative processing results, fracture development, water-rich characteristics, temperature distribution, and the corresponding parameter weighting coefficients and evaluation standards, a weighted comprehensive analysis method is used to conduct a comprehensive evaluation of the fractured carbonate reservoir in the optimal evaluation area, providing a basis for well location layout. Compared with traditional qualitative evaluation methods, the carbonate reservoir selection evaluation method of this invention can comprehensively evaluate the risks in geothermal resource exploration and development, improve the success rate of geothermal well drilling, and has the characteristics of highlighting key parameters, simple calculation, and convenience and speed.

[0070] In one example, the prediction of key factors for fractured carbonate reservoirs in a target area includes:

[0071] Predict the burial depth of the target area's thermal reservoir based on the plan view of the top surface burial depth of the carbonate reservoir;

[0072] Predict the fracture development in the target area based on the fracture development zone and crack development zone of the target area;

[0073] Predicting water-rich characteristics of the target area based on resistivity curves and radioactivity curves;

[0074] The average temperature in the middle of the reservoir is calculated based on the plan view of the burial depth of the top surface of the carbonate reservoir, and the temperature distribution of the target area is predicted based on the average temperature in the middle of the reservoir.

[0075] Specifically, for the reservoir burial depth, non-seismic exploration methods are mainly used, combined with existing geological borehole data, to describe the reservoir burial depth in the study area, obtaining a plan view of the top surface burial depth of the carbonate reservoir. For fault development, firstly, electrical and wave velocity characteristics are used to identify faults and determine fault development zones; secondly, statistical analysis methods are used to obtain the relationship between faults and fractures, indirectly obtaining fracture development zones and completing fault-fracture prediction. For water-rich characteristics, qualitative description is the primary method. Generally, after a reservoir becomes water-rich, the resistivity will show a significant downward pull, and radiometric measurements will also show certain anomalies. That is, the apparent resistivity curve shows a significant low value near the carbonate strata, especially showing a relatively low value against a high value background, which is considered a possible water-rich area; the radiometric curve shows a transition from a relatively high value area to a relatively low value area, and the transition area is considered a possible water-rich area. For temperature distribution, based on the reservoir top surface burial depth map, the average temperature in the middle of the reservoir is obtained using calculation formulas, and the temperature distribution of the target area is predicted based on the average temperature in the middle of the reservoir.

[0076] In one example, the expression for calculating the average temperature in the middle of the thermal reservoir is:

[0077] T=T0+△t1×(H-H0) / 100+△t2×Hm / 100;

[0078] Where T is the temperature in the middle of the reservoir, in °C; T0 is the temperature of the isothermal layer, in °C; H0 is the depth of the isothermal layer, in meters; H is the burial depth of the top surface of the reservoir, in meters; Δt1 is the average geothermal gradient of the caprock, in °C / 100m; Δt2 is the average geothermal gradient of the reservoir, in °C / 100m; and Hm is half the thickness of the reservoir, in meters.

[0079] Specifically, T0 is determined based on previous statistical research results; H0 is determined based on previous statistical research results; H is determined based on the burial depth map of the top surface of the thermal reservoir; Δt1 and Δt2 are calculated based on borehole data; and Hm is determined based on statistics from borehole data.

[0080] In one example, the settings for fracture development, water-rich characteristics, and temperature distribution, as well as the weighting coefficients for each parameter, include:

[0081] The weighting coefficients for fracture development, water-rich characteristics, and temperature distribution are set to 0.4, 0.3, and 0.3, respectively.

[0082] The parameters for fracture development include fracture development state and crack development degree, with weighting coefficients of 0.6 and 0.4 for fracture development state and crack development degree, respectively.

[0083] The parameters for water-rich characteristics include resistivity and radioactivity, with weighting coefficients of 0.8 and 0.2 for resistivity and radioactivity, respectively.

[0084] The parameters for temperature distribution include setting the average temperature in the middle of the thermal reservoir, with a weighting coefficient of 1 for the average temperature in the middle of the thermal reservoir.

[0085] Specifically, regarding fault development, based on exploration practice, accurate prediction of fault development zones is crucial for the refined exploration of fractured carbonate reservoirs. Therefore, a weighting coefficient of 0.4 is set for fault-fracture quantitative description, comprehensively considering both fault development status and fracture development degree. Fault development status is the primary factor, with a weighting coefficient of 0.6, while fracture development degree is weighted at 0.4. Regarding water-bearing characteristics, based on exploration practice, effective identification of water-bearing zones is core to successful exploration of fractured carbonate reservoirs, with a weighting coefficient of 0.3. Considering both electrical and radioactive characteristics of water-bearing reservoirs, low resistivity is the primary factor, with a weighting coefficient of 0.8. Due to significant interference from radioactive anomalies, a weighting coefficient of 0.2 is used. Regarding temperature distribution, based on exploration practice, reservoir temperature is also an important factor for successful exploration of fractured carbonate reservoirs, with a weighting coefficient of 0.3. Temperature distribution primarily considers the temperature in the central part of the reservoir, with a weighting coefficient of 1 for the central temperature.

[0086] In one example, determining the optimal evaluation area based on parameter data of the geothermal reservoir burial depth includes:

[0087] The target area is divided into four regions based on the burial depth of the top surface of the thermal reservoir;

[0088] The area with a top surface of the thermal reservoir buried at a depth of 800-2000m is designated as the first area, the area with a top surface of the thermal reservoir buried at a depth of 2000-2500m is designated as the second area, the area with a top surface of the thermal reservoir buried at a depth of 2500-3000m is designated as the third area, and the area with a top surface of the thermal reservoir buried at a depth of more than 3000m is designated as the fourth area.

[0089] The first region is the optimal evaluation region.

[0090] Specifically, based on exploration practice, it is believed that accurate characterization of reservoir depth is fundamental to efficient exploration of fractured carbonate reservoirs. Therefore, the target area is divided into four zones using a plan view of the reservoir top surface depth. The first zone, with a reservoir top surface depth of 800-2000m, represents the area where well placement is most favorable for carbonate reservoirs. The second zone, with a reservoir top surface depth of 2000-2500m, also represents the area where well placement is relatively favorable for carbonate reservoirs. The third region, with a top surface burial depth of 2500-3000m, is a generally favorable area for well placement in carbonate reservoirs. The fourth region, with a top surface burial depth exceeding 3000m, is unfavorable for reservoir porosity and fracture formation, making it an area where well placement in carbonate reservoirs is not recommended. Therefore, the first region was selected for subsequent comprehensive evaluation. By determining the optimal evaluation area from the target region based on reservoir burial depth, a comprehensive evaluation can be conducted without needing to evaluate the entire target region, significantly reducing the workload and improving efficiency.

[0091] In one example, the quantification of parameter data on fracture development, water-bearing characteristics, and temperature distribution in the optimal evaluation region includes:

[0092] The development status of fractures was quantified as follows: fracture fracture zones were quantified as 1, fractures and large-scale cracks were quantified as 0.6, fractures were few and large-scale cracks were not developed as 0.3, and fractures and large-scale cracks were not developed as 0.1.

[0093] The degree of crack development was quantified: well-developed was quantified as 1, moderately developed as 0.6, generally developed as 0.3, and undeveloped as 0.1.

[0094] The resistivity is quantified as follows: obvious low resistance anomalies are quantified as 1, moderate low resistance anomalies are quantified as 0.6, general low resistance anomalies are quantified as 0.3, and insignificant low resistance anomalies are quantified as 0.1.

[0095] Radioactivity is quantified as follows: a significant high radioactivity anomaly is quantified as 1, a relatively high radioactivity anomaly is quantified as 0.6, a moderate radioactivity anomaly is quantified as 0.3, and a low radioactivity anomaly is quantified as 0.1.

[0096] The average temperature in the middle of the thermal reservoir is quantified as follows: greater than 65℃ is quantified as 1, greater than 55℃ and less than or equal to 65℃ is quantified as 0.6, greater than 40℃ and less than or equal to 55℃ is quantified as 0.3, and less than or equal to 40℃ is quantified as 0.1.

[0097] In one example, the comprehensive evaluation of fractured carbonate reservoirs in the optimal evaluation area based on quantification results, weighting coefficients, and evaluation conditions includes:

[0098] Based on the quantitative processing results of each parameter and the weight coefficient of each parameter, the scores of fracture development, water-rich characteristics and temperature distribution at each location in the optimal evaluation area are calculated.

[0099] The comprehensive evaluation factor for each location is calculated based on the scores and corresponding weighting coefficients of fracture development, water-rich characteristics, and temperature distribution.

[0100] The thermal reservoir is rated based on the comprehensive evaluation factors and evaluation standards for each location.

[0101] In one example, the expression for calculating the comprehensive evaluation factor is:

[0102] A = aX1 + bX2 + cX3;

[0103] Where A is the comprehensive evaluation factor, a is the weighting coefficient corresponding to fracture development, b is the weighting coefficient corresponding to water-rich characteristics, c is the weighting coefficient corresponding to temperature distribution, X1 is the quantitative result of the parameters of fracture development, X2 is the quantitative result of the parameters of water-rich characteristics, and X3 is the quantitative result of the parameters of temperature distribution.

[0104] In one example, the evaluation criteria include:

[0105] When A > 0.7, the thermal storage area is rated as Class I.

[0106] When 0.7 ≤ A < 0.3, the thermal storage area is rated as Class II.

[0107] When 0.3≤A≤0.1, the thermal storage area is rated as Class III.

[0108] Among them, Zone I is the optimal well location deployment area.

[0109] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the invention. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present invention can be combined with each other.

[0110] Example 1

[0111] This embodiment provides a method for evaluating fractured carbonate reservoir geothermal areas, including:

[0112] I. Prediction and acquisition of key factors in fractured carbonate reservoirs.

[0113] (1) For the burial depth of the geothermal reservoir, non-seismic exploration methods are mainly used, combined with existing geological borehole data, to describe the burial depth of the geothermal reservoir in the study area, and to obtain a plan view of the burial depth of the top surface of the carbonate geothermal reservoir, such as... Figure 2 As shown.

[0114] MT, CSAMT, and micro-motion methods were used for exploration in Rongsheng Community and Taoyuan Community of Qihe County, Shandong Province. Combined with existing gravity and magnetic planar exploration results and actual drilling results, the burial depth of the geothermal reservoir in the study area was characterized. Figure 2 As can be seen, the top surface of the geothermal reservoir is buried in a northeast direction, showing the characteristic of being deeper in the west and shallower in the east. The geothermal reservoir is shallower on the east side of the northeast-trending fault, less than 2000m, while the geothermal reservoir on the west side is gradually deeper, even exceeding 3000m.

[0115] (2) For fracture development, firstly, the electrical characteristics and wave velocity characteristics are used to identify fractures and determine the fracture development area; secondly, the statistical analysis method is used to obtain the relationship between fractures and cracks, and the crack development area is indirectly obtained to complete the fracture-crack prediction.

[0116] Electromagnetic and micromotion data were used to interpret the faults in Rongsheng Community and Taoyuan Community in Qihe County, Shandong Province. It was found that the faults in the study area are mainly NE-trending, with secondary NW-trending faults. Among them, the NE-trending Jiaobintun Fault is the main fault in the study area, dipping southwest with a displacement of about 800m.

[0117] For fracture prediction, due to the lack of seismic data in urban areas, this study mainly relied on statistical analysis of the single-well productivity (unit yield) of existing wells and their distance from the fracture (root mean square distance) to indirectly identify areas with a high degree of fracture development. Statistical analysis showed that geothermal well productivity was relatively good when the well was within 600m of the fracture, and decreased with increasing distance. Therefore, areas within 600m of the fracture were defined as fracture-developing regions.

[0118] (3) The water-rich characteristics are mainly described qualitatively. Generally speaking, after the thermal reservoir becomes water-rich, the resistivity will show a significant downward pull and decrease, and the radioactivity measurement will also show certain anomalies.

[0119] In Rongsheng Community and Taoyuan Community of Qihe County, Shandong Province, non-seismic data were used to characterize low-resistivity areas under high-resistivity backgrounds, suggesting that low-resistivity areas are potential water-rich areas.

[0120] (4) For the temperature distribution, the average temperature in the middle of the reservoir is obtained using a calculation formula based on the burial depth map of the top surface of the reservoir. The calculation formula is: T=T0+△t1×(H-H0) / 100+△t2×Hm / 100

[0121] Where T is the temperature in the middle of the geothermal reservoir (°C); T0 is the temperature of the isothermal layer (°C), which is 16°C according to previous statistical studies; H0 is the depth of the isothermal layer (m), which is 30m according to previous statistical studies; H is the burial depth of the top surface of the geothermal reservoir; △t1 is the average geothermal gradient of the caprock (°C / 100m); △t2 is the average geothermal gradient of the geothermal reservoir (°C / 100m); and Hm is half the thickness of the geothermal reservoir (m).

[0122] Based on the top surface burial depth map of the carbonate reservoir in the Qihe area, and using the average geothermal gradient of the caprock (approximately 2.4℃ / 100m), the average geothermal gradient of the reservoir (approximately 1.5℃ / 100m), and the half-thickness Hm of the reservoir (350m), the temperature in the central part of the reservoir was calculated and mapped. The overall reservoir temperature is affected by burial depth, exhibiting a characteristic of increasing temperature from east to west.

[0123] II. Quantification of key factors and determination of weighting coefficients for fractured carbonate reservoirs.

[0124] The first step is to divide the thermal reservoir burial depth of the evaluation area into zones.

[0125] The evaluation area was divided into four regions based on the burial depth of the thermal reservoir, such as Figure 2 As shown in Table 1, the solid and dashed black lines represent the boundaries of each region, and the red lines represent faults. Region 1 has a geothermal reservoir depth of 800-2000m, is located in a structurally high area, and has generally good quality non-seismic data, making it the most favorable region for geothermal reservoir depth. Region 2 has a geothermal reservoir depth of 2000-2500m, is located within a fault step zone, and has good quality non-seismic data, making this region relatively favorable for geothermal reservoir depth. Region 3 has a geothermal reservoir depth of 2500-3000m, is located in a depression, and has average quality non-seismic data, making this region generally favorable for geothermal reservoir depth. Region 4 has a geothermal reservoir depth greater than 3000m, is located in a depression, and has poor quality non-seismic data, making it the unfavorable region for geothermal reservoir depth, as shown in Table 1.

[0126] Table 1. Zoning of Thermal Storage Burial Depth Characteristics

[0127]

[0128] The second step involves quantifying and assigning values ​​to three key factors: fracture development, water-rich characteristics, and temperature distribution.

[0129] (1) Regarding the development of faults, based on exploration practice, it is believed that accurate prediction of the fault development zone is the key to fine exploration of fractured carbonate reservoirs, and its weighting coefficient is 0.4.

[0130] A quantitative description of the fracture-fracture system was conducted, considering both the fracture development status and the degree of fracture development. The fracture development status was the primary factor, weighted at 0.6, while the degree of fracture development was weighted at 0.4, as shown in Table 2. In fracture-developed areas, and within 600m of the fracture, the fracture development quantification value was 1, indicating the most fracture-developed zone. Subsequent quantifications were performed for relatively well-developed, moderately well-developed, and poorly developed fracture zones, with corresponding values ​​of 0.6, 0.3, and 0.1, respectively. Higher scores indicate better fracture development in the carbonate reservoir. Figure 3 As shown.

[0131] Table 2 Quantitative parameters and weighting coefficients of fracture development

[0132]

[0133] (2) Regarding the water-rich characteristics, based on exploration practice, it is believed that the effective identification of water-rich development zones is the core of successful exploration of fractured carbonate reservoirs. Its weighting coefficient is taken as 0.3.

[0134] Taking into account both the electrical and radioactive characteristics of water-rich areas, the low resistivity of the electrical properties is the primary factor, with a weight of 0.8. Due to the significant interference of radioactive anomalies, the weight is set to 0.2. When a location exhibits a significant low resistivity anomaly and a high radioactive anomaly, the score is set to 1. The higher the score, the better the water-richness of the carbonate reservoir at that location. The water-rich area is quantified as 1. The remaining areas are quantified according to the degree of low resistivity anomaly: more obvious, generally obvious, and not obvious, with quantification values ​​of 0.6, 0.3, and 0.1, respectively, as shown in Table 3.

[0135] Table 3. Quantitative parameters and weighting coefficients of water-rich characteristics

[0136]

[0137] (4) Regarding temperature distribution, based on exploration practice, it is believed that reservoir temperature is also an important factor for successful exploration of fractured carbonate reservoirs, and its weighting coefficient is 0.3.

[0138] The main consideration is the temperature in the middle of the geothermal reservoir. As shown in Table 4, when the temperature is less than 40℃, the score is set to 0.1; when the temperature is greater than 40℃ and less than or equal to 55℃, the corresponding temperature quantification value is 0.3; when the temperature is greater than 55℃ and less than or equal to 65℃, the quantification value is 0.6; and when the temperature is greater than 65℃, the quantification value is 1. The larger the score, the higher the temperature of the carbonate rock geothermal reservoir in the area, which is more conducive to geothermal heating and thus improves the economic benefits of geothermal heating.

[0139] Table 4. Quantitative parameters and weighting coefficients for thermal storage temperature

[0140]

[0141] III. A weighted comprehensive analysis method is used to quantify the comprehensive evaluation of fractured carbonate reservoirs. The comprehensive evaluation factors are classified to identify favorable areas for fractured carbonate reservoirs, providing a basis for well location. The specific calculation formula is: A = aX1 + bX2 + cX3; where A is the comprehensive evaluation factor; a is the weighting coefficient corresponding to fracture development (0.4); b is the weighting coefficient corresponding to water-rich characteristics (0.3); c is the weighting coefficient corresponding to temperature distribution (0.3); X1 is the quantitative result of fracture development prediction; X2 is the quantitative result of water-rich characteristic prediction; and X3 is the quantitative result of temperature distribution prediction. When A > 0.7, the reservoir is rated as Class I; when 0.7 ≤ A < 0.3, the reservoir is rated as Class II; and when 0.3 ≤ A ≤ 0.1, the reservoir is rated as Class III.

[0142] Calculations show that the northeast-trending fault zone in Region 1 has the most developed faults, exhibiting significant low-resistivity and water-rich characteristics on the non-seismic profile, and a relatively low reservoir temperature (A = 0.79), classifying the reservoir as a Class I area. Well locations were strategically placed in Class I areas selected from the most favorable burial depth region 1, such as... Figure 2 and Figure 4 As shown.

[0143] Example 2

[0144] like Figure 5 As shown in the figure, this embodiment provides a selection evaluation system for fractured carbonate reservoirs, including:

[0145] The prediction module is used to predict key factors of fractured carbonate reservoirs in the target area in order to obtain parameter data of each key factor of the reservoir.

[0146] Key factors for geothermal reservoirs include: reservoir depth, fault development, water-rich characteristics, and temperature distribution.

[0147] The determination module is used to determine the optimal evaluation area based on parameter data of the geothermal reservoir burial depth;

[0148] The quantification and setting module quantifies the parameter data of fracture development, water-bearing characteristics and temperature distribution in the optimal evaluation area, and sets the weight coefficients of fracture development, water-bearing characteristics and temperature distribution as well as each parameter.

[0149] The comprehensive evaluation module is used to conduct a comprehensive evaluation of fractured carbonate reservoirs in the optimal evaluation area based on the quantitative processing results, weighting coefficients, and evaluation criteria.

[0150] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for evaluating a fractured carbonate reservoir selection area, characterized in that, The method comprises the following steps: predicting key factors of fractured carbonate rock heat reservoir in a target area to obtain parameter data of each key factor of the heat reservoir; wherein the key factors of the heat reservoir include heat reservoir burial depth, fracture development, water enrichment characteristics and temperature distribution; determining an optimal evaluation area based on the parameter data of the heat reservoir burial depth; quantitatively processing the parameter data of the fracture development, water enrichment characteristics and temperature distribution of the optimal evaluation area, and setting weight coefficients of the fracture development, water enrichment characteristics and temperature distribution and each parameter; comprehensively evaluating the fractured carbonate rock heat reservoir in the optimal evaluation area based on the quantitative processing result, the weight coefficients and evaluation criteria.

2. The method of claim 1, wherein, The prediction of the key factors of the fractured carbonate rock heat reservoir in the target area comprises: predicting the heat reservoir burial depth of the target area based on a carbonate rock heat reservoir top surface burial depth plan; predicting the fracture development of the target area based on a fracture development area and a fracture development area of the target area; predicting the water enrichment characteristics of the target area based on a resistivity curve and a radioactivity curve; calculating the average temperature in the middle of the heat reservoir based on a carbonate rock heat reservoir top surface burial depth plan, and predicting the temperature distribution of the target area based on the average temperature in the middle of the heat reservoir.

3. The method of claim 2, wherein, The expression for calculating the average temperature in the middle of the heat reservoir is: T=T0+△t1×(H-H0) / 100+△t2×Hm / 100; wherein T is the temperature in the middle of the heat reservoir, in ℃; T0 is the temperature of the isothermal layer, in ℃; H0 is the depth of the isothermal layer, in meters; H is the burial depth of the heat reservoir top surface, in meters; △t1 is the average geothermal gradient of the cap rock, in ℃ / 100m; △t2 is the average geothermal gradient of the heat reservoir layer, in ℃ / 100m; Hm is the half thickness of the heat reservoir layer, in meters.

4. The method of claim 1, wherein, The setting of the weight coefficients of the fracture development, water enrichment characteristics and temperature distribution and each parameter comprises: setting the weight coefficients of the fracture development, water enrichment characteristics and temperature distribution as 0.4, 0.3 and 0.3 respectively; the parameters of the fracture development include fracture development state and fracture development degree, and the weight coefficients of the fracture development state and the fracture development degree are set as 0.6 and 0.4 respectively; the parameters of the water enrichment characteristics include resistivity and radioactivity, and the weight coefficients of the resistivity and the radioactivity are set as 0.8 and 0.2 respectively; the parameter of the temperature distribution includes setting the average temperature in the middle of the heat reservoir, and the weight coefficient of the average temperature in the middle of the heat reservoir is 1.

5. The method of claim 1, wherein, The determination of the optimal evaluation area based on the parameter data of the heat reservoir burial depth comprises: dividing the target area into four areas based on the burial depth of the heat reservoir top surface; setting the area with a heat reservoir top surface burial depth of 800-2000m as the first area, the area with a heat reservoir top surface burial depth of 2000-2500m as the second area, the area with a heat reservoir top surface burial depth of 2500-3000m as the third area, and the area with a heat reservoir top surface burial depth exceeding 3000m as the fourth area; the first area is the optimal evaluation area.

6. The method of claim 4, wherein, The quantitative processing of the parameter data of the fracture development, water enrichment characteristics and temperature distribution of the optimal evaluation area comprises: The fracture development state is quantitatively processed: the fracture and fracture zone are quantified as 1, the fracture and large-scale crack development are quantified as 0.6, the fracture is less and the large-scale crack is not developed, and the fracture and large-scale crack are quantified as 0.1; The fracture development degree is quantitatively processed: development is quantified as 1, development is quantified as 0.6, development is quantified as 0.3, and development is quantified as 0.1; The resistivity is quantitatively processed: the low-resistance anomaly is obvious, the low-resistance anomaly is quantified as 1, the low-resistance anomaly is quantified as 0.6, the low-resistance anomaly is quantified as 0.3, and the low-resistance anomaly is not obvious, and the low-resistance anomaly is quantified as 0.1; The radioactivity is quantitatively processed: the radioactivity is high, the radioactivity is quantified as 1, the radioactivity is quantified as 0.6, the radioactivity is quantified as 0.3, and the radioactivity is low, and the radioactivity is quantified as 0.1; The average temperature in the middle of the thermal reservoir is quantitatively processed: greater than 65℃ is quantified as 1, greater than 55℃ and less than or equal to 65℃ is quantified as 0.6, greater than 40℃ and less than or equal to 55℃ is quantified as 0.3, and less than or equal to 40℃ is quantified as 0.

1.

7. The method of claim 1, wherein, The fracture type carbonate rock thermal reservoir comprehensive evaluation of the optimal evaluation area based on the quantitative processing results, the weight coefficient and the evaluation condition includes: Based on the quantitative processing results of each parameter and the weight coefficient of each parameter, the scores of the fracture development, water enrichment characteristics and temperature distribution of each position in the optimal evaluation area are calculated; Based on the scores of the fracture development, water enrichment characteristics and temperature distribution and the corresponding weight coefficients, the comprehensive evaluation factors of each position are calculated; Based on the comprehensive evaluation factors of each position and the evaluation standard, the thermal reservoir rating of each position is performed.

8. The method according to claim 7, wherein, The expression of the comprehensive evaluation factor is: A=aX1+bX2+cX3; Wherein, A is the comprehensive evaluation factor, a is the weight coefficient corresponding to the fracture development, b is the weight coefficient corresponding to the water enrichment characteristics, c is the weight coefficient corresponding to the temperature distribution, X1 is the quantitative result of the parameter of the fracture development, X2 is the quantitative result of the parameter of the water enrichment characteristics, and X3 is the quantitative result of the parameter of the temperature distribution.

9. The method according to claim 8, wherein, The evaluation standard includes: When A>0.7, the thermal reservoir rating is I class area; When 0.7≤A<0.3, the thermal reservoir rating is II class area; When 0.3≤A≤0.1, the thermal reservoir rating is III class area; Wherein, the I class area is the optimal well deployment area.

10. A system for evaluating fractured carbonate reservoir geothermal areas, characterized in that, It includes: A prediction module for predicting key factors of a fracture type carbonate rock thermal reservoir in a target area to obtain parameter data of each thermal reservoir key factor; Wherein, the thermal reservoir key factors include: thermal reservoir burial depth, fracture development, water enrichment characteristics and temperature distribution; A determination module for determining an optimal evaluation area based on the parameter data of the thermal reservoir burial depth; A quantitative processing and setting module for quantitatively processing the parameter data of the fracture development, water enrichment characteristics and temperature distribution of the optimal evaluation area, and setting the weight coefficients of the fracture development, water enrichment characteristics and temperature distribution and each parameter. The comprehensive evaluation module is configured to perform a comprehensive evaluation of the optimal evaluation area based on the quantization processing result, the weight coefficient, and an evaluation standard.

Images