Fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration

Abstract

The application discloses a kind of based on fracturing construction curve scale shale gas horizontal well logging crack prediction method, comprising the following steps: S1: according to fracturing construction curve calibration target horizontal well formation's crack section and matrix section;S2: obtain wavelet transform comprehensive coefficient WI;S3: obtain crack sensitive parameter, and determine limit standard;S4: construct judging matrix A and calculate weight vector W;S5: construct fuzzy matrix R and each parameter of the fuzzy matrix R is normalized;S6: obtain crack prediction comprehensive coefficient FI;S7: according to WI and FI, crack prediction is carried out to each section of target horizontal well formation.This application realizes the crack section in horizontal well and crack development level prediction, opens a new way for crack response characteristic and crack development level prediction method in horizontal well, has guiding role for using pre-fracturing crack prediction to optimize horizontal well fracturing construction scheme, horizontal well fracturing process wellbore stability analysis and single well productivity improvement.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, and in particular to a fracture prediction method for shale gas horizontal well logging based on fracturing operation curves. Background Technology

[0002] For tight shale gas reservoirs, fractures are not only effective storage spaces but also permeation channels that enhance the migration of natural gas from the matrix. They significantly influence the effectiveness of fracturing operations and are crucial parameters for geological and engineering evaluation. Accurate identification and evaluation of fractures are also of great value for development planning and well network deployment. Maintaining long-term stable production and improving recovery rates in shale gas reservoirs are key issues that need to be addressed, making the development of an effective method for predicting fractures in horizontal wells essential. In the development of tight oil and gas reservoirs, hydraulic fracturing is a vital engineering technique for enhancing oil and gas well production. The fracturing operation curve is a crucial reflection of the fracturing process and an important basis for predicting fracturing effects, the development of natural fractures before fracturing, and the propagation of fractures after fracturing.

[0003] Research on the classification, identification, evaluation, development characteristics, distribution prediction of favorable development intervals or zones, and their relationship with natural gas occurrence, enrichment, and production of shale fractures is of great significance to the exploration and development of shale gas. However, under the current logging technology background, horizontal well logging series have fewer methods and lower quality compared with vertical well logging, and there is a lack of new logging technology data. Moreover, electrical imaging logging, which can more accurately characterize fractures, cannot be applied in horizontal wells, making fracture logging prediction in horizontal wells more difficult. Summary of the Invention

[0004] To address the aforementioned problems, this invention aims to provide a fracture prediction method for shale gas horizontal well logging based on fracturing operation curves.

[0005] The technical solution of the present invention is as follows: A fracture prediction method for shale gas horizontal well logging based on fracturing operation curves includes the following steps: S1: Based on the characterization of the formation fracture properties before fracturing according to the horizontal well fracturing construction curve, the horizontal well logging information is calibrated to identify the fractured and matrix segments of the target horizontal well formation; S2: The P-wave time difference, S-wave time difference, and Stoneley wave time difference curves are reconstructed using wavelet transform, and the wavelet transform synthesis coefficient WI for crack prediction is obtained based on the reconstructed time difference curves. S3: Based on the sample points of the fractured section and the matrix section, select the fracture-sensitive parameters that can distinguish between the fractured section and the matrix section in the horizontal well, and determine the boundary standard between the fractured section and the matrix section corresponding to the fracture-sensitive parameters. S4: Based on the crack sensitivity parameters and the boundary criteria, construct the judgment matrix A using the analytic hierarchy process and calculate the weight vector W; S5: Construct a fuzzy matrix R according to the fuzzy mathematics method and normalize each parameter of the fuzzy matrix R; S6: Obtain the comprehensive crack prediction coefficient FI based on the weight vector W and the parameter-normalized fuzzy matrix R; S7: Based on the wavelet transform comprehensive coefficient WI and the fracture prediction comprehensive coefficient FI, fracture prediction is performed on each segment of the formation in the target horizontal well.

[0006] Preferably, in step S1, when calibrating the fractured and matrix segments of the target horizontal well formation: If the horizontal well fracturing operation curve of the target section is descending or descending steadily, then the target section is a fractured section. If the horizontal well fracturing operation curve of the target section is stable or rising, then the target section is a matrix section.

[0007] Preferably, in step S2, the wavelet transform synthesis coefficient WI is calculated using the following formula: WI=a REDTC+b REDTST+c REDTS (1) In the formula: a, b, and c are curve reconstruction coefficients; REDTC, REDTST, and REDTS are the longitudinal wave time difference, transverse wave time difference, and Stoneley wave time difference curves reconstructed by wavelet transform, respectively.

[0008] Preferably, in step S4, the weight vector W is calculated using the following formula: (2) In the formula: λ max It is the largest eigenvalue.

[0009] Preferably, in step S6, when obtaining the crack prediction comprehensive coefficient FI, it is calculated based on the product of the weight vector W and the parameter-normalized fuzzy matrix R.

[0010] Preferably, in step S7, when predicting fractures in each segment of the formation of the target horizontal well: If WI ≥ 0.18 and FI ≥ 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FA. If WI ≥ 0.18 and 0.39 ≤ FI < 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FB level. If WI ≥ 0.18 and 0.35 ≤ FI < 0.39, then the target layer is located in a fractured layer, and the fractures are generally well-developed, and the level is defined as FC. If WI≤0.18 and 0.34≤FI<0.35, then the target segment is located in the matrix segment and the fracture sub-segment is not developed, and the level is defined as MD level; If WI ≤ 0.18 and FI < 0.34, then the target segment is located in the matrix segment and has the least developed fractures, and the level is defined as ME level.

[0011] Preferably, in step S7, when predicting fractures in each segment of the formation of the target horizontal well: When WI≥0.18 and FI≥0.43, the horizontal well fracturing operation curve of the target section shows a downward trend; When WI≥0.18 and 0.39≤FI<0.43, the horizontal well fracturing operation curve of the target section includes both descending type and descending stable type; When WI ≥ 0.18 and 0.35 ≤ FI < 0.39, the horizontal well fracturing operation curve of the target section shows a downward stable type. When WI≤0.18 and 0.34≤FI<0.35, the horizontal well fracturing operation curve of the target section is stable. When WI≤0.18 and FI<0.34, the horizontal well fracturing operation curve of the target section is upward.

[0012] The beneficial effects of this invention are: This invention can accurately predict fractures in horizontal well formations using fracturing operation curves and horizontal well logging information, opening up new avenues for predicting fracture response characteristics and fracture development levels in horizontal wells. It also provides guidance for optimizing horizontal well fracturing operation schemes, analyzing wellbore stability and fracturing processes, and improving single-well productivity using pre-fracturing fracture prediction. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic flowchart of the fracture prediction method for shale gas horizontal well logging based on fracturing operation curves, as described in this invention. Figures 2-5 This is a schematic diagram of the fracturing operation curve for a shale gas horizontal well with sand-carrying fluid stage, as shown in a specific embodiment. Figures 6-8 This is a schematic diagram illustrating the calibration results of different formation segments in a horizontal well based on the morphological characteristics of the fracturing operation curve, as a specific embodiment. Figures 9-11 A schematic diagram of the reconstructed curve and fracture prediction results of a shale gas horizontal well, as shown in a specific embodiment; Figures 12-19 This is a schematic diagram of cross-plotting of fracture prediction parameters in a horizontal well, as shown in a specific embodiment. Figures 20-22 This is a schematic diagram showing the intersection of well logging information for different fracturing operation curve shapes in a specific embodiment. Figures 23-26 This is a verification diagram of the fracturing operation curve for predicting fractures in a shale gas horizontal well, based on a specific embodiment. Figures 27-28 This is a verification diagram for fracture prediction in a shale gas horizontal well, based on a specific embodiment. Detailed Implementation

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and technical features described in this application can be combined with each other. It should also be pointed out that, unless otherwise indicated, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terms "comprising" or "including" and similar words used in this invention refer to elements or objects preceding the word that encompass the elements or objects listed following the word and their equivalents, without excluding other elements or objects.

[0016] like Figure 1 As shown, this invention provides a fracture prediction method for shale gas horizontal well logging based on fracturing operation curves, comprising the following steps: S1: Based on the characterization of the formation fracture properties before fracturing according to the horizontal well fracturing construction curve, the horizontal well logging information is calibrated to identify the fractured and matrix segments of the target horizontal well formation.

[0017] The physical meanings of different types of fracturing operation curves in the sand-carrying fluid stage of shale gas horizontal wells vary considerably. Based on these curves, characteristics such as the expansion and extension of natural and artificial fractures in the formation can be determined, thereby enabling the calibration of different segments of the formation in the horizontal well. During calibration: if the horizontal well fracturing operation curve of the target segment is of the descending type (Ⅰ) or descending stable type (Ⅱ), then the target segment is a fracture segment; if the horizontal well fracturing operation curve of the target segment is of the stable type (Ⅲ) or ascending type (Ⅳ), then the target segment is a matrix segment.

[0018] S2: The P-wave time difference, S-wave time difference, and Stoneley wave time difference curves are reconstructed using wavelet transform, and the wavelet transform synthesis coefficient WI for crack prediction is obtained based on the reconstructed time difference curves.

[0019] Wavelet transform can more clearly characterize the high-frequency wavelet properties of cracks. This wavelet transform method is an existing technology, and its specific steps will not be detailed here. The envelope of the sensitivity curve processed by wavelet transform is reconstructed, and parameters are adjusted multiple times to construct the wavelet transform synthesis coefficients WI for predicting cracks. WI=a REDTC+b REDTST+c REDTS (1) In the formula: a, b, and c are curve reconstruction coefficients; REDTC, REDTST, and REDTS are the longitudinal wave time difference, transverse wave time difference, and Stoneley wave time difference curves reconstructed by wavelet transform, respectively.

[0020] S3: Based on the sample points of the fractured segment and the matrix segment, select the fracture-sensitive parameters that can distinguish between the fractured segment and the matrix segment in the horizontal well, and determine the boundary standard between the fractured segment and the matrix segment corresponding to the fracture-sensitive parameters.

[0021] In one specific embodiment, sample points of fracture segments and matrix segments calibrated by fracturing construction curves are selected for intersection. Based on the intersection diagram, the most sensitive parameter variables that can distinguish between fracture segments and matrix segments in horizontal wells can be selected, and the boundary criteria between fracture segments and matrix segments can be determined.

[0022] S4: Based on the crack sensitivity parameters and the boundary criteria, construct the judgment matrix A using the analytic hierarchy process and calculate the weight vector W.

[0023] In one specific embodiment, the weight vector W is calculated using the following formula: (2) In the formula: λ max It is the largest eigenvalue.

[0024] S5: Construct a fuzzy matrix R according to fuzzy mathematics and normalize each parameter of the fuzzy matrix R.

[0025] S6: Obtain the crack prediction comprehensive coefficient FI based on the weight vector W and the parameter-normalized fuzzy matrix R.

[0026] In one specific embodiment, the crack prediction comprehensive coefficient FI is obtained by multiplying the weight vector W and the parameter-normalized fuzzy matrix R.

[0027] S7: Based on the wavelet transform comprehensive coefficient WI and the fracture prediction comprehensive coefficient FI, fracture prediction is performed on each segment of the formation in the target horizontal well.

[0028] In a specific embodiment, when predicting fractures in each segment of the formation of a target horizontal well: If WI ≥ 0.18 and FI ≥ 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FA. If WI ≥ 0.18 and 0.39 ≤ FI < 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FB level. If WI ≥ 0.18 and 0.35 ≤ FI < 0.39, then the target layer is located in a fractured layer, and the fractures are generally well-developed, and the level is defined as FC. If WI≤0.18 and 0.34≤FI<0.35, then the target segment is located in the matrix segment and the fracture sub-segment is not developed, and the level is defined as MD level; If WI ≤ 0.18 and FI < 0.34, then the target segment is located in the matrix segment and has the least developed fractures, and the level is defined as ME level.

[0029] In a specific embodiment, when predicting fractures in each segment of the formation of a target horizontal well: When WI≥0.18 and FI≥0.43, the horizontal well fracturing operation curve of the target section shows a downward trend; When WI≥0.18 and 0.39≤FI<0.43, the horizontal well fracturing operation curve of the target section includes both descending type and descending stable type; When WI ≥ 0.18 and 0.35 ≤ FI < 0.39, the horizontal well fracturing operation curve of the target section shows a downward stable type. When WI≤0.18 and 0.34≤FI<0.35, the horizontal well fracturing operation curve of the target section is stable. When WI≤0.18 and FI<0.34, the horizontal well fracturing operation curve of the target section is upward.

[0030] In a specific embodiment, taking a horizontal well as an example, the fracture prediction method for shale gas horizontal well logging based on the fracturing construction curve described in this invention is used to predict fractures, specifically including the following steps: (1) Based on the characterization of pre-fracturing formation fracture properties using the horizontal well fracturing construction curve, the horizontal well logging information is calibrated to identify the fractured and matrix segments of the target horizontal well formation; in this embodiment, the horizontal well fracturing construction curve is as follows: Figures 2-5 As shown, the calibration results are as follows: Figures 6-8 As shown.

[0031] (2) The longitudinal wave time difference, transverse wave time difference and Stoneley wave time difference curves are reconstructed using wavelet transform, and the wavelet transform comprehensive coefficient WI for crack prediction is obtained based on the reconstructed time difference curves.

[0032] In this embodiment, orthogonal wavelets with tight support, symmetry, and smoothness, the dbN (N=1-10) series, are selected. A Mallat tower structure with 5 decomposition layers is used to perform wavelet transform analysis on DTC (P-wave transit time), DTS (Shingle-wave transit time), and DTST (Stoneley wave transit time) in conventional well logging information. The sensitive curves processed by the wavelet transform method are reconstructed by taking the envelope and undergoing multiple parameter adjustments to form the wavelet transform comprehensive coefficients for fracture prediction. WI=0.6376REDTC+0.2578REDTST+0.0165REDTS (3) The reconstructed P-wave time difference, S-wave time difference, and Stoneley wave time difference curves in this embodiment are as follows: Figures 9-11 As shown.

[0033] (3) Based on the sample points of the fractured section and the matrix section, select the fracture sensitive parameters that can distinguish the fractured section and the matrix section of the horizontal well, and determine the boundary standard of the fracture sensitive parameters corresponding to the fractured section and the matrix section.

[0034] In this embodiment, the intersection diagram of sample points of the fracture segment and matrix segment after calibration by the fracturing construction curve is shown below. Figures 12-22 As shown. From Figures 12-22 The fracture sensitivity parameters of the fracture segment and matrix segment can be obtained, and the boundary criteria of each parameter corresponding to the fracture segment and matrix segment can be determined. The results are shown in Table 1. Table 1. Boundary criteria between fractured and matrix segments

[0035] As can be seen from Table 1, the crack-sensitive parameters in this embodiment are six types: natural gamma, density, compensated neutron, crack coefficient, lateral ratio, and Young's modulus. The limit standards corresponding to these six parameters are the limit standards required in this step.

[0036] (4) Based on the crack sensitivity parameters and the boundary criteria, construct the judgment matrix A using the analytic hierarchy process and calculate the weight vector W. The weight vector W is calculated using equation (2). The result of this embodiment is weight vector W = [0.4206, 0.2694, 0.1424, 0.0858, 0.0509, 0.0310].

[0037] (5) Construct a fuzzy matrix R according to the fuzzy mathematics method and normalize each parameter of the fuzzy matrix R.

[0038] (6) Obtain the crack prediction comprehensive coefficient FI based on the weight vector W and the parameter-normalized fuzzy matrix R: FI=RW= (4) (7) Based on the wavelet transform comprehensive coefficient WI and the fracture prediction comprehensive coefficient FI, fracture prediction is performed on each segment of the formation in the target horizontal well, and the results are as follows: Figures 9-11 As shown.

[0039] from Figure 9-11 It can be seen that the logging response characteristics of the fractured section in horizontal wells are significantly different from those of the matrix section. The fractured section is characterized by a high natural gamma anomaly, significantly increased compensated neutron and density curves, increased sonic transit time with a "sawtooth" cycle jump phenomenon, a "positive difference" in deep lateral resistivity compared to shallow lateral resistivity with a "peak-like" curve shape, and a high energy amplitude value in the P-wave transit time wavelet transform curve resembling a "mountain peak". The matrix section is characterized by decreased compensated neutron and density curve values, "negative difference" or near-overlapping bilateral lateral curves with relatively flat curve shapes and no significant differences, no significant fluctuations in the natural gamma curve, and a small energy amplitude in the P-wave transit time wavelet transform curve.

[0040] In this embodiment, the fracture development results predicted by combining the fracturing operation curve and well logging information are divided into the following five levels: well-developed fracture (FA level, located in the fractured layer), relatively well-developed fracture (FB level, located in the fractured layer), moderately well-developed fracture (FC level, located in the fractured layer), less well-developed fracture (MD level, located in the matrix layer), and least well-developed fracture (ME level, located in the matrix layer). The curve of FA level fractures during fracturing operation is downward (Ⅰ), the curve of FB level fractures during fracturing operation is both downward (Ⅰ) and downward stable (Ⅱ), the curve of FC level fractures during fracturing operation is downward stable (Ⅱ), the curve of MD level fractures during fracturing operation is stable (Ⅲ), and the curve of ME level fractures during fracturing operation is upward (Ⅳ).

[0041] The crack prediction results (crack development level and predicted fracturing operation curve type) of this embodiment are compared with the actual working conditions, and the results are as follows: Figures 23-28 As shown in the figure. The comparison results show that the fracture development level and the predicted fracturing construction curve type predicted by this invention are consistent with the actual situation. This invention can accurately predict fractures in shale gas horizontal wells.

[0042] In summary, this invention can characterize the features of different fracture and matrix segments in horizontal wells based on the geological and engineering information revealed by various fracturing operation curves during the sand-carrying fluid stage. Furthermore, by calibrating and combining horizontal well logging information, it utilizes wavelet transform, cross-plotting, and mathematical modeling methods to predict formation fractures in horizontal wells. The fracture development levels and predicted fracturing operation curve types obtained by this invention are consistent with actual conditions, demonstrating that using logging information combined with fracturing operation curves to predict fractures is an effective method in horizontal wells. This invention utilizes the reflection of pre-fracturing formation fracture properties by the fracturing operation curves during the sand-carrying fluid stage of horizontal wells to calibrate logging information, opening up new avenues for predicting fracture response characteristics and fracture development levels in horizontal wells. It provides guidance for optimizing horizontal well fracturing operation schemes, analyzing wellbore stability and fracturing processes, and improving single-well productivity using pre-fracturing fracture prediction. Compared with existing technologies, this invention represents a significant advancement.

[0043] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A fracture prediction method for shale gas horizontal well logging based on fracturing operation curves, characterized in that, Includes the following steps: S1: Based on the characterization of the formation fracture properties before fracturing according to the horizontal well fracturing construction curve, the horizontal well logging information is calibrated to identify the fractured and matrix segments of the target horizontal well formation; S2: The P-wave time difference, S-wave time difference, and Stoneley wave time difference curves are reconstructed using wavelet transform, and the wavelet transform synthesis coefficient WI for crack prediction is obtained based on the reconstructed time difference curves. S3: Based on the sample points of the fractured section and the matrix section, determine the fracture-sensitive parameters that can distinguish between the fractured section and the matrix section in the horizontal well, and determine the boundary standard between the fractured section and the matrix section corresponding to the fracture-sensitive parameters. S4: Based on the crack sensitivity parameters and the boundary criteria, construct the judgment matrix A using the analytic hierarchy process and calculate the weight vector W; S5: Construct a fuzzy matrix R according to the fuzzy mathematics method and normalize each parameter of the fuzzy matrix R; S6: Obtain the comprehensive crack prediction coefficient FI based on the weight vector W and the parameter-normalized fuzzy matrix R; S7: Based on the wavelet transform comprehensive coefficient WI and the fracture prediction comprehensive coefficient FI, perform fracture prediction for each segment of the formation in the target horizontal well; When predicting fractures in each formation segment of the target horizontal well: If WI ≥ 0.18 and FI ≥ 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FA. If WI ≥ 0.18 and 0.39 ≤ FI < 0.43, then the target layer is located in a fractured layer with well-developed fractures, and the level is defined as FB level. If WI ≥ 0.18 and 0.35 ≤ FI < 0.39, then the target layer is located in a fractured layer, and the fractures are generally well-developed, and the level is defined as FC. If WI≤0.18 and 0.34≤FI<0.35, then the target segment is located in the matrix segment and the fracture sub-segment is not developed, and the level is defined as MD level; If WI ≤ 0.18 and FI < 0.34, then the target segment is located in the matrix segment and has the least developed fractures, and the level is defined as ME level.

2. The fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration according to claim 1, characterized in that, In step S1, when calibrating the fractured and matrix sections of the target horizontal well formation: If the horizontal well fracturing operation curve of the target section is descending or descending steadily, then the target section is a fractured section. If the horizontal well fracturing operation curve of the target section is stable or rising, then the target section is a matrix section.

3. The fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration according to claim 1, characterized in that, In step S2, the wavelet transform synthesis coefficient WI is calculated using the following formula: WI=a REDTC+b REDTST+c REDTS (1) In the formula: a, b, and c are curve reconstruction coefficients; REDTC, REDTST, and REDTS are the longitudinal wave time difference, transverse wave time difference, and Stoneley wave time difference curves reconstructed by wavelet transform, respectively.

4. The fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration according to claim 1, characterized in that, In step S4, the weight vector W is calculated using the following formula: （2） In the formula: λ max It is the largest eigenvalue.

5. The fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration according to claim 1, characterized in that, In step S6, when obtaining the crack prediction comprehensive coefficient FI, it is calculated based on the product of the weight vector W and the parameter-normalized fuzzy matrix R.

6. The fracture prediction method for shale gas horizontal well logging based on fracturing operation curve calibration according to claim 1, characterized in that, In step S7, when predicting fractures in each layer of the formation of the target horizontal well: When WI≥0.18 and FI≥0.43, the horizontal well fracturing operation curve of the target section shows a downward trend; When WI≥0.18 and 0.39≤FI<0.43, the horizontal well fracturing operation curve of the target section includes both descending type and descending stable type; When WI ≥ 0.18 and 0.35 ≤ FI < 0.39, the horizontal well fracturing operation curve of the target section shows a downward stable type. When WI≤0.18 and 0.34≤FI<0.35, the horizontal well fracturing operation curve of the target section is stable. When WI≤0.18 and FI<0.34, the horizontal well fracturing operation curve of the target section is upward.

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