A deep coal bed gas horizontal well perforation section optimization method based on logging data

Abstract

A kind of deep coal bed gas horizontal well perforation section optimization method based on well logging data, using conventional well logging data (natural gamma, gas side total hydrocarbon content), deep coal rock analysis test data (coal rock industrial component), first, crossplot means is used to determine the horizontal section completion quality parameter (Young's modulus, Poisson's ratio, brittleness index) in steps, then the formation reservoir quality parameter (gas side total hydrocarbon content) is arranged, finally, combined with the brittleness index parameter capable of reflecting the completion quality and the gas side total hydrocarbon content capable of reflecting the reservoir quality two parameters, the purpose is to form deep coal bed gas horizontal well perforation section comprehensive index to optimize and determine the horizontal section perforation favorable area;The application takes into account the mineability of reservoir and the compressibility of stratum, also reflects the formation reservoir quality and completion quality characteristics, emphasizes the influence of horizontal well section rock mechanics heterogeneity on perforation fracturing efficiency, with the characteristics of coal bed gas reservoir type evaluation precision, simple and practical method.

Description

Technical Field

[0001] This invention relates to the field of well logging evaluation technology for perforation fracturing in horizontal sections of deep coalbed methane wells, and particularly to a method for selecting the optimal perforation section in horizontal deep coalbed methane wells based on well logging data. Background Technology

[0002] In the development of deep coalbed methane, perforation fracturing and other production enhancement measures are often adopted. To maximize the fracturing effect in the horizontal section of coalbed methane wells, optimizing the perforation location using well logging data is an important task. Well logging data contains a wealth of reliable information about the formation radioactivity, lithology, coal and petrological industrial composition, rock mechanics, and enrichment patterns of the horizontal section of deep coalbed methane wells. Based on this, well logging data can be used to evaluate and optimize the perforation location in the horizontal section of deep coalbed methane wells.

[0003] There are various existing methods for selecting perforation sections in horizontal coalbed methane wells. Most adhere to the principle of uniformly perforating along the wellbore trajectory of the horizontal section, choosing a section relatively close to the coal seam with good cementing quality. However, because this only qualitatively considers the relative proximity of the coal seam and the quality of cementing, the selected perforation locations can be inappropriate. In actual production, factors such as formation reservoir quality (total hydrocarbon content on the gas side) and completion quality (Young's modulus, Poisson's ratio, brittleness index) affect the mechanical properties of the coal seam, including its low elastic modulus and high Poisson's ratio, as well as the swelling effect of clay minerals upon contact with water. This can lead to increased pump pressure and difficulties in adding proppant during fracturing operations, severely impacting the perforation and fracturing production enhancement effect of horizontal wells. For example, patent application CN202111312381.3, entitled "A Method for Selecting Perforation Locations in Horizontal Wells on the Coal Seam Roof to Improve the Volume of Coal Seam Fracturing Stimulation," discloses a comprehensive evaluation index prediction model for perforation locations in horizontal wells on the coal seam roof. This is a method for designing the perforation locations in horizontal wells based on the comprehensive evaluation index curve of the perforation location. However, it only considers reservoir quality parameters from well logging data and does not consider well completion quality parameters, thus failing to reflect the integrated geological engineering concept. For example, patent application CN201711400733.4, entitled "A Method for Segmented Fracturing of Horizontal Well Cluster Perforations," discloses a set of volumetric fracturing technologies developed for tight oil reservoirs in the Malang Depression of the Santanghu Basin. This method improves perforation efficiency by developing a matching ultra-low concentration, low-damage composite fracturing fluid system. However, it lacks further research on how to improve the synchronous initiation and extension of fractures within a single segment, thus having certain technical limitations. There is currently no research progress on how to combine the two factors of formation reservoir quality (total hydrocarbon content on the gas side) and completion quality (Young's modulus, Poisson's ratio, brittleness index) into a system for the optimal selection of perforation sections in the horizontal section of deep coalbed methane wells, which brings inconvenience to the selection of perforation sections in the horizontal section of deep coalbed methane wells. Summary of the Invention

[0004] To overcome the shortcomings of the existing technology, the present invention aims to provide a method for selecting the best perforation section in a horizontal well for deep coalbed methane based on well logging data. Utilizing conventional well logging data (natural gamma ray, gas-side total hydrocarbon content) and deep coal petrographic analysis data (coal petrographic industrial components), the method first uses cross-plotting to determine the completion quality parameters of the horizontal section (Young's modulus, Poisson's ratio, brittleness index) step by step. Then, it organizes the formation and reservoir quality parameters (gas-side total hydrocarbon content). Finally, it combines the brittleness index parameter, which reflects the completion quality, with parameters that reflect... Two parameters, namely the total hydrocarbon content on the gas side of the reservoir, are used to form a comprehensive index for perforation selection in horizontal wells of deep coalbed methane, which is used to optimize and determine the favorable perforation areas in the horizontal section. This method is proposed for horizontal wells of deep coalbed methane, taking into account both the recoverability of the reservoir and the compressibility of the formation, and reflecting the characteristics of both formation and reservoir quality and completion quality. It emphasizes the influence of the rock mechanical heterogeneity of the horizontal well section on the perforation and fracturing efficiency. While improving the accuracy of coalbed methane reservoir type evaluation, it also provides logging technology support for the optimization of fracturing sites. The method is simple and practical.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] A method for selecting the optimal perforated section in a deep coalbed methane horizontal well based on well logging data includes the following steps:

[0007] Step 1: Calculation of coal petrographic components using the cross-plot method

[0008] Based on the concept of cross plots, well logging response equations for the industrial components of coal and rock—fixed carbon content and ash content—are constructed. The specific response equations are as follows:

[0009] C oal = -0.3079 × N GR +95.746 (1)

[0010] M ois =0.2918×N GR -3.7306 (2)

[0011] In the formula: C oal M ois These are the contents of fixed carbon and ash, respectively, in %; N GR API (Advanced Phosphorus Radiation) is the natural gamma radiation of coal and rock.

[0012] Step 2: Calculate Young's modulus and Poisson's ratio based on fixed carbon and ash content.

[0013] With carbon and ash content fixed as independent variables, and based on the cross-plot approach, with Young's modulus and Poisson's ratio as dependent variables, the response equation is derived as follows:

[0014]

[0015]

[0016] E = -10.06 × ln(C) oal )+45.01 (5)

[0017] μ = -0.0215 × M ois +0.5709 (6)

[0018] Where: Δt c , Δt s These are the P-wave and S-wave transit times for coal and rock, respectively, in μs / ft; ρ b The bulk density of coal and rock is expressed in g / cm³. 3 μ is the Poisson's ratio of coal and rock, dimensionless; E is the Young's modulus of coal and rock, in GPa.

[0019] Step 3: Calculate the coal and rock brittleness index based on Young's modulus and Poisson's ratio

[0020] The units are normalized, and then the formation brittleness coefficient is calculated as half the sum of the percentages of the two parameters, as follows:

[0021]

[0022]

[0023]

[0024] In the formula: ΔE and Δμ are the normalized Young's modulus and Poisson's ratio, respectively, and are dimensionless; E max E min μ represents the maximum and minimum values ​​of Young's modulus, which are dimensionless. max μ min represents the maximum and minimum Poisson's ratio, dimensionless; BI is the formation brittleness index, %.

[0025] Step 4: Establish a comprehensive index for perforation selection in deep coalbed methane horizontal wells.

[0026] First, the brittleness index and total hydrocarbon content on the gas side were normalized. Then, based on the brittleness index, total hydrocarbon content on the gas side, and perforation section data of actual deep coalbed methane fracturing production wells, the analytic hierarchy process (AHP) was used to analyze the brittleness index, total hydrocarbon content on the gas side, and the fracturing effect of the perforation section, and assigned corresponding weights, as follows:

[0027]

[0028]

[0029] P s =0.5×(ΔBI+ΔQ)c (12)

[0030] Where: ΔBI, ΔQ c Normalized brittleness index and gas-side total hydrocarbon content, dimensionless; BI max BI min Q represents the maximum and minimum values ​​of the brittleness index, which are dimensionless; cmax Q cmin The maximum and minimum values ​​of total hydrocarbon content on the gas side are dimensionless; P s This is a dimensionless comprehensive index for perforation selection in horizontal wells of deep coalbed methane.

[0031] Step 5: Selection and Division Criteria for Perforated Sections in Deep Coalbed Methane Horizontal Wells

[0032] Based on the results of the above steps, the following table shows the optimal criteria for dividing the normalized perforation sections in deep coalbed methane horizontal wells:

[0033] Standard for Optimization and Division of Normalized Perforation Sections in Deep Coalbed Methane Horizontal Wells

[0034]

[0035] As shown in the table, the selection criteria for perforation sections in horizontal wells of deep coalbed methane can be divided into three categories: Category I indicates the best perforation section in the horizontal coal reservoir, with the best coalbed methane completion quality, reservoir quality, and compressibility; Category II indicates the medium perforation section in the horizontal coal reservoir, with good coalbed methane completion quality, reservoir quality, and average compressibility; and Category III indicates the poorest perforation section in the horizontal coal reservoir, with poor coalbed methane completion quality, reservoir quality, and worst compressibility.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] 1. The present invention provides a method for selecting the perforation section of a horizontal well in deep coalbed methane based on well logging data. This method can effectively utilize well logging data to select the perforation location of the horizontal section of a deep coalbed methane well, and organically combine two evaluation indicators: reservoir quality parameters (total hydrocarbon content on the gas side) and completion quality parameters (brittleness index).

[0038] 2. It fully considers the intrinsic relationship between the industrial components of coal and rock and the elastic parameters of the formation (Young's modulus and Poisson's ratio), and determines the brittleness index based on the elastic parameters of the formation, reflecting the idea of ​​integrated geology and engineering.

[0039] 3. This method not only improves the accuracy of perforation selection in deep coalbed methane horizontal wells, but also provides logging technology support for large-scale volumetric fracturing. It opens up a new way to select perforation sections in deep coalbed methane horizontal wells based on reservoir quality and completion quality. It is simple and practical, and has good application value. Attached Figure Description

[0040] Figure 1 This is a flowchart of the preferred method for perforated sections in horizontal wells for deep coalbed methane in this invention.

[0041] Figure 2 This is a graph showing the relationship between natural gamma radiation and fixed carbon content in coal and rock in this invention.

[0042] Figure 3 This is a graph showing the relationship between natural gamma and ash content in coal and rock in this invention.

[0043] Figure 4 This is a graph showing the relationship between the fixed carbon content of coal and rock and Young's modulus in this invention.

[0044] Figure 5 This is a graph showing the relationship between coal ash content and Poisson's ratio in this invention.

[0045] Figure 6 This is a quantitative evaluation result diagram of the preferred perforated section of a deep coalbed methane horizontal well according to the present invention. Detailed Implementation

[0046] The technical solution of the present invention will be described in detail below with reference to the embodiments.

[0047] Reference Figure 1 A method for selecting the optimal perforated section in a horizontal well of deep coalbed methane based on well logging data includes the following steps:

[0048] Step 1: Calculation of coal petrographic components using the cross-plot method

[0049] The industrial composition of coal is complex. In coal analysis and engineering practice, components with a relative volume of less than 1% are often ignored. Therefore, the industrial composition of coal can be determined to consist of three parts: fixed carbon, ash, and moisture. Since moisture in coal is not solid and its content is relatively small, and most importantly, its impact on the brittleness of the formation is extremely minor, moisture in the industrial composition of coal can be ignored or eliminated. Therefore, fixed carbon and ash have a greater impact on the brittleness of coal. Based on natural gamma logging data, and using the fixed carbon and ash content obtained from laboratory analysis, a correlation analysis was conducted between fixed carbon and ash content and logging data. It was found that natural gamma logging is most sensitive to fixed carbon and ash content. Therefore, based on the cross-plot concept, a logging response equation for the industrial composition (fixed carbon content and ash content) of coal was constructed, as follows: Figure 2 , Figure 3 As shown. The fixed carbon and ash content are determined using equations (1) and (2).

[0050] C oal = -0.3079 × N GR +95.746 (1)

[0051] Mois =0.2918×N GR -3.7306 (2)

[0052] In the formula: C oal M ois These are the contents of fixed carbon and ash, respectively, in %; N GR API is the natural gamma of coal and rock.

[0053] The fixed carbon and ash content in coal can be determined by using the industrial component calculation model established by the above two equations.

[0054] Step 2: Calculate Young's modulus and Poisson's ratio based on fixed carbon and ash content.

[0055] Based on the fixed carbon and ash content calculated in step one, and combined with the Young's modulus and Poisson's ratio calculated using well logging data (formulas (3) and (4)), the fixed carbon, ash content, Young's modulus, and Poisson's ratio of the well area to be calculated are calculated based on the conventional well logging data of the well area. First, the literature is reviewed to clarify the theoretical quantitative relationship between fixed carbon, ash content, Young's modulus, and Poisson's ratio, that is, to find out the intrinsic connection between reservoir quality and well completion quality. Then, the cross-plot idea is used to construct a planar cross-plot with fixed carbon and ash content as independent variables and Young's modulus and Poisson's ratio as dependent variables, and the response equation is obtained after correlation analysis, such as Figure 4 , Figure 5 As shown. Young's modulus and Poisson's ratio are determined using equations (5) and (6).

[0056]

[0057]

[0058] E = -10.06 × ln(C) oal )+45.01 (5)

[0059] μ = -0.0215 × M ois +0.5709 (6)

[0060] Where: Δt c , Δt s These are the P-wave and S-wave transit times for coal and rock, respectively, in μs / ft; ρ b The bulk density of coal and rock is expressed in g / cm³. 3 μ is the Poisson's ratio of coal and rock, dimensionless; E is the Young's modulus of coal and rock, in GPa.

[0061] The Young's modulus and Poisson's ratio of coal and rock can be obtained by using the calculation model of the elastic parameters of coal and rock established by the above two equations.

[0062] Step 3: Calculate the coal and rock brittleness index based on Young's modulus and Poisson's ratio

[0063] The formation brittleness index is determined based on the Young's modulus and Poisson's ratio calculated in step two. Since the units of Young's modulus and Poisson's ratio are very different, the units should be normalized in order to evaluate the influence of each parameter on rock brittleness, as shown in formulas (7) and (8). Then, the formation brittleness coefficient is obtained by taking half of the sum of the percentages of the two parameters, and the brittleness index is determined by formula (9).

[0064]

[0065]

[0066]

[0067] In the formula: ΔE and Δμ are the normalized Young's modulus and Poisson's ratio, respectively, and are dimensionless; E max E min μ represents the maximum and minimum values ​​of Young's modulus, which are dimensionless. max μ min represents the maximum and minimum Poisson's ratio, dimensionless; BI is the formation brittleness index, %.

[0068] Step 4: Establish a comprehensive index for perforation selection in deep coalbed methane horizontal wells.

[0069] According to the scheme in step three, the brittleness index, a formation completion quality parameter for deep coalbed methane horizontal wells, has been obtained. Combined with the formation and reservoir quality parameters, specifically the gas-side total hydrocarbon content (logging data), a comprehensive index model for perforation selection in deep coalbed methane horizontal wells is established based on the dual quality of completion (brittleness index) and reservoir (gas-side total hydrocarbon content). First, the brittleness index and gas-side total hydrocarbon content are normalized (see formulas (10) and (11). Then, based on the brittleness index, gas-side total hydrocarbon content, and perforation section data of actual deep coalbed methane fracturing production wells, the analytic hierarchy process (AHP) is used to analyze the brittleness index, gas-side total hydrocarbon content, and fracturing effect of the perforation section, assigning corresponding weights to determine the comprehensive index for perforation selection in deep coalbed methane horizontal wells. Formula (12) is used to determine the comprehensive index for perforation selection in deep coalbed methane horizontal wells.

[0070]

[0071]

[0072] P s =0.5×(ΔBI+ΔQ) c (12)

[0073] Where: ΔBI, ΔQ c Normalized brittleness index and gas-side total hydrocarbon content, dimensionless; BImax BI min Q represents the maximum and minimum values ​​of the brittleness index, which are dimensionless; cmax Q cmin The maximum and minimum values ​​of total hydrocarbon content on the gas side are dimensionless; P s This is a dimensionless comprehensive index for perforation selection in horizontal wells of deep coalbed methane.

[0074] Step 5: Selection and Division Criteria for Perforated Sections in Deep Coalbed Methane Horizontal Wells

[0075] Based on the results of the above steps, the following table shows the optimal criteria for dividing the normalized perforation sections in deep coalbed methane horizontal wells:

[0076] Standard for Optimization and Division of Normalized Perforation Sections in Deep Coalbed Methane Horizontal Wells

[0077]

[0078]

[0079] As shown in the table, the selection criteria for perforation sections in horizontal coalbed methane wells are divided into three categories: Category I indicates the best perforation section in the horizontal coal reservoir, with the best coalbed methane completion quality, reservoir quality, and fracturing effect; Category II indicates the medium perforation section in the horizontal coal reservoir, with good coalbed methane completion quality, reservoir quality, and average fracturing effect; and Category III indicates the poorest perforation section in the horizontal coal reservoir, with poor coalbed methane completion quality, reservoir quality, and the worst fracturing effect.

[0080] Based on the logging calculation models of various evaluation indicators in the above-mentioned criteria for the selection of perforated sections in horizontal wells of deep coalbed methane, and on the basis of writing a logging interpretation program, the main coal reservoirs of each well in the study block were subjected to fine logging processing and interpretation.

[0081] Figure 6 This is a log logging quantitative evaluation result chart regarding the optimal perforation section selection for a horizontal coalbed methane well in Well X. The main coal seam, No. 8, is located at a depth of 2400-3000m with an average thickness of 9.5m. This study categorizes the optimal perforation sections for horizontal wells into three types: Type I, Type II, and Type III. Type I perforation sections are the primary considerations for perforation locations during field fracturing, directly impacting reservoir fracturing and subsequent economic evaluation of oil production. Verifying the accuracy of this optimization result is crucial, requiring comparison between the optimized perforation sections based on logging data and the actual perforation sections constructed in the field. Only then can the accuracy of the method be determined. Well X has already undergone actual field perforation, and its actual perforation sections can be compared with the optimized Type I perforation sections for verification.

[0082] Ten Class I perforation sections were selected from the horizontal section of Well X based on a comprehensive index, ranging from 2412.5 to 2414 m (P). s(mean 0.904), 2448-2456m (P) s (mean 0.925), 2518-2520m (P) s (mean 0.914), 2556-2566m (P) s (mean 0.94), 2585-2586.8m (P) s (mean 0.91), 2638-2642m (P) s (mean 0.93), 2728-2734m (P) s (mean 0.95), 2791-2799m (P) s (mean 0.942), 2874-2878m (P) s (mean 0.96), 2924-2930m (P) s The mean value is 0.929. The actual perforation sections of this well are 2448-2456m, 2518-2522m, 2556-2564m, 2638-2643m, 2728-2734m, 2791-2798m, 2874-2878m, and 2924-2930m. Comparative analysis shows that the selected Class I perforation sections basically match the actual perforation sections in 8 instances, with 4 instances (2448-2456m, 2728-2734m, 2791-2798m, and 2874-2878m) being completely identical. The selection accuracy rate reached over 80%. This demonstrates that the method for selecting perforation sections in deep coalbed methane horizontal wells based on logging data has achieved the expected accuracy and can provide scientific logging technology support for the selection of perforation locations in horizontal sections of deep coalbed methane wells. Following fracturing of the entire No. 8 coal seam in Well X, the daily gas production reached 10,000-12,000 cubic meters. This fully demonstrates that the perforation location in the horizontal section of the deep coalbed methane well selected in this study is highly consistent with the actual fracturing monitoring and drainage results. It also further indicates that the accuracy of the perforation section results plays a crucial role in the fracturing and stimulation of deep coalbed methane. This method utilizes the information on deep coalbed methane reservoir quality and completion quality contained in well logging data. The optimized result meets the requirements for maximizing the fracturing effect in horizontal wells of deep coalbed methane, and has good prospects and value for widespread application.

[0083] Those skilled in the art should understand that, since coalbed methane logging is significantly affected by environmental factors, in order to ensure the effectiveness and feasibility of this method, it is necessary to ensure that the environmental impact correction effect of the logging data is good, and that the calculation of the four evaluation indicators, namely fixed carbon content, ash content, Young's modulus, and Poisson's ratio, is accurate. Only then can the evaluation results of the method for selecting the perforation section of deep coalbed methane horizontal wells have high accuracy.

Claims

1. A method for selecting the optimal perforation section in a deep coalbed methane horizontal well based on well logging data, characterized in that, Includes the following steps: Step 1: Calculation of coal petrographic components using the cross-plot method Based on the concept of cross plots, well logging response equations for the industrial components of coal and rock—fixed carbon content and ash content—were constructed. The specific response equations are as follows: C oal =-0.3079×N GR +95.746 (1) M ois =0.2918×N GR -3.7306 (2) In the formula: C oal M ois These are the contents of fixed carbon and ash, respectively, in %; N GR API (Advanced Phosphorus Radiation) is the natural gamma radiation of coal and rock. Step 2: Calculate Young's modulus and Poisson's ratio based on fixed carbon and ash content. With carbon and ash content as fixed independent variables, and based on the idea of ​​cross plots, with Young's modulus and Poisson's ratio as dependent variables, the response equation was derived. Step 3: Calculate the coal and rock brittleness index based on Young's modulus and Poisson's ratio The units are normalized, and then the formation brittleness coefficient is obtained by taking half the sum of the percentages of the two parameters. Step 4: Establish a comprehensive index for perforation selection in deep coalbed methane horizontal wells. First, the brittleness index and gas-side total hydrocarbon content are normalized. Then, based on the brittleness index, gas-side total hydrocarbon content, and perforation section data of actual deep coalbed methane fracturing production wells, the analytic hierarchy process (AHP) is used to analyze the brittleness index, gas-side total hydrocarbon content, and perforation section fracturing effect, and corresponding weights are assigned to determine the comprehensive index of perforation section selection for deep coalbed methane horizontal wells. Step 5: Selection and Division Criteria for Perforated Sections in Deep Coalbed Methane Horizontal Wells Based on the results of the above steps, the following table shows the optimal criteria for dividing the normalized perforation sections in deep coalbed methane horizontal wells: Standard for Optimization and Division of Normalized Perforation Sections in Deep Coalbed Methane Horizontal Wells As shown in the table, the selection criteria for perforation sections in horizontal wells of deep coalbed methane can be divided into three categories: Category I indicates the best perforation section in the horizontal coal reservoir, with the best coalbed methane completion quality, reservoir quality, and compressibility; Category II indicates the medium perforation section in the horizontal coal reservoir, with good coalbed methane completion quality, reservoir quality, and average compressibility; and Category III indicates the poorest perforation section in the horizontal coal reservoir, with poor coalbed methane completion quality, reservoir quality, and worst compressibility.

2. The method for selecting the perforated section of a deep coalbed methane horizontal well based on well logging data according to claim 1, characterized in that, The response equation for step two is as follows: E=-10.06×ln(C oal )+45.01 (5) μ=-0.0215×M ois +0.5709 (6) Where: Δt c , Δt s These are the P-wave and S-wave transit times for coal and rock, respectively, in μs / ft; ρ b The bulk density of coal and rock is expressed in g / cm³. 3 μ is the Poisson's ratio of coal and rock, dimensionless; E is the Young's modulus of coal and rock, in GPa.

3. The method for selecting the optimal perforation section of a deep coalbed methane horizontal well based on well logging data according to claim 2, characterized in that, The calculation of the coal and rock brittleness index in step three is as follows: In the formula: ΔE and Δμ are the normalized Young's modulus and Poisson's ratio, respectively, and are dimensionless; E max E min μ represents the maximum and minimum values ​​of Young's modulus, which are dimensionless. max μ min represents the maximum and minimum Poisson's ratio, dimensionless; BI is the formation brittleness index, %.

4. The method for selecting the perforated section of a deep coalbed methane horizontal well based on well logging data according to claim 3, characterized in that, The calculation of the comprehensive index in step four is as follows: P s =0.5×(ΔBI+ΔQ c ) (12) Where: ΔBI, ΔQ c Normalized brittleness index and gas-side total hydrocarbon content, dimensionless; BI max BI min Q represents the maximum and minimum values ​​of the brittleness index, which are dimensionless; cmax Q cmin The maximum and minimum values ​​of total hydrocarbon content on the gas side are dimensionless; P s This is a dimensionless comprehensive index for perforation selection in horizontal wells of deep coalbed methane.

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