A method for quantitatively evaluating hydraulic fractures in the near-wellbore region

Abstract

The present invention belongs to the technical field of near-wellbore, and specifically relates to a method for quantitatively evaluating hydraulic fractures in the near-wellbore area, including the following steps: By building corresponding grids in the hydraulic fractures, wellbore and bottom layer areas, and then forming a model discretization based on non-uniform grid technology; The present invention uses the time-lapse full waveform inversion (TL-FWI) algorithm to invert this data subset to achieve high-precision reconstruction of hydraulic fractures, and obtain key attributes such as the connectivity between fractures and the wellbore, fracture extensibility, and fracture geometry, so as to achieve quantitative evaluation of hydraulic fractures in the near-wellbore area. Through the research of the present invention, we expect to promote the transformation of Krauklis waves from theory to practical application, and significantly improve the understanding of the complex fracture propagation process in underground reservoirs. This will enable the formulation of more effective operation decisions and production strategies, promote the further development of hydraulic fracturing monitoring technology, and thus improve the effect of hydraulic fracturing.

Description

Technical Field

[0001] The present invention belongs to the technical field of near-wellbore, and particularly relates to a method for quantitatively evaluating hydraulic fractures in the near-wellbore area. Background Technique

[0002] With the decreasing production of conventional oil and gas reservoirs, the importance of unconventional oil and gas reservoirs has gradually emerged. In this context, hydraulic fracturing technology has become a key link to improve the exploitation efficiency of unconventional reservoirs. Hydraulic fracturing technology effectively releases oil and gas resources in the reservoir by increasing the connectivity of unconventional reservoirs. Especially in the near-wellbore area, the effect of hydraulic fracturing directly affects the connectivity between far-field oil and gas and the wellbore, thereby affecting the well production.

[0003] Currently, microseismic monitoring technology using distributed fiber optic sensor (DAS) data and strain rate response inversion method based on low-frequency DAS (LF-DAS) data have become the main means for hydraulic fracture assessment. Although microseismic monitoring technology is mainly used for qualitative analysis of hydraulic fractures, there are certain challenges in quantitatively evaluating key attributes such as the connectivity between hydraulic fractures and the wellbore, the extensibility of hydraulic fractures, and the geometric shape. In contrast, although the LF-DAS inversion method can quantitatively evaluate hydraulic fractures in the far-field area, it faces great difficulties in monitoring hydraulic fractures in the near-wellbore area (i.e., within several meters from the wellbore to the formation). Therefore, there is an urgent need for a method that can accurately characterize hydraulic fractures in the near-wellbore area to address this challenge. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for quantitatively evaluating hydraulic fractures in the near-wellbore area, aiming to solve the problem that currently, microseismic monitoring technology using distributed fiber optic sensor (DAS) data and strain rate response inversion method based on low-frequency DAS (LF-DAS) data have become the main means for hydraulic fracture assessment. Although microseismic monitoring technology is mainly used for qualitative analysis of hydraulic fractures, there are certain challenges in quantitatively evaluating key attributes such as the connectivity between hydraulic fractures and the wellbore, the extensibility of hydraulic fractures, and the geometric shape. In contrast, although the LF-DAS inversion method can quantitatively evaluate hydraulic fractures in the far-field area, it faces great difficulties in monitoring hydraulic fractures in the near-wellbore area (i.e., within several meters from the wellbore to the formation).

[0005] To achieve the above purpose, the present invention provides the following technical solution: A method for quantitatively evaluating hydraulic fractures in the near-wellbore area, comprising the following steps:

[0006] First step, by building corresponding grids in the hydraulic fracture, wellbore, and bottom layer areas, and then forming a model discretization based on non-uniform grid technology;

[0007] Step 2: After the completion of Step 1, obtain the DAS time-lapse response data subset. First, based on the anisotropic elastic wave equation, obtain the component v of the particle along the fiber optic cable layout direction x , and then obtain the DAS strain rate response by taking the derivative of the particle velocity component along the fiber optic direction Finally, obtain the DAS strain rate responses before and after fracturing respectively and After taking the difference, obtain the DAS time-lapse response data subset in the synthetic data

[0008] Step 3: After the completion of Step 2, invert the DAS time-lapse response data subset. First, obtain the DAS time-lapse response data subset in the actual data Then construct the TL-FWI error function, and obtain the gradient of the objective function through a gradient-based method. Finally, update the initial model based on the gradient of the objective function until the error of TL-FWI meets a certain threshold, and the development of hydraulic fractures in the near-wellbore area can be obtained;

[0009] Step 4: The conclusion obtained after the completion of Step 3 can be used to quantitatively evaluate the hydraulic fractures in the near-wellbore area

[0010] As a method for quantitatively evaluating hydraulic fractures in the near-wellbore area of the present invention, preferably, in Step 1, the hydraulic fracture area is discretized using a smaller grid, the wellbore area is discretized using a medium grid, and the bottom layer area is discretized using a large grid

[0011] As a method for quantitatively evaluating hydraulic fractures in the near-wellbore area of the present invention, preferably, in Step 2, on the basis of discretizing the model using a non-uniform grid, the anisotropic elastic wave equation is used to solve the DAS response. The anisotropic elastic wave equation is shown as follows

[0012]

[0013] As a method for quantitatively evaluating hydraulic fractures in the near-wellbore area of the present invention, preferably, in the anisotropic elastic wave equation, c 11 、c 13 、c 33 、c 44 are anisotropic elastic parameters, and v x 、v z are the horizontal and vertical components of the particle velocity. By applying a water hammer signal at the wellhead and solving the anisotropic elastic wave equation, we can obtain the horizontal component data v of the particle velocity along the fiber optic cable layout direction in the horizontal well x , then the DAS strain rate response can be obtained by the following formula

[0014] As a quantitative evaluation method for hydraulic fractures in the near-wellbore area of the present invention, preferably, represents the partial derivative along the horizontal direction, that is, the partial derivative along the fiber optic direction. Through the above formula, the DAS strain rate response can be obtained from the anisotropic elastic wave equation.

[0015] As a quantitative evaluation method for hydraulic fractures in the near-wellbore area of the present invention, preferably, through the techniques of the first step and the second step, a subset of DAS time-lapse response data dominated by Krauklis waves can be obtained. On this basis, we can obtain the subset of DAS time-lapse response data in the actual data in the same way Based on synthetic data and actual data We can construct the objective function of TL-FWI as shown in the following formula:

[0016]

[0017] As a quantitative evaluation method for hydraulic fractures in the near-wellbore area of the present invention, preferably, where is the data residual, E(m) is the objective function of TL-FWI, and m is the model parameter, that is, the anisotropic elastic parameter. The derivative of the objective function can be obtained through gradient-based algorithms and the model is updated through the following formula:

[0018]

[0019] As a quantitative evaluation method for hydraulic fractures in the near-wellbore area of the present invention, preferably, where m is n the model obtained in the nth iteration, and m n+1 is the new model updated based on the nth model, and μ n is the update step size. When the error of TL-FWI is less than a certain threshold, the time-lapse change of the hydraulic fracture can be obtained.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] The objective of the present invention is to solve the problem of the difficulty in quantitatively evaluating hydraulic fractures in the near-wellbore area. By making full use of the advantages of full-wellbore coverage and wide-azimuth reception of distributed fiber optic acoustic sensing system (DAS) data, and combining with the time-lapse inversion strategy, the present invention aims to utilize the time-lapse response difference of DAS data recorded before and after fracturing to extract a data subset containing the Krauklis wave response. By using the time-lapse full waveform inversion (TL-FWI) algorithm to invert this data subset, high-precision reconstruction of hydraulic fractures can be achieved, and key attributes such as the connectivity between fractures and the wellbore, fracture extensibility, and fracture geometry can be obtained, so as to realize the quantitative evaluation of hydraulic fractures in the near-wellbore area. Through the research of the present invention, we expect to promote the transformation of Krauklis waves from theory to practical application, and significantly improve the understanding of the complex fracture propagation process in underground reservoirs. This will enable the formulation of more effective operation decisions and production strategies, promote the further development of hydraulic fracturing monitoring technology, and thus improve the effect of hydraulic fracturing. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0023] Figure 1 is a schematic flowchart of the present invention;

[0024] Figure 2 is a schematic diagram of a) data before fracturing; b) data after fracturing; c) time-lapse response data subset of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the 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 of 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 shall fall within the protection scope of the present invention.

[0026] Please refer to Figure 1-2 , the present invention provides the following technical solutions: A method for quantitatively evaluating hydraulic fractures in the near-wellbore area, including the following steps:

[0027] First step, by building corresponding grids in the hydraulic fracture, wellbore, and bottom layer areas, and then forming a model discretization based on non-uniform grid technology;

[0028] Second step, after the first step is completed, obtain the DAS time-lapse response data subset. First, based on the anisotropic elastic wave equation, obtain the component v of the particle along the fiber optic layout direction x, and then obtain the DAS strain rate response by taking the derivative of the particle velocity component along the fiber optic direction Finally, obtain the DAS strain rate responses before and after fracturing respectively and After taking the difference, obtain the DAS time shift response data subset in the synthetic data

[0029] Step 3: After Step 2 is completed, invert the DAS time shift response data subset. First, obtain the DAS time shift response data subset in the actual data Then construct the TL-FWI error function, and obtain the gradient of the objective function through a gradient-based method. Finally, update the initial model based on the gradient of the objective function until the error of TL-FWI meets a certain threshold, and the development of hydraulic fractures in the near-wellbore area can be obtained;

[0030] Step 4: The conclusion obtained after Step 3 can be used to quantitatively evaluate the hydraulic fractures in the near-wellbore area.

[0031] Preferably: In the first step, the hydraulic fracture area is discretized with a smaller grid, the wellbore area is discretized with a medium grid, and the bottom layer area is discretized with a large grid.

[0032] Preferably: In the second step, on the basis of discretizing the model with a non-uniform grid, use the anisotropic elastic wave equation to solve the DAS response. The anisotropic elastic wave equation is shown as follows:

[0033]

[0034] In the anisotropic elastic wave equation, c 11 , c 13 , c 33 , c 44 are anisotropic elastic parameters, and v x , v z are the horizontal and vertical components of the particle velocity. By applying a water hammer signal at the wellhead and solving the anisotropic elastic wave equation, we can obtain the horizontal component data v x of the particle velocity along the fiber optic layout direction in the horizontal well, and then the DAS strain rate response can be obtained by the following formula

[0035] represents the partial derivative along the horizontal direction, that is, the partial derivative along the fiber optic direction. Through the above formula, the DAS strain rate response can be obtained from the anisotropic elastic wave equation.

[0036] In specific use, first obtain the DAS strain rate response before fracturing (Figure 2 a), After the fracturing is completed, we can obtain the DAS strain rate response after fracturing. ( Figure 2 b). By obtaining the difference between the DAS strain rate response after fracturing and that before fracturing, we can obtain a subset of DAS time-lapse response data. ( Figure 2 c). As can be seen from Figure 2 c, the subset of time-lapse response data only contains tube waves and Krauklis waves. By using preprocessing techniques to remove the tube waves, we can obtain a subset of DAS time-lapse response data dominated by Krauklis waves.

[0037] Preferably: Through the techniques of the first step and the second step, we can obtain a subset of DAS time-lapse response data dominated by Krauklis waves. On this basis, we can obtain a subset of DAS time-lapse response data in the actual data in the same way. Based on synthetic data and actual data we can construct the objective function of TL-FWI as shown in the following equation:

[0038]

[0039] where is the data residual, E(m) is the objective function of TL-FWI, m is the model parameter, that is, the anisotropic elastic parameter. The derivative of the objective function can be obtained through gradient-based algorithms. and the model is updated through the following equation:

[0040]

[0041] where m n is the model obtained at the nth iteration, m n+1 is the new model updated based on the nth model, and μ n is the update step size. When the error of TL-FWI is less than a certain threshold, the time-lapse change of the hydraulic fracture can be obtained.

[0042] The technical solution for quantitative evaluation of near-wellbore hydraulic fractures based on Krauklis waves and DAS can be mainly divided into four parts. The first part is the discretization of the model based on non-uniform grid technology. The second part is the extraction of subsets of DAS time-lapse response data. The third part is the inversion of the subsets of DAS time-lapse response data to obtain the time-lapse change information of near-wellbore hydraulic fractures. The fourth part is the quantitative evaluation of key attributes such as the connectivity between hydraulic fractures and the wellbore, the extensibility of hydraulic fractures, and the geometric shape of hydraulic fractures. Based on the time-lapse changes of hydraulic fractures, key attributes such as the connectivity between hydraulic fractures and the wellbore, the extensibility of hydraulic fractures, and the geometric shape of hydraulic fractures can be obtained, thereby realizing the quantitative evaluation of near-wellbore hydraulic fractures, which helps to guide production and operation decisions and promote the further development of hydraulic fracturing monitoring technology.

[0043] By using the response of Krauklis waves, which is directly related to fracture properties, to invert near-wellbore hydraulic fractures, the problem of difficult quantitative evaluation of near-wellbore hydraulic fractures is overcome, and the evaluation of hydraulic fractures is advanced from qualitative analysis to quantitative analysis.

[0044] The non-uniform grid technology is used to discretize the multi-scale model system of fracture-wellbore-formation, which greatly reduces the calculation cost and promotes the development of Krauklis wave numerical simulation technology.

[0045] Combined with the DAS technology widely used in hydraulic fracturing monitoring, this technical solution breaks through the barrier that Krauklis waves are limited to theoretical derivation and laboratory simulation, and promotes the practical application of Krauklis waves.

[0046] The TL-FWI technology is used to invert the DAS response. On the one hand, it can extract the data subsets dominated by Krauklis waves for inversion, greatly reducing the non-linearity of inversion. On the other hand, the FWI, a high-precision inversion technology, is used to invert fractures, which helps to finely characterize the fracture structure.

[0047] The technical solution proposed by the present invention is particularly applicable to the hydraulic fracturing method of horizontal well staged fracturing. After each stage of fracturing is completed, the fracturing effect can be fed back, which helps to guide subsequent operations and production decisions, thereby improving the single-well performance and the exploitation ability of unconventional oil and gas reservoirs.

[0048] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for quantitatively evaluating hydraulic fractures in the near-wellbore area, characterized in that: The following steps are involved: The first step is to construct corresponding grids in hydraulic fractures, wellbore and bottom areas, and then form a model discretization based on non-uniform grid technology, and set is the data residual, E(m) is the objective function of TL-FWI, m is the model parameter, and m n The model obtained by the nth iteration, m n+1 is the new model after the n-th model update, μ n is the update step size, i.e., the anisotropic elastic parameter; The second step is to obtain the DAS time-shift response data subset after the first step. First, the component v of the particle along the fiber layout direction is obtained based on the anisotropic elastic wave equation. x , and then the DAS strain rate response is obtained by the derivative of the particle velocity component along the fiber direction Finally, the DAS strain rate response before and after fracturing is calculated respectively. and After subtraction, the DAS time-shift response data subset in the synthetic data is obtained The anisotropic elastic parameters are set as: c 11 、c 13 、c 33 、c 44 , the horizontal and vertical components of the particle velocity are set to: v x 、v z ; In the third step, after the second step, the DAS time-shift response data subset is inverted. First, the DAS time-shift response data subset in the actual data is obtained. Then, the TL-FWI error function is constructed, and the gradient of the objective function is obtained through the gradient method. Finally, the initial model is updated based on the gradient of the objective function until the error of TL-FWI meets a certain threshold, and the development of hydraulic fractures in the near-wellbore area can be obtained. The conclusions obtained after completing the fourth and third steps can be used to quantitatively evaluate the hydraulic fractures in the near-wellbore area.

2. A method for quantitatively evaluating hydraulic fractures in the near-wellbore region according to claim 1, characterized in that: In the first step, the hydraulic fracture area is discretized using a smaller grid, the wellbore area is discretized using a medium grid, and the bottom layer area is discretized using a large grid.

3. A method for quantitatively evaluating hydraulic fractures in the near-wellbore region according to claim 1, characterized in that: By applying a water hammer signal at the wellhead and solving the anisotropic elastic wave equation, the horizontal component data v of the particle velocity along the optical fiber deployment direction in the horizontal well can be obtained. x , then the DAS strain rate response It can be obtained by the following formula Represents the partial derivative along the horizontal direction, that is, the partial derivative along the optical fiber direction. The above formula can be used to obtain the DAS strain rate response from the anisotropic elastic wave equation.

4. A method for quantitatively evaluating hydraulic fractures in the near-wellbore region according to claim 1, characterized in that: In the second step, based on the discretization of the model using a non-uniform grid, the anisotropic elastic wave equation is used to solve the DAS response. The anisotropic elastic wave equation is shown as follows:

5. A method for quantitatively evaluating hydraulic fractures in the near-wellbore region according to claim 1, characterized in that: Through the techniques in the first and second steps, we can obtain the DAS time-shift response data subset dominated by Krauklis waves. On this basis, we can obtain the DAS time-shift response data subset in the actual data in the same way. Based on synthetic data and actual data We can construct the objective function of TL-FWI as shown below: The derivative of the objective function can be obtained through the gradient algorithm And update the model by the following formula:

6. A method for quantitatively evaluating hydraulic fractures in the near-wellbore region according to claim 1, characterized in that: When the error of TL-FWI is less than a certain threshold, the time-shift variation of the hydraulic fracture can be obtained.

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