A method of fracture modeling

Abstract

The present application relates to a kind of crack modeling method, belong to oilfield development technical field.The crack modeling method of the present application, including the following steps:1) utilize the matrix geological grid of work area, in combination with the statistical crack parameter data of work area, with the density body of crack development of work area as constraint, establish the DFN crack model of work area;2) the simulated production curve of the simulated production data of the DFN crack model simulated based on step 1) of work area is compared with actual production curve, correct the crack parameter of DFN crack model, make the fitting rate of simulated production curve and actual production curve reach set value.The crack modeling method of the present application, with actual production curve correction guide crack modeling parameter, improve the accuracy of discrete fracture network (DFN) model modeling, to solve the problem that the model error of existing modeling method is large, and the degree of conformity with production dynamic characteristics is low.

Description

Technical Field

[0001] This invention relates to a fracture modeling method, belonging to the field of oilfield development technology. Background Technology

[0002] For fractured reservoirs, especially low-permeability reservoirs, fracture modeling is an important technical means to characterize reservoir heterogeneity in reservoir research or prediction. Oilfield development practice has proven that accurately establishing fracture models can not only provide a scientific basis for effectively controlling edge water from entering the reservoir through the fracture network, but also effectively improve the accuracy of numerical simulation predictions.

[0003] Fracture research, which began in the 1950s and 60s, has achieved significant results after more than 60 years of development. On the one hand, fractures can serve as migration channels and accumulation spaces for oil and gas, forming fractured reservoirs in formations with highly developed open fractures. On the other hand, the presence of fractures can further enhance reservoir heterogeneity, posing challenges to oil and gas field exploration and development. In particular, during the development of oil (gas) fields with well-developed edge and bottom water, edge and bottom water can enter the reservoir through the fracture network, causing water flooding. Therefore, for fractured reservoirs, it is necessary to establish fracture models to quantitatively describe fracture development during both exploration and development.

[0004] Currently, the commonly used fracture modeling method is the stochastic fracture modeling method. After the fracture model is established, a dual-medium modeling method is generally used to coarse the fracture parameters into the matrix model, treating the fracture parameters as equivalent to reservoir parameters. The entire dual-medium model is then fitted with the production history. Generally, the model runs for a long time, and it only adjusts the permeability parameters shared by the matrix and fractures, without specifically adjusting the fracture parameters. At the same time, due to the characteristics of fractures, such as large size variations and complex spatial distribution, existing fracture modeling methods have always suffered from large model errors and low degree of consistency between the final model and the dynamic characteristics of production, which greatly restricts the development of fractured reservoir research. Summary of the Invention

[0005] The purpose of this invention is to provide a crack modeling method with small modeling errors and a high degree of consistency with production dynamics.

[0006] To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0007] A crack modeling method includes the following steps: 1) Using the geological grid of the work area matrix and combined with the statistical crack parameter data of the work area, a DFN crack model of the work area is established with the crack development density volume of the work area as a constraint; 2) The simulated production curve of the production data simulated by the DFN crack model established in step 1) is compared with the actual production curve, and the crack parameters of the DFN crack model are corrected so that the fitting rate between the simulated production curve and the actual production curve reaches the set value.

[0008] The fracture modeling method of this invention combines dynamic and static methods, using actual production curves to correct and guide fracture modeling parameters, thereby improving the accuracy of discrete fracture network (DFN) modeling. This solves the problems of large model errors and low consistency with production dynamics in existing modeling methods. Since fractures are generally well-developed in low-permeability reservoirs, the fracture modeling method of this invention is particularly suitable for fracture modeling in low-permeability reservoirs with well-developed fractures.

[0009] Furthermore, in step 1), the fracture parameters of the work area include fracture size, dip direction, dip angle, aperture, and permeability. These fracture parameters are obtained through statistical analysis combining core data, field outcrop data, and well logging data.

[0010] It is understandable that the actual production curve is obtained based on historical production data measured from production wells in the work area. Further, in step 2), the method for comparing the simulated production curve and the actual production curve in the work area to correct the fracture parameters of the DFN fracture model includes the following steps:

[0011] i) Obtain production data based on the DFN fracture model simulation and historical production data measured by production wells in the work area, respectively. Compare the simulated production curve based on the simulated production data with the actual production curve based on the historical production data, and obtain the fitting rate between the simulated production curve and the actual production curve, denoted as α.

[0012] ii) When the fitting rate α between the simulated production curve and the actual production curve is ≤ M, adjust the crack development density and then proceed with steps 1) and i) in sequence until the fitting rate α > M; M is 70-80%;

[0013] When the fitting rate α > M, or the fracture development density is adjusted to a fitting rate α > M, based on the fracture development density corresponding to the fitting rate, the fracture aperture and permeability are adjusted, and steps 1) and i) are performed sequentially until the production curve fitting rate reaches the set value; the set value > α. It is understood that the set value can be set according to production needs, with a maximum not exceeding 100%, and generally 95% to 100% is sufficient to meet actual production requirements.

[0014] Since crack development density is a sensitive parameter related to the simulated production curve, it is adjusted first. This shows that the M value is fundamental to the accuracy of the model. For any work area, an M value between 70% and 80% generally meets production requirements; for example, an M value of 75% is acceptable. It can be understood that the fitting rate of this invention = (average value of simulated production curve data points - average value of actual production curve data points) / average value of actual production curve data points × 100%, where the simulated and actual production curve data points are data points from the same time period.

[0015] Further, in step 2), the simulated production data is obtained using a method comprising the following steps: based on the DFN fracture model, the finite element method is used to simulate the fluid flow process in the fracture at time steps, thereby obtaining the simulated production data. For example, the Fracman software can be used for rapid production capacity evaluation module to accurately simulate the fluid flow process in the fracture using the finite element method at time steps. The advantage of using this method to obtain simulated production data compared to other methods is that other numerical simulation techniques usually require the establishment of a dual-medium model and a fluid model for numerical simulation, and the simultaneous adjustment of reservoir parameters and fracture parameters of the dual media, and the simulation process is time-consuming; this invention provides given values ​​for various parameters of the reservoir, uses the fracture model as a basis, uses Fracman software to quickly simulate fluid movement, and uses history fitting to specifically adjust fracture parameters, which can greatly save simulation running time and establish a fracture model that meets production needs.

[0016] Furthermore, in step 1), the fracture development density volume of the work area is established based on the functional relationship between the fracture development density and the main controlling factors of fracture development within the work area. The main controlling factors of fracture development are determined by establishing a functional relationship between the fracture development density of a single well in the work area and different seismic attributes, and taking the seismic attribute with the highest correlation as the main controlling factor of fracture development.

[0017] Furthermore, in step 1), the geological grid of the work area matrix is ​​a structural model grid of the work area. The structural model grid of the work area can be established using Petrel software. Attached Figure Description

[0018] Figure 1 This is a graph showing the relationship between crack development density and seismic coherence attribute function in the embodiment;

[0019] Figure 2 This is a diagram illustrating the fitting process between the simulated production curve and the actual production curve in the embodiment.

[0020] Figure 3 This is a comparison chart showing the average daily production of oil wells deployed under the guidance of the model established in the example, and oil wells deployed during the same period without the guidance of the model. Detailed Implementation

[0021] The technical solution of the present invention will be further described below with reference to specific embodiments.

[0022] Example

[0023] The crack modeling method in this embodiment is based on a permeability of less than 50×10⁻⁶. -3 μm 2 Taking well A in a certain work area with well fractures as an example, the following steps are included:

[0024] 1) By summarizing and analyzing previous geological understanding, data on well location, well trajectory, imaging logging, field observation, seismic attributes, and laboratory fracture analysis of well area A in a certain work area were collected. This allowed for the determination of fracture size, dip direction, dip angle, aperture, permeability, and fracture density per meter in a single well. Furthermore, various test data, wellbore parameters, fluid parameters, and production dynamics data were prepared to provide fundamental parameters for rapid productivity evaluation.

[0025] 2) By establishing a functional relationship between the fracture development density of a single well in the work area and the main controlling factors of fracture development, a fracture development density volume is established based on the main controlling factors of fracture development. Specifically, the method for establishing the fracture development volume includes the following steps:

[0026] i) The coherence volume, ant volume, curvature and other attribute data volumes of seismic interpretation can be used as the basis for controlling fracture development. Taking advantage of the high accuracy of imaging logging, the relationship between fracture development density of a single well in the work area and various seismic attribute functions can be established through well-seismic integration. Based on the correlation coefficient, the seismic coherence volume with the highest correlation can be determined as the basis for controlling fracture development density.

[0027] ii) Based on the relationship between crack development density and seismic coherence attribute function, establish a crack development density volume for the work area; the relationship between crack development density and seismic coherence attribute function is shown in [reference needed]. Figure 1 .

[0028] 3) Establish a DFN fracture model using the geological grid of the work area; specifically, establishing the DFN fracture model includes the following steps:

[0029] i) The work area structural model grid was established using Petrel software as the matrix geological grid. The Petrel software used is a three-dimensional visualization modeling software based on the Windows platform that is widely used at home and abroad. It integrates structural modeling, lithofacies modeling, reservoir attribute modeling, fracture modeling and reservoir numerical simulation, and is suitable for various reservoir types.

[0030] ii) Using the basic data of the crack model in step 1, the size, dip, angle, aperture, and permeability of the cracks in the work area are statistically analyzed using the spatial clustering method.

[0031] iii) Using the DFN fracture network deterministic modeling method, combined with the statistical results of fracture parameters in the work area, and constrained by the fracture development density volume in the work area, a DFN fracture model is generated in the matrix geological grid of the work area.

[0032] 4) Compare the simulated production curves of the production data simulated by the DFN crack model established in step 1) with the actual production curves, and correct the crack parameters of the DFN crack model to ensure that the fitting rate between the simulated and actual production curves reaches the set value, thus establishing an accurate DFN crack model. The specific steps are as follows:

[0033] i) Based on the DFN fracture model established in step 3), and combined with the wellbore parameters collected in step 1) as well as parameters such as reservoir fluids, reservoir properties (porosity, permeability), and effective reservoir thickness, the Fracman software is used to perform a rapid production evaluation module to accurately simulate the fluid flow process in the fractures according to the finite element method and time step, thereby obtaining the production data simulated by the fracture model.

[0034] ii) Obtain production data simulated based on the DFN fracture model and historical production data measured from production wells in the work area, respectively, and compare the fitting rate between the simulated production curve based on the simulated production data and the actual production curve based on the historical production data; the fitting rate here is calculated as (average value of simulated production curve data points - average value of actual production curve data points) / average value of actual production curve data points × 100%. The fitting rate between the simulated production curve and the actual production curve based on the newly established DFN fracture model is 65% < 75%, and the fracture development density needs to be adjusted.

[0035] iii) Then increase the fracture development density to 1.1 times, and repeat steps 3)iii), 4)i), and 4)ii). The resulting simulated production curve has a fitting rate of 78% (>75%) to the actual production curve. Based on the fracture development density at this fitting rate, adjust the fracture aperture and permeability, and repeat steps 3)iii) and 4)i) until the fitting rate reaches 100%. The corresponding fracture model at this point is the final correct DFN fracture model. The fitting process between the simulated and actual production curves is as follows: Figure 2 As shown.

[0036] The DFN fracture model established in this embodiment is more accurate. Under the guidance of this model, when the permeability is less than 50 × 10⁻⁶, the accuracy is higher. -3 μm 2 In a certain work area with well-developed fractures, three oil wells were deployed. Compared to two wells deployed during the same period without model guidance, production indicators were compared. The average daily production of the wells deployed using the model was significantly higher than that of the wells deployed without model guidance (e.g., ...). Figure 3 (As shown).

Claims

1. A crack modeling method, characterized in that: Includes the following steps: 1) Using the matrix geological grid of the work area and combined with the statistical fracture parameter data of the work area, a DFN fracture model of the work area is established with the fracture development density volume of the work area as a constraint. The fracture development density volume of the work area is established based on the functional relationship between the fracture development density and the main controlling factors of fracture development in the work area. The main controlling factors of fracture development are determined by establishing the functional relationship between the fracture development density of a single well in the work area and different seismic attributes, and taking the seismic attribute with the highest correlation as the main controlling factor of fracture development. 2) Compare the simulated production curves of the production data simulated by the DFN crack model established in step 1) with the actual production curves, and correct the crack parameters of the DFN crack model so that the fitting rate between the simulated and actual production curves reaches the set value. Specifically, this includes: i) Obtain production data based on the DFN fracture model simulation and historical production data measured by production wells in the work area, respectively. Compare the simulated production curve based on the simulated production data with the actual production curve based on the historical production data, and obtain the fitting rate between the simulated production curve and the actual production curve, denoted as α. ii) When the fitting rate α between the simulated production curve and the actual production curve is ≤ M, adjust the crack development density and then proceed with steps 1) and i) sequentially until the fitting rate α > M; M is 70~80%; When the fitting rate α > M or the fracture development density is adjusted to the fitting rate α > M, based on the fracture development density corresponding to the fitting rate, the fracture aperture and permeability are adjusted and then steps 1) and i) are performed sequentially until the production curve fitting rate reaches the set value; the set value > α, and the set value is 95~100%.

2. The crack modeling method according to claim 1, characterized in that: In step 1), the crack parameters of the work area include crack size, dip direction, dip angle, aperture and permeability.

3. The crack modeling method according to claim 1, characterized in that: In step 2), M is 75%.

4. The crack modeling method according to claim 1, characterized in that: In step 2), the simulated production data is obtained by a method including the following steps: based on the DFN crack model, the finite element method is used to simulate the flow process of fluid in the crack according to the time step, and then the simulated production data is obtained.

5. The crack modeling method according to claim 1, characterized in that: In step 1), a crack development density body for the work area is established based on the relationship between crack development density and seismic coherence attribute function.

6. The crack modeling method according to claim 1, characterized in that: In step 1), the geological grid of the work area matrix is ​​the structural model grid of the work area.

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