Fracturing optimization method and device based on shale gas reservoir horizontal well

Abstract

The invention provides a fracturing optimization method and device based on a shale gas reservoir horizontal well. The fracturing optimization method based on the shale gas reservoir horizontal well comprises the steps that an engineering dessert coefficient is determined according to engineering dessert parameters; determining a physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well; determining the productivity contribution rate according to the dimensionless flow and the dimensionless total flow of each crack; determining comprehensive index data according to the engineering dessert coefficient, the physical property index and the productivity contribution rate; and determining a corresponding fractured well section according to a comparison result of the comprehensive index data and a preset index threshold value. The well section needing preferential fracturing can be determined, and benefits are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas development, and in particular, to a fracturing optimization method and device based on horizontal wells in shale gas reservoirs. Background Art

[0002] The horizontal well segmented fracturing technology is one of the important means for shale gas reservoir development. Its purpose is to effectively communicate the reservoir and the wellbore by increasing the contact area between the horizontal wellbore and the reservoir. And horizontal well segmentation is an important pre-work to ensure later cluster fracturing and fracturing construction operations. The focus of the segmentation work is to find the "sweet spots" of the shale gas reservoir along the horizontal wellbore. The so-called "sweet spots" refer to the best positions for shale gas exploration and development along the horizontal wellbore, and the development sections are divided based on the "sweet spot" positions.

[0003] Productivity analysis is an important part of reservoir engineering. It can help engineers determine various physical parameters of test wells and formation characteristics, production capacity, and the connectivity relationships between oil, gas, and water and between wells. Establishing an appropriate fracturing horizontal well productivity model for horizontal wells can achieve the purposes of reasonable productivity allocation and determining the fracturing scale. Summary of the Invention

[0004] The main purpose of the embodiments of the present invention is to provide a fracturing optimization method and device based on horizontal wells in shale gas reservoirs to determine the well sections that need to be fractured preferentially.

[0005] To achieve the above purpose, the embodiments of the present invention provide a fracturing optimization method based on horizontal wells in shale gas reservoirs, including:

[0006] Determining an engineering sweet spot coefficient according to engineering sweet spot parameters;

[0007] Determining a physical property index according to the permeability, porosity, gas saturation, and organic carbon content of the horizontal well;

[0008] Determining a productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture;

[0009] Determining comprehensive index data according to the engineering sweet spot coefficient, the physical property index, and the productivity contribution rate;

[0010] Determining the corresponding fracturing well sections according to the comparison result between the comprehensive index data and a preset index threshold.

[0011] In one of the embodiments, determining the comprehensive index data according to the engineering sweet spot coefficient, the physical property index, and the productivity contribution rate includes:

[0012] Determining compressibility index data according to the engineering sweet spot coefficient;

[0013] Determine the physical property index data according to the physical property index;

[0014] Determine the production capacity index data according to the production capacity contribution rate;

[0015] Determine the comprehensive index data according to the compressibility index data, the physical property index data and the production capacity index data.

[0016] In one embodiment, it further includes:

[0017] Determine the dimensionless total flow rate according to the dimensionless bottom-hole pressure and the Laplace time variable;

[0018] Determine the dimensionless flow rate of the fracture according to the production of the fracture and the total production of the fractured horizontal well.

[0019] In one embodiment, it further includes:

[0020] Determine the dimensionless bottom-hole pressure according to the Laplace time variable, the dimensionless bottom-hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

[0021] In one embodiment, it further includes:

[0022] Determine the dimensionless bottom-hole pseudo-pressure according to the reservoir permeability, the dimensionless fracture conductivity, the dimensionless distance and the dimensionless fracture flow rate of the fracture.

[0023] An embodiment of the present invention further provides a fracturing optimization device based on a horizontal well in a shale gas reservoir, including:

[0024] An engineering sweet spot coefficient module, configured to determine an engineering sweet spot coefficient according to engineering sweet spot parameters;

[0025] A physical property index module, configured to determine a physical property index according to the permeability, porosity, gas saturation and organic carbon content of a horizontal well;

[0026] A production capacity contribution rate module, configured to determine a production capacity contribution rate according to the dimensionless flow rate of each fracture and the dimensionless total flow rate;

[0027] A comprehensive index data module, configured to determine comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the production capacity contribution rate;

[0028] A fracturing interval module, configured to determine a corresponding fracturing interval according to a comparison result between the comprehensive index data and a preset index threshold.

[0029] In one embodiment, the comprehensive index data module includes:

[0030] A compressibility index data unit, configured to determine compressibility index data according to the engineering sweet spot coefficient;

[0031] A physical property index data unit for determining physical property index data according to the physical property index;

[0032] A productivity index data unit for determining productivity index data according to the productivity contribution rate;

[0033] A comprehensive index data unit for determining the comprehensive index data according to the compressibility index data, the physical property index data and the productivity index data.

[0034] In one embodiment, it further includes:

[0035] A dimensionless total flow rate module for determining the dimensionless total flow rate according to the dimensionless bottom hole pressure and the Laplace time variable;

[0036] A dimensionless flow rate module for determining the dimensionless flow rate of the fracture according to the production rate of the fracture and the total production rate of the fractured horizontal well.

[0037] In one embodiment, it further includes:

[0038] A dimensionless bottom hole pressure module for determining the dimensionless bottom hole pressure according to the Laplace time variable, the dimensionless bottom hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

[0039] In one embodiment, it further includes:

[0040] A dimensionless bottom hole pseudo-pressure module for determining the dimensionless bottom hole pseudo-pressure according to the reservoir permeability, the dimensionless fracture conductivity, the dimensionless distance and the dimensionless fracture flow rate of the fracture.

[0041] An embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, the steps of the fracturing optimization method based on horizontal wells in shale gas reservoirs are implemented.

[0042] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the fracturing optimization method based on horizontal wells in shale gas reservoirs are implemented.

[0043] An embodiment of the present invention further provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the steps of the fracturing optimization method based on horizontal wells in shale gas reservoirs are implemented.

[0044] The fracturing optimization method and device based on horizontal wells in shale gas reservoirs according to the embodiments of the present invention first determine the engineering sweet spot coefficient, physical property index, and productivity contribution rate, and then determine the well sections that need to be fractured preferentially according to the above indexes, which can improve the efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0046] Figure 1 is the flowchart of the fracturing optimization method based on horizontal wells in shale gas reservoirs according to the embodiments of the present invention;

[0047] Figure 2 is the flowchart of determining the dimensionless flow rate according to the embodiments of the present invention;

[0048] Figure 3 is the flowchart of S104 according to the embodiments of the present invention;

[0049] Figure 4 is the cumulative frequency histogram of the compressibility index according to the embodiments of the present invention;

[0050] Figure 5 is the graph of the compressibility index data along the wellbore according to the embodiments of the present invention;

[0051] Figure 6 is the cumulative frequency histogram of the physical property index according to the embodiments of the present invention;

[0052] Figure 7 is the graph of the physical property index data along the wellbore according to the embodiments of the present invention;

[0053] Figure 8 is the schematic diagram of sweet spot fracture layout according to the embodiments of the present invention;

[0054] Figure 9 is the schematic diagram of the productivity contribution rate of different fractures according to the embodiments of the present invention;

[0055] Figure 10 is the cumulative frequency histogram of the productivity index according to the embodiments of the present invention;

[0056] Figure 11 is the three-dimensional graph of the comprehensive index data according to the embodiments of the present invention;

[0057] Figure 12 is the graph of the comprehensive index data according to the embodiments of the present invention;

[0058] Figure 13It is a structural block diagram of a fracturing optimization device based on a horizontal well in a shale gas reservoir in an embodiment of the present invention;

[0059] Figure 14 It is a schematic block diagram of the system composition of the electronic device 9600 in an embodiment of the present application. Specific embodiments

[0060] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0061] Those skilled in the art know that the embodiments of the present invention can be implemented as a system, a device, a device, a method, or a computer program product. Therefore, the present disclosure can be specifically implemented in the following forms: completely hardware, completely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0062] Based on the division of geological and engineering sweet spots, the present invention further adds factors affecting production capacity, and further subdivides the geological and engineering sweet spots to achieve the purpose of refined sectioning and improved economic benefits. Figure 1 It is a flowchart of a fracturing optimization method based on a horizontal well in a shale gas reservoir in an embodiment of the present invention. As Figure 1 shown, the fracturing optimization method based on a horizontal well in a shale gas reservoir includes:

[0063] S101: Determine the engineering sweet spot coefficient according to the engineering sweet spot parameters.

[0064] Specifically, when implemented, the engineering sweet spot parameters of shale gas are both independent and mutually influential. For example, between brittle minerals and rock mechanics parameters, multiple engineering sweet spot parameters are used and relevant calculation formulas and the independence weight coefficient model are used to evaluate the engineering sweet spot. The independence weight coefficient model determines the index weight according to the collinearity strength between each index and other indexes. Suppose there are index items X1, X2,..., X m , if the multiple correlation coefficient of a certain index with other indexes is larger, it means that the collinear relationship between this index and other indexes is stronger, and it is easier to be represented by the linear combination of other indexes, then the more duplicate information, and thus it is considered that the weight of this index is smaller. Among them, the multiple correlation coefficient CR i of a certain index with other indexes is calculated as:

[0065]

[0066] Among them, CR i is the multiple correlation coefficient, Xi Represents the dessert parameters of a certain project; Represents the average value of the dessert parameters of a certain project; Represents the linear combination value of the dessert parameters of other projects, β i , where β0 is a constant.

[0067] Use the correlation coefficient method to optimize the main project dessert parameters, and combine the multiple correlation coefficient to obtain the comprehensive coefficient of each main project dessert parameter. Comprehensive coefficient = R i / CR i , where R i Represents the correlation coefficient (the i-th correlation coefficient), and then use the comprehensive coefficient for normalization processing to obtain the weights of each main project dessert parameter. The calculation formula of the weight (W i ) is:

[0068]

[0069] Since the correlation coefficient between the transformed main project dessert parameters and the proppant concentration is used, the independent weight coefficient model is adopted to evaluate the shale gas project dessert. Therefore, this project dessert coefficient is called the project dessert coefficient, which is expressed as:

[0070]

[0071] Among them, X E is the project dessert coefficient, and n is the number of data.

[0072] S102: Determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well.

[0073] In specific implementation, for shale gas reservoirs, the better the physical properties and the higher the gas content, the stronger the gas supply capacity of the reservoir.

[0074] For geological desserts, mainly select high-quality reservoirs with high permeability, high porosity, good gas logging display (high gas saturation) and high organic carbon content for sectioning. Considering that the characteristic parameter data of the horizontal section of shale gas wells have small differences and are concentrated, the normalization method is used to eliminate the influence of the inconsistent units and orders of magnitude of the original data of each variable, map the values to the range of [0,1], and establish a physical property index evaluation model:

[0075]

[0076] Among them, P index is the physical property index, dimensionless; K i is the permeability at a certain position of the horizontal well, K max is the maximum value of the permeability along the horizontal well section, K min is the minimum value of the permeability along the horizontal well section, and the units are all mD; φi is the porosity at a certain position in the horizontal well, φ max is the maximum value of the porosity along the horizontal well section, φ min is the minimum value of the porosity along the horizontal well section; S gi is the gas saturation at a certain position in the horizontal well, S gmax is the maximum value of the gas saturation along the horizontal well section, S gmin is the minimum value of the gas saturation along the horizontal well section; TOC i is the organic carbon content at a certain position in the horizontal well, TOC max is the maximum value of the organic carbon content along the horizontal well section, TOC min is the minimum value of the organic carbon content along the horizontal well section.

[0077] S103: Determine the productivity contribution rate according to the dimensionless flow rate and the dimensionless total flow rate of each fracture.

[0078] Among them, the productivity contribution rate is q FlD / q FlD is the dimensionless flow rate of the l-th fracture, is the Lapalce dimensionless total flow rate.

[0079] Figure 2 is the flow chart for determining the dimensionless flow rate in the embodiment of the present invention. As Figure 2 shown, the fracturing optimization method for horizontal wells in shale gas reservoirs further includes:

[0080] S201: Determine the dimensionless total flow rate according to the dimensionless bottom hole pressure and the Laplace time variable.

[0081] In one embodiment, the dimensionless total flow rate can be obtained through the following formula:

[0082]

[0083] Among them, u is the Laplace time variable, is the dimensionless bottom hole pressure.

[0084] In one embodiment, it further includes:

[0085] Determine the dimensionless bottom hole pressure according to the Laplace time variable, the dimensionless bottom hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

[0086] During specific implementation, for a quantitative production fracturing horizontal well, the sum of the slot yields of each fracture should be equal to the total production q of the fracturing horizontal well sc , then in the Laplace space, there is the following dimensionless flow normalization condition:

[0087]

[0088] where L FlD is the dimensionless fracture half-length of the l-th fracture, and m is the number of fractures.

[0089] A definite line source solution can be obtained for each fracture, and the bottom-hole flowing pressure of the system of equations can be solved by using the Gaussian elimination method in the Laplace space. Considering the effects of wellbore storage and skin effect according to the Duhamel principle, the dimensionless bottom-hole pressure can be determined:

[0090]

[0091] where is the dimensionless bottom-hole pseudo-pressure, C D is the dimensionless wellbore storage coefficient, s f is the fracture avoidance skin data.

[0092] In one embodiment, it further includes:

[0093] Determining the dimensionless bottom-hole pseudo-pressure according to the reservoir permeability, dimensionless fracture conductivity, dimensionless distance, and dimensionless fracture flow rate of the fracture.

[0094] Specifically, when implementing, the dimensionless bottom-hole pseudo-pressure can be determined by the following formula:

[0095]

[0096] where K is the reservoir permeability, with the unit of mD; R FlD is the dimensionless conductivity of the l-th fracture, x D is the dimensionless distance in the x direction, is the dimensionless fracture flow rate of the l-th fracture in the Laplace space, is the dimensionless flow rate per unit length in the Laplace space, LflD is the dimensionless fracture half-length of the l-th fracture, K0 is the modified Bessel function of the second kind of order zero, f1 is the first coefficient, R D is the dimensionless distance, A c is the second coefficient, and I0 is the modified Bessel function of the first kind of order zero.

[0097] In one embodiment, the derivation process of the dimensionless bottom-hole pseudo-pressure is as follows:

[0098] Figure 8 is the schematic diagram of the sweet spot fracture layout in the embodiment of the present invention. As Figure 8 shown, in order to obtain the productivity contributions at different positions, the established productivity prediction model of the fractured horizontal well can be used to perform fracture layout treatment in the geological and engineering sweet spot sections.

[0099] According to the source function theory, the fracturing cracks can be approximately regarded as the areal sources in the shale gas reservoir, that is, the pressure response of the reservoir is the superposition result caused by m continuous areal sources. This model is only shown as an example and does not mean that it is limited to this type of model. It is particularly important to establish a productivity model according to the field situation. The pressure response of the l-th crack can be obtained from formula (5):

[0100]

[0101] Among them, is the dimensionless pressure in the Laplace space of the l-th crack, and L fLD is the dimensionless half-length of the l-th crack, K is the reservoir permeability with the unit of mD; α is the integration variable.

[0102] The seepage model of the hydraulic fracture is as follows:

[0103]

[0104] Among them, k Fl is the permeability of the l-th crack with the unit of mD; p F is the pressure of the crack with the unit of MPa; μ is the gas viscosity with the unit of mPa·s; z is the gas deviation factor, dimensionless. x F is the half-length of the crack with the unit of m. x and y are the Cartesian coordinate directions respectively.

[0105] For the second term in formula (6):

[0106]

[0107] Among them, W Fl is the width of the l-th crack with the unit of m; y l is the y-direction position coordinate of the l-th crack.

[0108] Combining formula (5) and formula (7) can obtain:

[0109]

[0110] There is no flow in the y direction, so formula (8) becomes:

[0111]

[0112] The coupling point of the natural fracture and the hydraulic fracture is:

[0113]

[0114] Among them, T sc is the temperature under standard conditions with the unit of °C; p scis the pressure under standard conditions, with the unit of MPa; T is the reservoir temperature, with the unit of °C.

[0115] Combining Equation (9) and Equation (10) gives:

[0116]

[0117] where k f1 is the matrix permeability, with the unit of mD.

[0118] Assume the production rate of the l-th fracture is q Fl , then:

[0119]

[0120] where h is the reservoir thickness, with the unit of m.

[0121] At the fracture boundary:

[0122]

[0123] The line source solution q of the coupling of natural fractures and hydraulic fracturing L is:

[0124]

[0125] Nondimensionalize the above equation and perform Laplace transform to obtain:

[0126]

[0127] where, is the dimensionless pseudo-pressure of the fracture in Laplace space; x D is the dimensionless distance in the x direction; y D is the dimensionless distance in the y direction; W FD is the dimensionless fracture width; R FlD is the dimensionless conductivity of the l-th fracture, k f1 is the matrix permeability, with the unit of mD; L is the reference length, with the unit of m; y Dl is the dimensionless coordinate of the position of the l-th fracture in the y direction.

[0128]

[0129]

[0130] where LFlD is the dimensionless half-length of the l-th fracture.

[0131]

[0132] Furthermore, we get:

[0133]

[0134] Among them, is the dimensionless fracture pseudo-pressure of the l-th fracture; is the flow rate per unit length of Laplace dimensionless.

[0135]

[0136] At the wall surface of the l-th fracturing fracture, the pressure in the reservoir is equal to the pressure in the fracture. Then, by combining formula (19) and formula (20), the dimensionless bottom-hole pseudo-pressure formula can be obtained:

[0137]

[0138] S202: Determine the dimensionless flow rate of the fracture according to the production of the fracture and the total production of the fractured horizontal well.

[0139] Specifically, the dimensionless flow rate of the fracture can be obtained through the following formula:

[0140]

[0141] where q Fl is the production of the l-th fracture, and q sc is the total production of the fractured horizontal well.

[0142] S104: Determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index, and the productivity contribution rate.

[0143] Figure 3 is the flow chart of S104 in the embodiment of the present invention. As Figure 3 shown, S104 includes:

[0144] S301: Determine the compressibility index data according to the engineering sweet spot coefficient.

[0145] Figure 4 is the cumulative frequency histogram of the compressibility index in the embodiment of the present invention. Figure 5 is the chart of the compressibility index data along the wellbore in the embodiment of the present invention. As Figure 4 - Figure 5 shown, the engineering sweet spot coefficient is the compressibility index; calculate any coefficient of the engineering sweet spot of the reservoir along the horizontal wellbore according to the engineering sweet spot coefficient calculation method, and calibrate any coefficient into 3 grades of good, medium, and poor. The cumulative frequency less than 33.3% is recognized as poor, 33.3% - 66.6% is recognized as medium, and greater than 66.6% is recognized as good. The corresponding compressibility index data are 1 point, 3 points, and 5 points respectively; Figure 5 The abscissa in

[0146] S302: Determine the physical property index data according to the physical property index.

[0147] Figure 6 is the cumulative frequency histogram of the physical property index in the embodiment of the present invention. Figure 7 is the chart of the physical property index data along the wellbore in the embodiment of the present invention. As Figure 6 - Figure 7 shown, the K along the horizontal well can be obtained according to the geophysical logging of the shale gas well i , φ i , S gi , TOC i , and the physical property index along the horizontal well can be calculated using formula (4). Segment the values of the physical property index along the horizontal well section, count the number and cumulative frequency of different value segments, and the cumulative frequency less than 33.3% can be identified as poor, 33.3% - 66.6% as medium, and greater than 66.6% as good. The corresponding physical property index data are 1 point, 3 points, and 5 points respectively. Figure 7 The abscissa in [] is the depth of the horizontal well section, with the unit of m.

[0148] S303: Determine the productivity index data according to the productivity contribution rate.

[0149] Figure 9 is the schematic diagram of the productivity contribution rate of different fractures in the embodiment of the present invention. Figure 10 is the cumulative frequency histogram of the productivity index in the embodiment of the present invention. As Figure 9 - Figure 10 shown, t D is the real - space time converted from the Laplace - space time u. Make a cumulative frequency distribution histogram according to the productivity contribution index of each section. Similarly, the productivity cumulative frequency less than 33.3% is identified as poor, 33.3% - 66.6% as medium, and greater than 66.6% as good, and they correspond to 1 point, 3 points, and 5 points respectively, further screening the productivity sweet spots. Figure 10 The productivity index data in [] is the productivity contribution rate.

[0150] S304: Determine the comprehensive index data according to the compressibility index data, the physical property index data, and the productivity index data.

[0151] Figure 11 is the three - dimensional diagram of the comprehensive index data in the embodiment of the present invention. Figure 12 is the chart of the comprehensive index data in the embodiment of the present invention. As Figure 11 - Figure 12 shown, superimpose the index data respectively assigned to the three indicators of gas reservoir - engineering - productivity. Combine the three data of each of the three factors to obtain twenty - seven results, and obtain the comprehensive index data by synthesizing the three sweet spot index data.

[0152] S105: Determine the corresponding fracturing interval according to the comparison result between the comprehensive index data and the preset index threshold.

[0153] In specific implementation, when the comprehensive index data is greater than the preset index threshold, the fracturing interval corresponding to this data is preferentially fractured; otherwise, it is not fractured.

[0154] Figure 1 The execution subject of the shown fracturing optimization method based on horizontal wells in shale gas reservoirs can be a computer. From Figure 1 the shown process, it can be seen that the fracturing optimization method based on horizontal wells in shale gas reservoirs in the embodiments of the present invention uses the seepage physical equation, predicts the production capacity according to the seam treatment at the engineering and geological sweet spots, further improves the seam placement accuracy according to the production capacity of each segment, reduces ineffective or inefficient fracturing segments, and achieves the purpose of reducing costs and improving economic benefits.

[0155] Based on the same inventive concept, the embodiments of the present invention also provide a fracturing optimization device based on horizontal wells in shale gas reservoirs. Since the principle of solving problems by this device is similar to that of the fracturing optimization method based on horizontal wells in shale gas reservoirs, the implementation of this device can refer to the implementation of the method, and the repeated parts will not be described again.

[0156] Figure 13 It is the structural block diagram of the fracturing optimization device based on horizontal wells in shale gas reservoirs in the embodiments of the present invention. As Figure 13 shown, the fracturing optimization device based on horizontal wells in shale gas reservoirs includes:

[0157] Engineering sweet spot coefficient module, used to determine the engineering sweet spot coefficient according to engineering sweet spot parameters;

[0158] Physical property index module, used to determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well;

[0159] Production contribution rate module, used to determine the production contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture;

[0160] Comprehensive index data module, used to determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the production contribution rate;

[0161] Fracturing interval module, used to determine the corresponding fracturing interval according to the comparison result between the comprehensive index data and the preset index threshold.

[0162] In one of the embodiments, the comprehensive index data module includes:

[0163] Compressibility index data unit, used to determine the compressibility index data according to the engineering sweet spot coefficient;

[0164] Physical property index data unit, configured to determine physical property index data according to the physical property index;

[0165] Production capacity index data unit, configured to determine production capacity index data according to the production capacity contribution rate;

[0166] Comprehensive index data unit, configured to determine the comprehensive index data according to the compressibility index data, the physical property index data and the production capacity index data.

[0167] In one embodiment, it further includes:

[0168] Dimensionless total flow module, configured to determine the dimensionless total flow according to the dimensionless bottom-hole pressure and the Laplace time variable;

[0169] Dimensionless flow module, configured to determine the dimensionless flow of the fracture according to the production of the fracture and the total production of the fractured horizontal well.

[0170] In one embodiment, it further includes:

[0171] Dimensionless bottom-hole pressure module, configured to determine the dimensionless bottom-hole pressure according to the Laplace time variable, the dimensionless bottom-hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

[0172] In one embodiment, it further includes:

[0173] Dimensionless bottom-hole pseudo-pressure module, configured to determine the dimensionless bottom-hole pseudo-pressure according to the reservoir permeability, the dimensionless fracture conductivity, the dimensionless distance and the dimensionless fracture flow of the fracture.

[0174] In summary, the fracturing optimization device based on the horizontal well in the shale gas reservoir according to the embodiment of the present invention first determines the engineering sweet spot coefficient, the physical property index and the production capacity contribution rate, and then determines the well section that needs to be fractured preferentially according to the above indexes, which can improve the efficiency.

[0175] Figure 14 It is a schematic block diagram of the system composition of the electronic device 9600 according to the embodiment of the present application. As Figure 14 shown, the electronic device 9600 may include a central processing unit 9100 and a memory 9140; the memory 9140 is coupled to the central processing unit 9100. It should be noted that this Figure 14 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0176] In one embodiment, the function of the fracturing optimization method based on the horizontal well in the shale gas reservoir may be integrated into the central processing unit 9100. Among them, the central processing unit 9100 may be configured to perform the following controls:

[0177] Determine the engineering sweet spot coefficient according to the engineering sweet spot parameters;

[0178] Determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well;

[0179] Determine the productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture;

[0180] Determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate;

[0181] Determine the corresponding fracturing well section according to the comparison result between the comprehensive index data and the preset index threshold.

[0182] As can be seen from the above description, the fracturing optimization method based on horizontal wells in shale gas reservoirs provided by this application first determines the engineering sweet spot coefficient, the physical property index and the productivity contribution rate, and then determines the well section that needs to be fractured preferentially according to the above indexes, which can improve the efficiency.

[0183] In another embodiment, the fracturing optimization device based on horizontal wells in shale gas reservoirs can be separately configured from the central processing unit 9100. For example, the fracturing optimization device based on horizontal wells in shale gas reservoirs can be configured as a chip connected to the central processing unit 9100, and the functions of the fracturing optimization method based on horizontal wells in shale gas reservoirs can be realized through the control of the central processing unit.

[0184] As Figure 14 shown, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It should be noted that the electronic device 9600 does not necessarily have to include Figure 14 all the components shown in; in addition, the electronic device 9600 may further include Figure 14 components not shown in, and reference may be made to the prior art.

[0185] As Figure 14 shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processing unit 9100 receives inputs and controls the operations of the various components of the electronic device 9600.

[0186] Among them, the memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, or other suitable devices. The above information related to failures can be stored, and in addition, programs for executing relevant information can be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0187] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to supply power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display can be, for example, an LCD display, but is not limited thereto.

[0188] The memory 9140 can be a solid-state memory, for example, a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It can also be a memory that stores information even when power is off, can be selectively erased and has more data. Examples of such a memory are sometimes referred to as EPROMs, etc. The memory 9140 can also be some other type of device. The memory 9140 includes a buffer 9141 (sometimes referred to as a buffer memory). The memory 9140 can include an application / function storage unit 9142, which is used to store application programs and function programs or the processes for operating the electronic device 9600 by the central processing unit 9100.

[0189] The memory 9140 can also include a data storage unit 9143, which is used to store data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 can include various drivers of the electronic device for communication functions and / or for performing other functions of the electronic device (such as a messaging application, an address book application, etc.).

[0190] The communication module 9110 is a transmitter / receiver 9110 that transmits and receives signals via the antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processing unit 9100 to provide input signals and receive output signals, which can be the same as in the case of a conventional mobile communication terminal.

[0191] Based on different communication technologies, multiple communication modules 9110 can be provided in the same electronic device, such as a cellular network module, a Bluetooth module, and / or a wireless local area network module, etc. The communication module (transmitter / receiver) 9110 is also coupled to the speaker 9131 and the microphone 9132 via the audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, so as to implement the usual telecommunication functions. The audio processor 9130 can include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processing unit 9100, so that it is possible to record on the local machine through the microphone 9132 and play the sound stored on the local machine through the speaker 9131.

[0192] An embodiment of the present invention also provides a computer-readable storage medium capable of implementing all steps of the fracturing optimization method for horizontal wells in shale gas reservoirs with the execution subject being a server or a client in the above embodiments. A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, all steps of the fracturing optimization method for horizontal wells in shale gas reservoirs in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0193] Determine the engineering sweet spot coefficient according to the engineering sweet spot parameters;

[0194] Determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well;

[0195] Determine the productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture;

[0196] Determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate;

[0197] Determine the corresponding fracturing well section according to the comparison result between the comprehensive index data and the preset index threshold.

[0198] In summary, the computer-readable storage medium of the embodiment of the present invention first determines the engineering sweet spot coefficient, the physical property index and the productivity contribution rate, and then determines the well section that needs to be fractured preferentially according to the above indexes, which can improve the efficiency.

[0199] An embodiment of the present invention also provides a computer program product capable of implementing all steps of the fracturing optimization method for horizontal wells in shale gas reservoirs with the execution subject being a server or a client in the above embodiments. The computer program product includes a computer program / instructions, and when the computer program / instructions are executed by a processor, all steps of the fracturing optimization method for horizontal wells in shale gas reservoirs in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0200] Determine the engineering sweet spot coefficient according to the engineering sweet spot parameters;

[0201] Determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well;

[0202] Determine the productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture;

[0203] Determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate;

[0204] Determine the corresponding fracturing well section according to the comparison result between the comprehensive index data and the preset index threshold.

[0205] In summary, the computer program product of the embodiment of the present invention first determines the engineering sweet spot coefficient, physical property index, and productivity contribution rate, and then determines the well section that needs to be fractured preferentially according to the above indexes, which can improve the efficiency.

[0206] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program type embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0207] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0208] Although the present application provides method operation steps as described in the embodiments or flowcharts, based on routine or non-creative labor, there can be more or fewer operation steps. The order of steps listed in the embodiments is only one way among the execution orders of numerous steps and does not represent the only execution order. When the actual device or client product executes, it can be executed in the order shown in the embodiments or the drawings or in parallel (such as in a parallel processor or multi-threaded processing environment).

[0209] Although the embodiments of this specification provide method operation steps as described in the embodiments or flowcharts, based on routine or non-creative means, there can be more or fewer operation steps. The order of steps listed in the embodiments is only one way among the execution orders of numerous steps and does not represent the only execution order. When the actual device or terminal product executes, it can be executed in the order shown in the embodiments or the drawings or in parallel (such as in a parallel processor or multi-threaded processing environment, or even in a distributed data processing environment). The term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, product or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, product or device. Without further limitation, there is no exclusion of additional identical or equivalent elements in the process, method, product or device comprising the said elements.

[0210] For the sake of convenience in description, when describing the above device, it is divided into various modules according to functions for separate description. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules implementing the same function can be realized by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0211] Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, the method steps can be logically programmed to enable the controller to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Therefore, this kind of controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or the structures within the hardware component.

[0212] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0213] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0214] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, causing a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process Figure 1 one process or a plurality of processes and / or blocks Figure 1 steps for implementing the functions specified in one block or a plurality of blocks.

[0215] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0216] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

[0217] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0218] Those skilled in the art will appreciate that the embodiments of this specification may be provided as a method, system, or computer program product. Accordingly, the embodiments of this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0219] Each embodiment in this specification can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The embodiments of this specification can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0220] The embodiments in this specification are all described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and reference can be made to the partial description of the method embodiments for the relevant parts. In the description of this specification, the description of reference terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0221] The above is only the embodiments of the embodiments of this specification and is not used to limit the embodiments of this specification. For those skilled in the art, various changes and modifications can be made to the embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of this specification shall be included within the scope of the claims of the embodiments of this specification.

Claims

1. A fracturing optimization method based on horizontal wells in shale gas reservoirs, characterized in that Including: Determine the engineering sweet spot coefficient according to the engineering sweet spot parameters; Determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well; Determine the productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture; Determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate; Determine the corresponding fracturing well section according to the comparison result between the comprehensive index data and the preset index threshold.

2. The fracturing optimization method based on horizontal wells in shale gas reservoirs according to claim 1, wherein, Determining the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate includes: Determine the compressibility index data according to the engineering sweet spot coefficient; Determine the physical property index data according to the physical property index; Determine the productivity index data according to the productivity contribution rate; Determine the comprehensive index data according to the compressibility index data, the physical property index data and the productivity index data.

3. The fracturing optimization method based on horizontal wells in shale gas reservoirs according to claim 1, characterized in that, It also includes: Determine the dimensionless total flow rate according to the dimensionless bottom hole pressure and the Laplace time variable; Determine the dimensionless flow rate of the fracture according to the production of the fracture and the total production of the fractured horizontal well.

4. The fracturing optimization method based on horizontal wells in shale gas reservoirs according to claim 3, wherein, It also includes: Determine the dimensionless bottom hole pressure according to the Laplace time variable, the dimensionless bottom hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

5. The fracturing optimization method based on horizontal wells in shale gas reservoirs according to claim 4, characterized in that, It also includes: Determine the dimensionless bottom hole pseudo-pressure according to the reservoir permeability, the dimensionless fracture conductivity, the dimensionless distance and the dimensionless fracture flow rate of the fracture.

6. A fracturing optimization device based on horizontal wells in shale gas reservoirs, characterized in that, Including: An engineering sweet spot coefficient module, used to determine the engineering sweet spot coefficient according to the engineering sweet spot parameters; A physical property index module, used to determine the physical property index according to the permeability, porosity, gas saturation and organic carbon content of the horizontal well; A productivity contribution rate module, used to determine the productivity contribution rate according to the dimensionless flow rate and dimensionless total flow rate of each fracture; A comprehensive index data module, used to determine the comprehensive index data according to the engineering sweet spot coefficient, the physical property index and the productivity contribution rate; A fracturing well section module, used to determine the corresponding fracturing well section according to the comparison result between the comprehensive index data and the preset index threshold.

7. The fracturing optimization device based on a horizontal well in a shale gas reservoir according to claim 6, characterized in that The comprehensive index data module includes: A compressibility index data unit, used to determine the compressibility index data according to the engineering sweet spot coefficient; A physical property index data unit, used to determine the physical property index data according to the physical property index; A productivity index data unit, used to determine the productivity index data according to the productivity contribution rate; A comprehensive index data unit, used to determine the comprehensive index data according to the compressibility index data, the physical property index data and the productivity index data.

8. The fracturing optimization device based on a horizontal well in a shale gas reservoir according to claim 6, wherein It also includes: A dimensionless total flow rate module, used to determine the dimensionless total flow rate according to the dimensionless bottom hole pressure and the Laplace time variable; A dimensionless flow rate module, used to determine the dimensionless flow rate of the fracture according to the production of the fracture and the total production of the fractured horizontal well.

9. The fracturing optimization device based on a horizontal well in a shale gas reservoir according to claim 8, characterized in that It also includes: A dimensionless bottom hole pressure module, used to determine the dimensionless bottom hole pressure according to the Laplace time variable, the dimensionless bottom hole pseudo-pressure, the dimensionless wellbore storage coefficient and the fracture avoidance skin data.

10. The fracturing optimization device based on a horizontal well in a shale gas reservoir according to claim 9, characterized in that, It also includes: The dimensionless bottom-hole pseudo-pressure module is used to determine the dimensionless bottom-hole pseudo-pressure according to the reservoir permeability, the dimensionless fracture conductivity, the dimensionless distance, and the dimensionless fracture flow rate of the fracture.

11. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, the steps of the fracturing optimization method for horizontal wells in shale gas reservoirs according to any one of claims 1 to 5 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the fracturing optimization method for horizontal wells in shale gas reservoirs according to any one of claims 1 to 5 are implemented.

13. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, the steps of the fracturing optimization method for horizontal wells in shale gas reservoirs according to any one of claims 1 to 5 are implemented.

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