Fracturing risk assessment method based on three-dimensional distribution of double sweet spots of reservoir fracturability

Abstract

The present invention relates to a fracturing risk assessment method based on the three-dimensional distribution of double sweet spots of reservoir fracturability, including: obtaining a geological sweet spot data body through normalization based on single well logging geological data to establish a three-dimensional geological model of block fracturability; calculating a three-dimensional fracturability data body based on single well stratification data; gridding the three-dimensional geological model of block fracturability, and interpolating the three-dimensional fracturability data body in the grid; and cross-cutting the interpolated three-dimensional geological model of the block fracturability to obtain the plane distribution of fracturing risks of each reservoir at different depths. This method can accurately divide the risks of faults and water layers in the fracturing layer section, and effectively guide the fracturing design to avoid risks.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum development, and in particular to a method and a device for evaluating fracturing risk based on three-dimensional distribution of double sweet spots of reservoir fracturability. Background Art

[0002] In the exploration and development of unconventional oil and gas, the recoverable reserves of oil and gas in tight lithology are huge, but at the same time they are accompanied by the characteristics of "three lows", complex lithology, some strata contain peat interlayers, strong reservoir heterogeneity, and large regional differences. In order to achieve better fracturing effect, it is necessary to simultaneously optimize the geological sweet spots and engineering sweet spots (double sweet spots) of the reservoir in three-dimensional space. Among them, the engineering sweet spot (fracturability) is a key indicator for evaluating the formation of complex fractures in such reservoirs after fracturing. The three-dimensional spatial distribution law of fracturability is of great significance for the subsequent fracturing field construction and design. After the model is established, it helps to guide the field construction, but the geological factors in the reservoir, that is, the macroscopic geological structural parameters (such as faults), are often ignored. During construction, if the fault is blocked during the extension of the fracture, it will limit the extension of the fracture, the formation suction volume will reach saturation, the pressure will rise, and normal construction will be impossible, or the leakage of fracturing fluid and well leakage will occur in the leakage fault, causing underground accidents such as serious environmental pollution. Secondly, if a high-water-containing layer is compressed and leaked, waterlogging of the gas reservoir or the oil layer will occur. The incompatibility of formation water and oil layer liquid will block the pore throats and greatly reduce the production after compression.

[0003] Sweet spots in unconventional reservoirs are the characteristics of such reservoirs that can be fractured. The three-dimensional spatial distribution law of the fracturing properties of geological sweet spots is of great significance to the subsequent fracturing site construction and design. Accurately finding the sweet spot layer is conducive to reducing the cost of exploration and development and improving the overall production capacity of the block.

[0004] Among the many fracturability models available today, the conventional method is to obtain important material basis parameters that affect the productivity of the fracturing well section through logging data, such as total hydrocarbon content, water saturation, porosity and permeability, etc., which are also the main dependent variables for evaluating geological sweet spots. However, during fracturing construction, it is very easy to leak macroscopic faults or aquifers around the target layer. This results in the inability to accurately reflect the actual small layer conditions in the existing three-dimensional fracturability model analysis. Summary of the invention

[0005] The purpose of the present invention is to provide a fracturing risk assessment method based on the three-dimensional distribution of double sweet spots of the reservoir fracturing in order to solve the safety risk problem caused by fault breakthrough after fracturing in the prior art.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A fracturing risk assessment method based on three-dimensional distribution of double sweet spots of reservoir fracturing, comprising:

[0008] Based on the logging geological data of each single well in the block, the geological sweet spot data volume is obtained through normalization to establish a three-dimensional geological model of the block's fracturability;

[0009] According to the stratified data of each well in the block, the three-dimensional data volume of fracturability is calculated;

[0010] The three-dimensional geological model of the block's fracturability is divided into grids, and the three-dimensional data volume of fracturability is interpolated in the grids;

[0011] The three-dimensional geological model of the block's fracturability is interpolated along the horizontal section to obtain the planar distribution of fracturing risks of each reservoir at different depths.

[0012] The fracturing risk assessment method based on the three-dimensional distribution of the double sweet spots of the reservoir fracturing also includes: determining the fracturing risk level according to the horizontal and vertical distances of the fault, the vertical distance between the reservoir and the high aquifer, and the water saturation of the reservoir, and conducting fracturing risk assessment on the strata and well locations in the block.

[0013] The single well stratification data includes at least one of the following groups: longitudinal and transverse acoustic wave time difference, neutron density, natural gamma, resistivity, porosity, and permeability.

[0014] The three-dimensional geological model of the block's fracturability is gridded, including dividing it into three-dimensional geological grids with each layer of 1-3m.

[0015] The calculation of the three-dimensional fracturability data body includes: fitting and correcting the mechanical parameters of the whole well, establishing a single well mechanical parameter profile, calculating the fracturability profiles of multiple single wells according to the fracturability calculation method, and interpolating the fracturability profiles of multiple single wells into the three-dimensional fracturability data body through an interpolation algorithm.

[0016] After interpolating the three-dimensional data volume of fracturability in the grid, the grid is coarsened, and the three-dimensional geological model of fracturability of the block after the coarsening is cut horizontally to obtain the risk plane distribution of each reservoir layer at different depths.

[0017] The mesh coarsening includes: determining the fracture height of the fault risk through the median, average and maximum values ​​of the fracture heights detected by on-site fracturing logging, and coarsening the mesh in the small layer of the block's three-dimensional geological model of fracturability according to the obtained fracture height.

[0018] The median, mean, and maximum values ​​of each cluster of fracture heights in the first segment detected by on-site fracturing logging are used to select the logarithmic interpolation of fracture heights to determine the fault risk.

[0019] After the block's three-dimensional geological model of fracturability is interpolated along the transverse section, it is expanded along the designed wellbore trajectory to obtain a risk longitudinal profile along the wellbore.

[0020] A fracturing risk assessment device based on three-dimensional distribution of double sweet spots of reservoir fracturing, comprising:

[0021] The three-dimensional geological module is suitable for obtaining the geological sweet spot data volume through normalization based on the well logging geological data of each single well in the block, so as to establish a three-dimensional geological model of the block's fracturability;

[0022] The three-dimensional data volume module is suitable for calculating the three-dimensional data volume of fracturability based on the layered data of each single well in the block;

[0023] An interpolation module, suitable for meshing the three-dimensional geological model of the block's fracturability and interpolating the three-dimensional data volume of the fracturability within the grid;

[0024] The evaluation module is suitable for obtaining the planar distribution of fracturing risks of each reservoir at different depths along the three-dimensional geological model of the block after transverse section interpolation, so as to evaluate the fracturing risks of the layers and wells in the block.

[0025] The present invention adopts the above technical solution, which has the following advantages:

[0026] According to the logging data of each single well in the block, the present invention uses the grey correlation method to normalize each parameter to obtain the geological sweet spot data body, and uses professional geological modeling software to establish a three-dimensional geological model of the block's fracturability. Starting from the evaluation of the potential for efficient transformation of unconventional reservoirs, the problem of safety risks caused by faults after fracturing is considered, and a fault assessment method is added to establish a three-dimensional fracturable reservoir evaluation model. Only the transverse acoustic wave time difference, neutron density, GR, resistance, and calculated porosity, permeability and other data are needed to calculate the fault risk level, and achieve a more comprehensive and safe fracturability evaluation. The proposed method can more accurately divide the risks of faults and water layers in the fracturing layer section, and effectively guide the fracturing design to avoid risks.

[0027] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] By reading the detailed description of the preferred embodiment below, various other advantages and benefits will become clear to those of ordinary skill in the art. The accompanying drawings are only used to illustrate the purpose of the preferred embodiment and are not considered to be limitations of the present invention. In the entire drawings, the same reference numerals are used to represent the same components.

[0029] In the attached picture:

[0030] Figure 1 It is a process flow chart of a fracturing risk assessment method based on three-dimensional distribution of double sweet spots of reservoir fracturability according to an embodiment of the present invention.

[0031] Figure 2 is a schematic diagram of a geological modeling layer model according to an embodiment of the present invention.

[0032] Figure 3 It is a schematic diagram of a comprehensive fracturability profile and an oil, gas and water profile of a well according to an embodiment of the present invention.

[0033] Figure 4 Schematic diagram of a three-dimensional geological fracturability data volume according to an embodiment of the present invention.

[0034] Figure 5 4 is a schematic diagram of a risk profile of the distance between a well model and a fault according to an embodiment of the present invention.

[0035] Figure 6 It is a schematic diagram of the upper layer water saturation risk profile of Well A after detailed risk assessment according to an embodiment of the present invention.

[0036] Figure 7 It is a schematic diagram of the risk profile along the trajectory of well A according to an embodiment of the present invention.

[0037] Figure 8 It is a schematic diagram of the longitudinal reverse risk profile along the trajectory of well A according to an embodiment of the present invention.

[0038] Meaning of the accompanying text:

[0039] Figure 4 and Figure 8 The general term in the color bar color template selection type does not affect the specific data;

[0040] Figure 5 The distance of the well model from the fault risk is the name of the variable in the modeling process. Users can name it according to their own habits. There is no unified standard.

[0041] Figure 6 The water saturation risk of the middle and upper layers is the name of the variable in the modeling process. Users can name it according to their own habits, and there is no unified standard;

[0042] Figure 7 Medium water saturation is the unified expression of oil fields, and the color template selection is universal. DETAILED DESCRIPTION

[0043] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0044] The word "sweetheart" is translated from "Sweet heart" in the foreign oil and gas exploration and development industry. In the process of oil and gas exploration and development, large areas of oil and gas-bearing areas and large sections of oil and gas-bearing layers will be revealed, but often a part of them has good development benefits under the current economic and technical conditions. Its distribution may not be in a piece in the vertical and horizontal directions, so it is called a sweetheart. The geological sweetheart focuses on the comprehensive evaluation of source rocks, reservoirs, overpressure and fractures, and the engineering sweetheart focuses on the comprehensive evaluation of burial depth, rock fracturing, stress anisotropy, etc. For example, the current evaluation of the "sweetheart area" of unconventional tight oil, tight gas, shale oil and shale gas mainly focuses on the evaluation of geological sweetheart elements such as favorable source layers, reservoirs, overpressure, fractures, local structures, and engineering sweetheart elements such as pressure coefficient, brittleness, and stress anisotropy. Fracturing is the abbreviation of fracturing in this book.

[0045] In one embodiment of the present invention, a three-dimensional geological model of block fracturability is first established; a mechanical parameter profile of each well is established, and a single well fracturability profile is established according to a fracturability calculation method; the three-dimensional geological model is gridded, and a three-dimensional data body of single well geological fracturability is interpolated in the grid; then, the grids in the small layers of the three-dimensional geological model are coarsened; after the grid is coarsened, the three-dimensional model is cut horizontally to obtain the risk plane distribution of each reservoir small layer at different depths; the risk level is determined according to the three risk parameters of the horizontal and vertical distances of the fault, the vertical distance between the reservoir and the high aquifer, and the water saturation of the reservoir, and the fracturing risk assessment is performed on the layer and well location of the target block.

[0046] In one embodiment of the present invention, taking a certain well (well A for short) as an example, the present invention provides a fracturing risk assessment method based on the three-dimensional distribution of double sweet spots of the reservoir.

[0047] like Figure 1 As shown, the specific steps are as follows:

[0048] S1. According to the logging data of each single well in the block, four basic parameters such as total hydrocarbon content, water saturation, porosity and permeability are selected, and the basic parameters are normalized by the grey correlation method to obtain the geological sweet spot data body, and a three-dimensional geological model of the block's fracturability is established.

[0049] Among them, the normalization processing method formula is as follows:

[0050]

[0051] In the formula, G n represents the normalized calculation result, G represents the parameter value of the bathymetric evaluation point, G min Indicates the minimum value of the parameter, G maxIndicates the maximum value of the parameter. The denominator is the maximum value minus the minimum value of a parameter in the logging data of the area, and the numerator is the parameter value minus the minimum value of the depth evaluation point. The higher the normalized calculation result data, the higher the predicted production after fracturing, which is in direct proportion.

[0052] After obtaining the data body through the above method, according to the layered data of the single well, professional geological modeling software, such as Petrel modeling software, is used to first establish the basic model of the block geological layer, and according to the network density requirements of different block models, the model is adjusted to perfect convergence, such as Figure 2 shown.

[0053] S2. According to the stratified data of each well in the block, a three-dimensional data volume of fracturability is calculated: the mechanical parameters of the whole well are fitted and corrected (for example, distorted parameters and abnormal parameters that do not conform to the field construction rules are deleted), and the mechanical parameter profiles of each well are established. According to the fracturability calculation method, the fracturability profile of a single well is established, such as Figure 3 Among them, the single well stratification data include longitudinal and transverse acoustic wave time difference, neutron density, GR, resistivity, porosity, permeability, etc. GR is the abbreviation of Gamma Ray, which stands for natural gamma.

[0054] S3, divide the 3D geological model into 3D geological grids according to 1-3m layers, and insert the single well geological fracturability 3D data volume into the grids through algorithms, such as Figure 4 shown.

[0055] S4. The fracture height for identifying fault risks is determined by the median, average, and maximum values ​​of the fracture heights detected by the on-site fracturing logging department.

[0056] The statistics of cluster fracture height of Well A are shown in Table 1.

[0057] Table 1. Statistics of cluster fracture height of Well A

[0058] Serial number median Average Maximum Paragraph 0 64.5 55.4 71.5 Paragraph 1 36.4 33.2 39.6 Paragraph 2 54.2 55.2 67.5 Paragraph 3 61.5 66.7 70.8 Paragraph 4 56.2 53.2 60.1

[0059] S5, according to the fracture height value obtained in step S4, the grid in the small layer of the three-dimensional geological model is coarsened, and the result is drawn as shown in FIG. Figure 5 The distribution of predicted attribute parameters can be predicted by using interpolation or random simulation methods to reflect the characteristics of underground reservoirs and the distribution characteristics of heterogeneous bodies in three-dimensional space. The values ​​of each small grid are extracted, weighted averaged and assigned to each large grid. The results are as follows: Figure 6 shown.

[0060] The input data must conform to the form of normal distribution, but the attribute parameters after discretization do not meet the distribution requirements, so the attribute parameters in the three-dimensional grid are processed. When performing variogram analysis on the attribute parameters, it is carried out layer by layer and phase by phase to obtain the vertical range.

[0061] Conduct risk assessment of the safe area (safe fracturing range for engineering construction) to prevent leakage from the macro faults and aquifers during fracturing construction of a well. Plane grid coarsening should reduce the vertical and horizontal segment step lengths as much as possible while reducing the number of grids and retaining attribute characteristics, and the grid ratio should be kept within a reasonable range.

[0062] S6. Cut the three-dimensional model horizontally to obtain the risk plane distribution of each reservoir layer at different depths; expand it along the designed wellbore trajectory to obtain the risk longitudinal profile along the wellbore. Figure 7 It is the risk profile along the trajectory of well A. Figure 8 It is the longitudinal reverse risk profile along the trajectory of well A.

[0063] S7. Determine the risk level based on the three risk parameters: horizontal and vertical distance of the fault, vertical distance between the reservoir and the high aquifer, and water saturation of the reservoir, and conduct a fracturing risk assessment on the strata and well locations of the target block. The risk level is divided into three levels: high risk, medium risk, and low risk. The specific classification standards are shown in Table 2:

[0064] Table 2. Risk level classification standards

[0065]

[0066] According to the above method, the faults in the model block of the example well A are divided into high-risk layers within 300m horizontally and vertically from the faults, medium-risk layers between 300-500m, and low-risk layers above 500m; the vertical distance between the reservoir and the high aquifer (water saturation>60%) is within 50m as a high-risk layer, medium-risk layers between 50-70m, and low-risk layers above 70m; the reservoir water saturation is 80% as a high-risk layer, 30%-80% as a medium-risk layer, and below 30% as a low-risk layer. According to the data body, the fault risk fracture height is calculated to be about 50m.

[0067] By matching the classification standards to actual wells, it can be seen from the longitudinal and lateral expansion distribution profiles of the regional risk assessment model that Well A is located in the high- and medium-risk areas, and the 16th sublayer of Well A is in the low-risk layer.

[0068] In summary, the fracturing risk assessment method based on the three-dimensional distribution of double sweet spots of the reservoir fracturability provided by the present invention and the model of the three-dimensional fracturable reservoir based on the macroscopic geological structure can effectively determine the risk level of related layers and well locations, thereby assisting in development decision-making and greatly reducing the development cost of oil and gas.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fracturing risk assessment method based on three-dimensional distribution of double sweet spots of reservoir fracturing, characterized in that: include: Based on the logging geological data of each single well in the block, the geological sweet spot data volume is obtained through normalization to establish a three-dimensional geological model of the block's fracturability; According to the stratified data of each single well in the block, a three-dimensional data body of fracturability is calculated, and the calculation of the three-dimensional data body of fracturability includes: fitting and correcting the mechanical parameters of the whole well, establishing a single well mechanical parameter profile, calculating the fracturability profiles of multiple single wells according to the fracturability calculation method, interpolating the fracturability profiles of multiple single wells into the three-dimensional data body of fracturability through an interpolation algorithm, and after interpolating the three-dimensional data body of fracturability in a grid, coarsening the grid, and cutting the three-dimensional geological model of the block after the coarsening of the grid along the horizontal direction to obtain the risk plane distribution of each reservoir layer at different depths; Dividing the three-dimensional geological model of the block into grids, and interpolating the three-dimensional data volume of the fracturability in the grids; A three-dimensional geological model of the fracturability of the block after lateral sectioning and interpolation to obtain a planar distribution of fracturing risks of each reservoir at different depths; It also includes: determining the fracturing risk level based on the horizontal and vertical distances of the fault, the vertical distance between the reservoir and the high aquifer, and the water saturation of the reservoir, and conducting a fracturing risk assessment on the strata and well locations in the block.

2. The fracturing risk assessment method based on three-dimensional distribution of reservoir double sweet spots according to claim 1 is characterized in that: The single well stratification data includes at least one of the following groups: longitudinal and transverse acoustic wave time difference, neutron density, natural gamma, resistivity, porosity, and permeability.

3. The method for fracturing risk assessment based on three-dimensional distribution of reservoir double sweet spots fracturability according to claim 1, characterized in that: The three-dimensional geological model of the fracturability of the block is gridded, including dividing the three-dimensional geological grid into layers of 1-3 m each.

4. The method for fracturing risk assessment based on three-dimensional distribution of reservoir double sweet spots fracturability according to claim 1, characterized in that: Coarsening the grid includes: determining the fracture height of the fault risk through the median, average and maximum values ​​of the fracture heights detected by on-site fracturing logging, and coarsening the grid in the small layer of the three-dimensional geological model of the block's fracturability according to the obtained fracture height.

5. The method for fracturing risk assessment based on three-dimensional distribution of double sweet spots of reservoir fracturability according to claim 4, characterized in that: The median, mean, and maximum values ​​of each cluster of fracture heights in the first section detected by on-site fracturing logging are used to select the logarithmic interpolation of fracture heights to determine the fault risk.

6. The method for fracturing risk assessment based on three-dimensional distribution of double sweet spots of reservoir fracturability according to claim 5, characterized in that: After the three-dimensional geological model of the fracturability of the block is interpolated along the transverse section, it is expanded along the designed wellbore trajectory to obtain a risk longitudinal profile along the wellbore.

7. A fracturing risk assessment device based on three-dimensional distribution of double sweet spots of reservoir fracturing, characterized in that: include: The three-dimensional geological module is suitable for obtaining the geological sweet spot data volume through normalization based on the well logging geological data of each single well in the block, so as to establish a three-dimensional geological model of the block's fracturability; The three-dimensional data volume module is suitable for calculating the three-dimensional data volume of fracturability according to the layered data of each single well in the block. The calculation of the three-dimensional data volume of fracturability includes: fitting and correcting the mechanical parameters of the whole well, establishing the mechanical parameter profile of the single well, calculating the fracturability profiles of multiple single wells according to the fracturability calculation method, interpolating the fracturability profiles of multiple single wells into the three-dimensional data volume of fracturability through the interpolation algorithm, and after interpolating the three-dimensional data volume of fracturability in the grid, coarsening the grid, and cutting the three-dimensional geological model of the block after the coarsening of the grid along the horizontal direction to obtain the risk plane distribution of each reservoir layer at different depths; An interpolation module, adapted to grid the three-dimensional geological model of the block's fracturability, and interpolate the three-dimensional data volume of the fracturability within the grid; The evaluation module is suitable for obtaining the planar distribution of fracturing risks of each reservoir at different depths along the three-dimensional geological model of the fracturability of the block after transverse sectioning and interpolation, so as to evaluate the fracturing risks of the strata and well locations of the block, determine the fracturing risk level according to the horizontal and vertical distances of the faults, the vertical distance between the reservoir and the high aquifer, and the water saturation of the reservoir, and evaluate the fracturing risks of the strata and well locations of the block.

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