Carbonate rock acidification effect evaluation method and device, storage medium and processor

Abstract

The invention relates to the field of oil and gas field development, and discloses a carbonate rock acidification effect evaluation method and device, a storage medium and a processor, and the method comprises the steps: obtaining a first image of a reservoir acidification process, and carrying out the binary segmentation processing of the first image, and obtaining a binary image comprising a reservoir skeleton region and a fracture-cavity region; calculating the porosity of the reservoir based on the number of pixels in the fracture-cavity area in the binarized image; and based on the binarized image, calculating the fractal dimension of the fracture-cavity area in the binarized image; and evaluating the acidification effect of the reservoir according to the porosity and the fractal dimension. The porosity of the reservoir and the fractal dimension of the fracture-cavity area can reflect the change of the geometrical morphology and the spatial structure of the reservoir in the acidification process, and the change of the geometrical morphology and the spatial structure of the reservoir determines the seepage capacity of the reservoir. Therefore, the acidification effect of the reservoir can be accurately evaluated based on the porosity of the reservoir and the fractal dimension of the fracture-cavity area.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development, and particularly relates to a method for evaluating carbonate acidification effect, a device for evaluating carbonate acidification effect, a machine-readable storage medium, and a processor. Background Art

[0002] Carbonate reservoirs are rich in oil and gas and have a wide distribution range, and are one of the key targets for oil and gas exploration and development. In practical applications, acidification is a key means for efficient development of carbonate reservoirs. By evaluating the acidification effect of the reservoir, it is possible to provide guidance for optimizing the acidification process.

[0003] However, affected by the comprehensive effects of multi-stage hydrocarbon accumulation, tectonic movement, karst superimposed transformation, etc., fractures and caves are generally developed in carbonate reservoirs, and the reservoir permeability space has extremely strong heterogeneity and multi-scale characteristics in three-dimensional space, and the spatial structure is very complex. Therefore, during the acidification process, the flow law and physicochemical action law of acid fluid in the reservoir fracture-cave space are relatively complex, and there are many influencing factors, making it so that there is currently no scheme that can accurately evaluate the acidification effect of the reservoir, thus seriously restricting the efficient development of carbonate oil and gas reservoirs. Summary of the Invention

[0004] The purpose of the present invention is to overcome the problem that there is a lack of a scheme in the prior art that can accurately evaluate the acidification effect of the reservoir, and to provide a method for evaluating carbonate acidification effect, a device for evaluating carbonate acidification effect, a machine-readable storage medium, and a processor.

[0005] To achieve the above purpose, the first aspect of the present invention provides a method for evaluating carbonate acidification effect, the method comprising:

[0006] Obtain a first image of the reservoir acidification process, perform binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-cave region;

[0007] Based on the number of pixels in the fracture-cave region in the binary image, calculate the porosity of the reservoir; and, based on the binary image, calculate the fractal dimension of the fracture-cave region in the binary image;

[0008] Evaluate the acidification effect of the reservoir according to the porosity and the fractal dimension.

[0009] In an embodiment of the present application, the method further comprises:

[0010] Perform reservoir seepage simulation based on the binary image, calculate the equivalent permeability of the reservoir according to the simulation result, and calculate the skin factor of the reservoir according to the equivalent permeability;

[0011] Evaluate the acidification effect of the reservoir according to the porosity, the fractal dimension, the equivalent permeability and the skin factor.

[0012] In the embodiment of the present application, the obtaining the first image of the reservoir acidification process includes: obtaining a plurality of first images of the reservoir acidification process in real time.

[0013] In the embodiment of the present application, the calculating the porosity of the reservoir based on the number of pixels in the fracture-vug area of the binary image is carried out based on the following formula:

[0014]

[0015] where φ is the porosity of the reservoir; v φ is the number of pixels in the fracture-vug area; v is the total number of pixels in the first image.

[0016] In the embodiment of the present application, the calculating the fractal dimension of the fracture-vug area in the binary image based on the binary image includes:

[0017] Cover the binary image with a plurality of square boxes with the same side length, record the number of boxes covering the fracture-vug area, and calculate the fractal dimension of the fracture-vug area in the binary image based on the number of boxes covering the fracture-vug area and the side length of the square box.

[0018] In the embodiment of the present application, the calculating the fractal dimension of the fracture-vug area in the binary image based on the number of boxes covering the fracture-vug area and the side length of the square box is carried out based on the following formula:

[0019]

[0020] where D is the fractal dimension of the fracture-vug area; r is the side length of the square box; N(r) is the number of boxes covering the fracture-vug area.

[0021] In the embodiment of the present application, the reservoir seepage simulation is carried out based on the binary image, the equivalent permeability of the reservoir is calculated according to the simulation result, and the skin factor of the reservoir is calculated according to the equivalent permeability, respectively based on the following formulas:

[0022]

[0023]

[0024] where K is the equivalent permeability of the reservoir, in units of m 2 ; q is the flow rate of the acid solution, in units of m 3 / s; μ is the viscosity of the acid solution, with the unit of Pa·s; L is the length of the reservoir corresponding to the binary image, with the unit of m; A is the cross-sectional area of the reservoir corresponding to the binary image, with the unit of m 2 ; P1 is the inlet pressure of the reservoir, with the unit of Pa; P2 is the outlet pressure of the reservoir, with the unit of Pa;

[0025] S is the skin factor of the reservoir; K0 is the initial equivalent permeability of the reservoir before acidification, with the unit of m 2 ; r s is the acidification radius, with the unit of m; r w is the wellbore radius, with the unit of m.

[0026] The second aspect of the present application provides a carbonate rock acidification effect evaluation device, including:

[0027] An image processing module, configured to obtain a first image during the acidification process of the reservoir, perform binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton area and a fracture-vug area;

[0028] A calculation module, configured to calculate the porosity of the reservoir based on the number of pixels in the fracture-vug area of the binary image; and calculate the fractal dimension of the fracture-vug area in the binary image based on the binary image;

[0029] An evaluation module, configured to evaluate the acidification effect of the reservoir according to the porosity and the fractal dimension.

[0030] The third aspect of the present application provides a processor configured to execute the above-mentioned carbonate rock acidification effect evaluation method.

[0031] The fourth aspect of the present application provides a machine-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the processor is configured to execute the above-mentioned carbonate rock acidification effect evaluation method.

[0032] Through the above technical solutions, the technical solutions include: obtaining a first image during the acidification process of the reservoir, performing binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton area and a fracture-vug area; calculating the porosity of the reservoir based on the number of pixels in the fracture-vug area of the binary image; and calculating the fractal dimension of the fracture-vug area in the binary image based on the binary image; evaluating the acidification effect of the reservoir according to the porosity and the fractal dimension. Since the porosity of the reservoir and the fractal dimension of the fracture-vug area can reflect the changes in the geometric shape and spatial structure of the reservoir during the acidification process, and the changes in the geometric shape and spatial structure of the reservoir determine the seepage capacity of the reservoir and affect the reservoir production, the acidification effect of the reservoir can be accurately evaluated based on the porosity of the reservoir and the fractal dimension of the fracture-vug area.

[0033] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the following specific implementation, they are used to explain the embodiments of the present application, but do not constitute a limitation to the embodiments of the present application. In the drawings:

[0035] Figure 1 Schematically shows a schematic flowchart of a method for evaluating the acidification effect of carbonate rocks according to an embodiment of the present application;

[0036] Figure 2-1 and Figure 2-2 Schematically shows a schematic diagram of covering a binary image with a square box according to an embodiment of the present application;

[0037] Figure 3 Schematically shows a schematic flowchart of another method for evaluating the acidification effect of carbonate rocks according to an embodiment of the present application;

[0038] Figure 4 Schematically shows a schematic diagram of reservoir seepage simulation according to an embodiment of the present application;

[0039] Figure 5 Schematically shows a structural block diagram of a device for evaluating the acidification effect of carbonate rocks according to an embodiment of the present application;

[0040] Figure 6 Schematically shows an internal structure diagram of a computer device according to an embodiment of the present application.

[0041] DESCRIPTION OF THE REFERENCE NUMERALS

[0042] 210 - Image processing module; 220 - Calculation module; 230 - Evaluation module; A01 - Processor; A02 - Network interface; A03 - Internal memory; A04 - Display screen; A05 - Input device; A06 - Non-volatile storage medium; B01 - Operating system; B02 - Computer program. SPECIFIC IMPLEMENTATION

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. It should be understood that the specific implementation manners described herein are only used to illustrate and explain the embodiments of this application, and are not used to limit the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope protected by this application.

[0044] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of this application, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0045] In addition, if there are descriptions such as "first" and "second" involved in the embodiments of this application, the descriptions of "first", "second", etc. are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0046] As described in the background art, acidification is a key means to achieve efficient development of carbonate reservoirs. During the acidification construction process, the acid fluid enters the fractures and karst caves and undergoes dissolution. After acidification, the geometric shape and spatial structure of the fractures and karst caves directly determine the acidification effect of the reservoir, and the acidification effect further affects the reservoir production. By evaluating the acidification effect of the reservoir, it can provide guidance for optimizing the acidification construction process. Currently, when evaluating the acidification effect of fractured-vuggy carbonate reservoirs, generally, well test interpretation means are used to invert the fracture and karst cave information. However, affected by the comprehensive effects of multi-stage hydrocarbon accumulation, tectonic movements, and karst superimposed transformation, etc., fractures and karst caves are generally developed in carbonate reservoirs, and the reservoir-permeability space structure is very complex, resulting in relatively complex flow laws and physicochemical action laws of the acid fluid in the fracture-vuggy space of the reservoir. This makes the fracture and karst cave information obtained by the above-mentioned inversion using well test interpretation means have great uncertainty. It can be seen that there is currently no scheme that can accurately evaluate the acidification effect of the reservoir, which severely restricts the efficient development of carbonate oil and gas reservoirs.

[0047] In view of this, in one embodiment of this application, a method for evaluating the acidification effect of carbonate rocks is provided, asFigure 1 As shown, the method for evaluating the acidification effect of carbonate rocks may include the following steps:

[0048] Step 101: Obtain a first image of the reservoir acidification process, and perform binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-vug region.

[0049] Among them, the reservoir may be a fracture-vug type carbonate rock reservoir. The first image may be obtained at any time during the reservoir acidification.

[0050] In practical applications, the first image of the reservoir acidification process can be obtained by means of core acidification experiments or numerical simulations. When numerically simulating the reservoir acidification process, specifically, numerical simulation software such as COMSOL and TOUGH or self-programming can be used to simulate the reservoir acidification process.

[0051] In step 101, when performing binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-vug region, in specific implementation, the first image can be binary segmented by selecting an appropriate threshold into a reservoir skeleton region and a fracture-vug region; among them, the fracture-vug region is the fracture-cave region.

[0052] To further improve the effect after binary segmentation processing, that is, to accurately segment the reservoir skeleton region and the fracture-vug region, after obtaining the first image of the reservoir acidification process, the first image can be square cropped to extract an image representing the unit cell size from the first image. Then, the median filtering method is used to denoise the image to obtain a denoised image. Furthermore, when performing binary segmentation processing subsequently, specifically, the denoised image is binary segmented to obtain a binary image including a reservoir skeleton region and a fracture-vug region.

[0053] Step 102, calculate the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image; and calculate the fractal dimension of the fracture-vug region in the binary image based on the binary image.

[0054] In the embodiments of the present application, calculating the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image may specifically include: extracting the image of the fracture-vug region from the binary image and counting the number of pixels in the image of the fracture-vug region; then, dividing the number of pixels in the image of the fracture-vug region by the total number of pixels in the first image to obtain the porosity of the reservoir. It can be understood that since the first image is obtained at a certain moment during the reservoir acidification, this porosity is the porosity of the reservoir during the acidification process.

[0055] Specifically, based on the number of pixels in the fracture-vug region of the binary image, the porosity of the reservoir can be calculated according to the following formula (1):

[0056]

[0057] where φ is the porosity of the reservoir, i.e., the porosity of the reservoir during the acidification process; v φ is the number of pixels in the fracture-vug region, i.e., the number of pixels in the image of the fracture-vug region; v is the total number of pixels in the first image.

[0058] In the embodiments of the present application, based on the binary image, the fractal dimension of the fracture-vug region in the binary image is calculated. Specifically, in implementation, it may include: using the box-counting method, covering the binary image with a plurality of square boxes of the same side length, recording the number of boxes covering the fracture-vug region, and calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box.

[0059] Among them, covering the binary image with a plurality of square boxes of the same side length may specifically refer to completely covering the binary image with a plurality of square boxes of the same side length. Such a complete coverage can be regarded as one coverage process. In practical applications, the above coverage process can be repeatedly executed, that is, the binary image is subjected to multiple coverage processes. In one coverage process, the binary image is completely covered with a plurality of square boxes of the same side length. In different coverage processes, the side lengths of the square boxes used are different. As Figure 2-1 and Figure 2-2 shown, they are respectively schematic diagrams of two coverage processes. In these two coverage processes, in each coverage process, the binary image is completely covered with a plurality of square boxes of the same side length, and the side lengths of the square boxes used in the two coverage processes are different.

[0060] Furthermore, recording the number of boxes covering the fracture-vug region may include: recording the number of boxes covering the fracture-vug region after each coverage process. Then, calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box may include: calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box corresponding to each coverage process. Based on this, specifically, calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box can be carried out according to the following formula (2):

[0061]

[0062] In the above formula (2), D is the fractal dimension of the fracture-vug area; r is the side length of the square box; N(r) is the number of boxes covering the fracture-vug area. Among them, r can specifically refer to the number of pixels covered by the side length of the square box; furthermore, based on the number of boxes covering the fracture-vug area and the side length of the square box, the fractal dimension of the fracture-vug area in the binary image is calculated, which can be understood as: based on the number of boxes covering the fracture-vug area and the number of pixels covered by the side length of the square box, the fractal dimension of the fracture-vug area in the binary image is calculated. For example, if the number of pixels covered by a square box is 10×10, then the number of pixels covered by its side length is 10, and r = 10 is substituted into formula (2) for calculation.

[0063] The above formula can be understood as that for each covering process, the corresponding r and N(r) can be obtained, and the point (lnr, lnN(r)) corresponding to this covering process is plotted in the coordinate system with lnr as the abscissa and lnN(r) as the ordinate. Correspondingly, the points (lnr, lnN(r)) corresponding to each covering process are plotted in the same coordinate system in the same way. Then, linear fitting is performed on the points (lnr, lnN(r)) corresponding to each covering process to obtain a fitting line, and the fractal dimension of the fracture-vug area is the opposite of the slope of the fitting line.

[0064] Step 103, evaluate the acidification effect of the reservoir according to the porosity and the fractal dimension.

[0065] In the embodiments of the present application, the porosity of the reservoir can quantitatively characterize the structure of the reservoir. Generally speaking, the larger the porosity of the reservoir, the higher the development degree and the wider the distribution range of fractures and vugs in the reservoir, and the better the acidification transformation effect. The fractal dimension of the fracture-vug area can be used to characterize the complexity of fractures and vugs and can quantitatively characterize the structure of the reservoir. Generally speaking, the larger the fractal dimension of the fracture-vug area, the higher the development degree and the wider the distribution range of fractures and vugs in the reservoir, and the better the acidification transformation effect. That is, the porosity and the fractal dimension can characterize the geometric shape and spatial structure of the reservoir during the acidification process, and can further reflect the changes in the geometric shape and spatial structure of the reservoir during the acidification process.

[0066] In practical applications, the initial image corresponding to the reservoir before acidification can also be obtained. Referring to the processing method and calculation method of the first image during the acidification process of the reservoir, the initial image is processed, and the porosity of the reservoir before acidification and the fractal dimension of the fracture-vug area before acidification are calculated based on the initial image. Then, the porosity of the reservoir during the acidification process is compared with the porosity of the reservoir before acidification, and the fractal dimension of the fracture-vug area during the acidification process is compared with the fractal dimension of the fracture-vug area before acidification to reflect the changes in the geometric shape and spatial structure of the reservoir during the acidification process.

[0067] It can be understood that the carbonate rock acidification effect evaluation method provided by the embodiments of the present application includes: obtaining a first image of the reservoir acidification process, performing binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-vug region; calculating the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image; and calculating the fractal dimension of the fracture-vug region in the binary image based on the binary image; evaluating the acidification effect of the reservoir according to the porosity and the fractal dimension. Since the porosity of the reservoir and the fractal dimension of the fracture-vug region can reflect the changes in the geometric shape and spatial structure of the reservoir during the acidification process, and the changes in the geometric shape and spatial structure of the reservoir determine the seepage capacity of the reservoir and affect the reservoir production, the acidification effect of the reservoir can be accurately evaluated based on the porosity of the reservoir and the fractal dimension of the fracture-vug region.

[0068] On the other hand, since both the porosity of the reservoir and the fractal dimension of the fracture-vug region have definite numerical values, during the evaluation of the acidification effect, the acidification effect can be quantitatively evaluated based on the porosity of the reservoir and the fractal dimension of the fracture-vug region. For example, weights can be set for the porosity of the reservoir and the fractal dimension of the fracture-vug region respectively, and the score of the acidification effect is set as = porosity of the reservoir × weight + fractal dimension of the fracture-vug region × weight. It should be understood that this example is only a specific way of quantitatively evaluating the acidification effect and does not represent an improper limitation of the solution of the present application. In practical applications, other scoring rules can also be formulated based on the porosity of the reservoir and the fractal dimension of the fracture-vug region according to actual needs.

[0069] In the existing reservoir acidification effect evaluation methods, it is difficult to quantitatively evaluate the acidification effect. However, based on the carbonate rock acidification effect evaluation method provided by the embodiments of the present application, by characterizing the geometric shape and spatial structure of the reservoir during the acidification process based on the porosity of the reservoir and the fractal dimension of the fracture-vug region with definite numerical values, the acidification effect of the reservoir can be quantitatively evaluated, and thus more refined guidance can be provided for the acidification construction process.

[0070] To more comprehensively and accurately evaluate the acidification effect of the reservoir, as Figure 3 shown, the carbonate rock acidification effect evaluation method provided by the embodiments of the present application further includes step 104 of performing reservoir seepage simulation based on the binary image, calculating the equivalent permeability of the reservoir according to the simulation result, and calculating the skin factor of the reservoir according to the equivalent permeability. Then step 103 includes step 1031 of evaluating the acidification effect of the reservoir according to the porosity, the fractal dimension, the equivalent permeability, and the skin factor.

[0071] In the embodiments of the present application, reservoir seepage simulation is performed based on the binary image, and the equivalent permeability of the reservoir is calculated according to the simulation results. In specific implementation, the finite element method can be used to perform reservoir seepage simulation on the binary image.

[0072] As Figure 4 shown, Figure 4 in which M represents the binary image, L represents the fracture, and R represents the karst cave. When performing reservoir seepage simulation, boundary conditions can be set for the binary image, with the left inlet pressure set to P1, the right outlet pressure set to P2, and the upper and lower boundaries being closed boundaries. Then, triangular meshing is performed, and the permeabilities of the skeleton, fracture, and karst cave are set to K1, K2, and K3 (K1 < K2 < K3) respectively. After simulation, the reservoir pressure field and velocity field can be obtained. That is, after reservoir seepage simulation, the left inlet pressure of P1, the right outlet pressure of P2, and the acid fluid flow rate can be obtained.

[0073] After obtaining the simulation results, the Darcy formula can be used to calculate the equivalent permeability of the reservoir. Specifically, for performing reservoir seepage simulation based on the binary image and calculating the equivalent permeability of the reservoir according to the simulation results, it can be carried out based on the following formula (3):

[0074]

[0075] where K is the equivalent permeability of the reservoir, that is, the equivalent permeability of the reservoir structure corresponding to the binary image, with the unit of m 2 ; q is the flow rate of the acid fluid, with the unit of m 3 / s; μ is the viscosity of the acid fluid, with the unit of Pa·s; L is the length of the reservoir corresponding to the binary image, that is, the length of the reservoir corresponding to the binary image along the acid fluid flow direction (from the left inlet to the right outlet), with the unit of m; A is the cross-sectional area of the reservoir corresponding to the binary image, with the unit of m 2 ; P1 is the inlet pressure of the reservoir, with the unit of Pa; P2 is the outlet pressure of the reservoir, with the unit of Pa.

[0076] In the embodiments of the present application, for calculating the skin factor of the reservoir according to the equivalent permeability, it can be carried out based on the following formula (4):

[0077]

[0078] where S is the skin factor of the reservoir; K0 is the initial equivalent permeability of the reservoir before acidification, with the unit of m 2 ; r s is the acidification radius, with the unit of m; r w is the wellbore radius, with the unit of m. Among them, the acidification radius r sIt can be calculated according to the expansion range of wormholes in the binarized image, and the wellbore radius is generally on the order of 0.1 meter.

[0079] In the prior art, the skin factor is usually obtained indirectly by well test interpretation methods. Some ideal assumptions are involved in the obtaining process, making the obtained skin factor reflect the total skin effect caused by various factors near the wellbore, and it is difficult to evaluate the acidification effect finely and accurately. In the embodiments of the present application, the evolution characteristics of reservoir permeability, such as acidification radius, etc., are obtained based on the expansion range of acid-etched wormholes in the image, and then the skin factor calculated by the Hawkins formula can be used to evaluate the reservoir acidification effect more directly and accurately.

[0080] In the embodiments of the present application, the equivalent permeability of the reservoir can quantitatively characterize the seepage capacity of the reservoir. Generally speaking, the greater the equivalent permeability of the reservoir, the better the seepage capacity of the reservoir and the better the acidification transformation effect. The skin factor of the reservoir can be used to quantitatively characterize the nature and severity of the skin effect of the reservoir, and the acidification transformation effect of the reservoir can be evaluated through the skin factor. When the skin factor is less than 0, it indicates that the acidification stimulation measures are effective. The greater the absolute value of the skin factor, the better the acidification transformation effect and the better the stimulation effect.

[0081] It can be understood that by adopting the above scheme, by further calculating the equivalent permeability and skin factor of the reservoir, and based on the porosity, fractal dimension, equivalent permeability and skin factor of the reservoir, the acidification effect of the reservoir is evaluated, so that the acidification effect of the reservoir can be evaluated from both the structure and physical properties of the reservoir, and thus the evaluation is more comprehensive and accurate. Among them, the porosity and fractal dimension of the reservoir can evaluate the acidification effect from the structure aspect of the reservoir. The porosity and fractal dimension of the reservoir are quantitative characterizations of the reservoir structure. The larger the porosity and fractal dimension, the higher the development degree and the wider the distribution range of fractures and karst caves in the reservoir. The equivalent permeability and skin factor of the reservoir can evaluate the acidification effect from the physical property aspect of the reservoir. The equivalent permeability and skin factor of the reservoir are quantitative characterizations of the reservoir physical properties. The greater the equivalent permeability and the greater the absolute value of the skin factor, the better the acidification transformation effect and the more conducive to the production of oil and gas after the transformation.

[0082] Correspondingly, since both the equivalent permeability and skin factor of the reservoir have definite numerical values, when evaluating the acidification effect, a more refined quantitative evaluation of the acidification effect can be carried out based on the porosity, fractal dimension, equivalent permeability and skin factor. The specific scoring rules for the quantitative evaluation can be formulated according to actual needs and will not be elaborated here.

[0083] In the prior art, when evaluating the acidification effect of fractured-vuggy carbonate reservoirs, generally, well test interpretation means are used to invert fracture and cave information. This method is relatively complex and time-consuming, and it is difficult to evaluate the acidification effect in real time. In the embodiments of the present application, when obtaining the first image of the reservoir acidification process in step 101, the first image of the reservoir acidification process can be obtained in real time. Furthermore, the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir during the acidification process can be obtained in real time, so that the acidification effect can be evaluated in real time.

[0084] In order to further effectively guide and optimize the acidification construction process, in one implementation, step 101 of obtaining the first image of the reservoir acidification process may include: obtaining multiple first images of the reservoir acidification process in real time. Furthermore, the carbonate rock acidification effect evaluation method provided by the embodiments of the present application can be understood as: obtaining multiple first images of the reservoir acidification process in real time, and each first image corresponds to a different moment; then, referring to the above solution, each first image can be processed and calculated, and furthermore, for each first image, the porosity of the corresponding reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir can be obtained.

[0085] That is, through the above method, the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir at each moment of the acidification process can be obtained. Furthermore, as the acidification process progresses, the dynamic changes of the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir can be obtained. Based on the dynamic changes of the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir, the changes and trends of the reservoir structure and physical properties can be obtained, so that the acidification construction process can be effectively guided and optimized.

[0086] In specific implementation, the acidification construction parameters such as acid type, concentration, injection rate, etc. can be adjusted in real time according to the dynamic changes of the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir, so that the porosity of the reservoir, the fractal dimension of the fracture-vug area, the equivalent permeability of the reservoir, and the skin factor of the reservoir change to a larger value and continue to change, and furthermore, the reservoir structure and physical properties change to a trend more favorable for production increase, so as to realize the guidance and optimization of the acidification construction process.

[0087] Based on the same inventive concept, as Figure 5 shown, Figure 5The structural block diagram of a carbonate rock acidification effect evaluation device according to an embodiment of the present application is schematically shown. In one embodiment, a carbonate rock acidification effect evaluation device 200 is provided, including an image processing module 210, a calculation module 220, and an evaluation module 230, where:

[0088] The image processing module 210 is configured to obtain a first image of the reservoir acidification process, perform binary segmentation processing on the first image, and obtain a binary image including a reservoir skeleton region and a fracture-vug region;

[0089] The calculation module 220 is configured to calculate the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image; and calculate the fractal dimension of the fracture-vug region in the binary image based on the binary image;

[0090] The evaluation module 230 is configured to evaluate the acidification effect of the reservoir according to the porosity and the fractal dimension.

[0091] It can be understood that by using the carbonate rock acidification effect evaluation device 200 provided in the embodiment of the present application, since the porosity of the reservoir and the fractal dimension of the fracture-vug region can reflect the changes in the geometric shape and spatial structure of the reservoir during the acidification process, and the changes in the geometric shape and spatial structure of the reservoir determine the seepage capacity of the reservoir and affect the reservoir production, the acidification effect of the reservoir can be accurately evaluated based on the porosity of the reservoir and the fractal dimension of the fracture-vug region.

[0092] In one implementation manner, the calculation module 220 is further configured to perform reservoir seepage simulation based on the binary image, calculate the equivalent permeability of the reservoir according to the simulation result, and calculate the skin factor of the reservoir according to the equivalent permeability. Then the evaluation module is configured to evaluate the acidification effect of the reservoir according to the porosity, the fractal dimension, the equivalent permeability, and the skin factor.

[0093] In one implementation manner, the image processing module 210 is configured to obtain multiple first images of the reservoir acidification process in real time.

[0094] In one implementation manner, the calculation module 220 is configured to calculate the porosity of the reservoir based on the following formula:

[0095]

[0096] where φ is the porosity of the reservoir; v φ is the number of pixels in the fracture-vug region; v is the total number of pixels in the first image

[0097] In one embodiment, the calculation module 220 is configured to cover the binarized image with a plurality of square boxes having the same side length, record the number of boxes covering the fracture-vug region, and calculate the fractal dimension of the fracture-vug region in the binarized image based on the number of boxes covering the fracture-vug region and the side length of the square box.

[0098] In one embodiment, the calculation module 220 is configured to calculate the fractal dimension of the fracture-vug region in the binarized image based on the following formula:

[0099]

[0100] where D is the fractal dimension of the fracture-vug region; r is the side length of the square box; and N(r) is the number of boxes covering the fracture-vug region.

[0101] In one embodiment, the calculation module 220 is configured to calculate the equivalent permeability of the reservoir based on the following formula:

[0102]

[0103] where K is the equivalent permeability of the reservoir, in m 2 ; q is the flow rate of the acid solution, in m 3 / s; μ is the viscosity of the acid solution, in Pa·s; L is the length of the reservoir corresponding to the binarized image, in m; A is the cross-sectional area of the reservoir corresponding to the binarized image, in m 2 ; P1 is the inlet pressure of the reservoir, in Pa; P2 is the outlet pressure of the reservoir, in Pa.

[0104] In one embodiment, the calculation module 220 is configured to calculate the skin factor of the reservoir based on the following formula:

[0105]

[0106] where S is the skin factor of the reservoir; K0 is the initial equivalent permeability of the reservoir before acidification, in m 2 ; r s is the acidification radius, in m; r w is the wellbore radius, in m.

[0107] The carbonate rock acidification effect evaluation device 200 includes a processor and a memory. The above image processing module 210, calculation module 220, and evaluation module 230 can all be stored in the memory as program units and implemented by the processor executing the above program modules stored in the memory to achieve corresponding functions.

[0108] The processor contains a kernel, which retrieves the corresponding program units from the memory. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash RAM. The memory includes at least one memory chip.

[0109] An embodiment of the present application provides a machine-readable storage medium with a program stored thereon. When the program is executed by a processor, it implements the above-mentioned method for evaluating the acidification effect of carbonate rocks.

[0110] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor A01, it implements a method for evaluating the acidification effect of carbonate rocks. The display screen A04 of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device A05 of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0111] Those skilled in the art can understand that Figure 6 the structure shown in

[0112] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different component layout. Figure 6 In one embodiment, the device for evaluating the acidification effect of carbonate rocks provided by the present application can be implemented in the form of a computer program, and the computer program can run on a computer device as Figure 5The image processing module 210, calculation module 220, and evaluation module 230 shown. The computer program composed of each program module enables the processor to execute the steps in the carbonate rock acidification effect evaluation method of each embodiment of the present application described in this specification.

[0113] Figure 6 The computer device shown can execute the method through the image processing module 210, calculation module 220, and evaluation module 230 in the carbonate rock acidification effect evaluation device shown. Figure 5 as shown.

[0114] An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, the following steps are implemented:

[0115] Obtain a first image of the reservoir acidification process, perform binary segmentation processing on the first image to obtain a binary image including the reservoir skeleton area and the fracture-vug area;

[0116] Based on the number of pixels in the fracture-vug area in the binary image, calculate the porosity of the reservoir; and, based on the binary image, calculate the fractal dimension of the fracture-vug area in the binary image;

[0117] Evaluate the acidification effect of the reservoir according to the porosity and the fractal dimension.

[0118] In one embodiment, the method further includes:

[0119] Perform reservoir seepage simulation based on the binary image, calculate the equivalent permeability of the reservoir according to the simulation result, and calculate the skin factor of the reservoir according to the equivalent permeability;

[0120] Evaluate the acidification effect of the reservoir according to the porosity, the fractal dimension, the equivalent permeability, and the skin factor.

[0121] In one embodiment, the obtaining of the first image of the reservoir acidification process includes:

[0122] Obtain multiple first images of the reservoir acidification process in real time.

[0123] In one embodiment, the calculation of the porosity of the reservoir based on the number of pixels in the fracture-vug area in the binary image is performed according to the following formula:

[0124]

[0125] where φ is the porosity of the reservoir; v φ is the number of pixels in the fracture-vug area; v is the total number of pixels in the first image.

[0126] In one embodiment, calculating the fractal dimension of the fracture-vug region in the binary image based on the binary image includes:

[0127] Covering the binary image with a plurality of square boxes having the same side length, recording the number of boxes covering the fracture-vug region, and calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box.

[0128] In one embodiment, calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box is performed based on the following formula:

[0129]

[0130] where D is the fractal dimension of the fracture-vug region; r is the side length of the square box; and N(r) is the number of boxes covering the fracture-vug region.

[0131] In one embodiment, performing reservoir seepage simulation based on the binary image, calculating the equivalent permeability of the reservoir according to the simulation result, and calculating the skin factor of the reservoir according to the equivalent permeability are respectively performed based on the following formulas:

[0132]

[0133]

[0134] where K is the equivalent permeability of the reservoir, with the unit of m 2 ; q is the flow rate of the acid solution, with the unit of m 3 / s; μ is the viscosity of the acid solution, with the unit of Pa·s; L is the length of the reservoir corresponding to the binary image, with the unit of m; A is the cross-sectional area of the reservoir corresponding to the binary image, with the unit of m 2 ; P1 is the inlet pressure of the reservoir, with the unit of Pa; P2 is the outlet pressure of the reservoir, with the unit of Pa;

[0135] S is the skin factor of the reservoir; K0 is the initial equivalent permeability of the reservoir before acidification, with the unit of m 2 ; r s is the acidification radius, with the unit of m; r w is the wellbore radius, with the unit of m.

[0136] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can 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.

[0137] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows 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, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0138] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0140] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0141] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0142] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. 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 disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0143] It should also be noted that the term "comprising," "including," or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0144] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for evaluating the acidification effect of carbonate rocks, characterized in that, The method includes: Obtaining a first image of the reservoir acidification process, performing binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-vug region; Calculating the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image; and calculating the fractal dimension of the fracture-vug region in the binary image based on the binary image; Evaluating the acidification effect of the reservoir according to the porosity and the fractal dimension.

2. The carbonate rock acidification effect evaluation method according to claim 1, wherein The method further includes: Performing reservoir seepage simulation based on the binary image, calculating the equivalent permeability of the reservoir according to the simulation result, and calculating the skin factor of the reservoir according to the equivalent permeability; Evaluating the acidification effect of the reservoir according to the porosity, the fractal dimension, the equivalent permeability, and the skin factor.

3. The carbonate rock acidification effect evaluation method according to claim 1, characterized in that, The obtaining of the first image of the reservoir acidification process includes: obtaining a plurality of first images of the reservoir acidification process in real time.

4. The carbonate rock acidification effect evaluation method according to claim 2, wherein The calculating of the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image is performed based on the following formula: where φ is the porosity of the reservoir; v φ is the number of pixels in the fracture-vug area; v is the total number of pixels in the first image.

5. The carbonate rock acidification effect evaluation method according to claim 2, wherein, The calculating of the fractal dimension of the fracture-vug region in the binary image based on the binary image includes: Covering the binary image with a plurality of square boxes with the same side length, recording the number of boxes covering the fracture-vug region, and calculating the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box.

6. The carbonate rock acidification effect evaluation method according to claim 5, characterized in that The calculating of the fractal dimension of the fracture-vug region in the binary image based on the number of boxes covering the fracture-vug region and the side length of the square box is performed based on the following formula: where D is the fractal dimension of the fracture-vug region; r is the side length of the square box; and N(r) is the number of boxes covering the fracture-vug region.

7. The carbonate rock acidification effect evaluation method according to claim 2, wherein The performing of the reservoir seepage simulation based on the binary image, calculating the equivalent permeability of the reservoir according to the simulation result, and calculating the skin factor of the reservoir according to the equivalent permeability are respectively performed based on the following formulas: where K is the equivalent permeability of the reservoir, with the unit of m 2 ; q is the flow rate of the acid solution, with the unit of m 3 / s; μ is the viscosity of the acid solution, with the unit of Pa·s; L is the length of the reservoir corresponding to the binary image, with the unit of m; A is the cross-sectional area of the reservoir corresponding to the binary image, with the unit of m 2 ; P1 is the inlet pressure of the reservoir, with the unit of Pa; P2 is the outlet pressure of the reservoir, with the unit of Pa; S is the skin factor of the reservoir; K0 is the initial equivalent permeability of the reservoir before acidizing, with the unit of m 2 ; r s is the acidizing radius, with the unit of m; r w is the wellbore radius, with the unit of m.

8. An apparatus for evaluating the acidification effect of carbonate rocks, characterized in that, Including: An image processing module for obtaining a first image of the reservoir acidification process, performing binary segmentation processing on the first image to obtain a binary image including a reservoir skeleton region and a fracture-vug region; A calculation module for calculating the porosity of the reservoir based on the number of pixels in the fracture-vug region of the binary image; and calculating the fractal dimension of the fracture-vug region in the binary image based on the binary image; An evaluation module for evaluating the acidification effect of the reservoir according to the porosity and the fractal dimension.

9. A processor, characterized in that, Configured to execute the carbonate rock acidification effect evaluation method according to any one of claims 1 to 7.

10. A machine-readable storage medium having instructions stored thereon, characterized in that, When executed by a processor, the instruction causes the processor to be configured to execute the carbonate rock acidification effect evaluation method according to any one of claims 1 to 7.

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