Rock core permeation effect evaluation method and system based on digital rock core

Abstract

The invention relates to the technical field of digital rock cores, and discloses a rock core permeation effect evaluation method and system based on a digital rock core, and the method comprises the following steps: constructing a digital rock core model; according to the porosity, carrying out preliminary evaluation on the core permeability effect to obtain an evaluation initial value; comprehensively judging whether the evaluation initial value is adjusted or not according to the pore connectivity rate and the average connected pore diameter; if the evaluation initial value is judged to be adjusted, adjusting the evaluation initial value according to the pore influence coefficient to obtain an evaluation adjustment value; environment temperature, environment humidity and fluid viscosity of the rock core sample are collected, an environment influence coefficient is obtained according to the environment temperature and the environment humidity, a fluid influence coefficient is obtained according to the fluid viscosity, the evaluation adjustment value is corrected according to the environment influence coefficient and the fluid influence coefficient, and an evaluation final value is obtained. According to the method, the permeation effect of the rock core can be comprehensively and accurately evaluated through multi-dimensional consideration factors.

Description

Technical Field

[0001] The present invention relates to the field of digital core technology, and in particular to a core penetration effect evaluation method and system based on digital cores. Background Art

[0002] In fields such as oil and gas exploration and development, as well as geological engineering, core permeability assessment is crucial for understanding formation fluid flow characteristics, optimizing extraction plans, and engineering design. Traditional core permeability assessment methods primarily rely on laboratory physical experiments, such as steady-state and unsteady-state methods for measuring permeability, to obtain core pore structure information through direct observation and simple measurements. However, these methods have numerous limitations.

[0003] On the one hand, traditional experimental methods can often only obtain macroscopic permeability data of the core as a whole, making it difficult to deeply analyze the impact of the complex pore structure inside the core on the permeability effect, and unable to accurately reflect key factors such as the connectivity and throat characteristics of the microscopic pores inside the core, resulting in insufficient accuracy in the evaluation results. On the other hand, traditional methods find it difficult to fully consider the impact of environmental factors and fluid properties on the permeability of the core during the evaluation process. In the actual formation environment, changes in temperature and humidity will significantly affect the physical properties of the fluid and the pore structure of the core. The viscosity of different fluids will also change their seepage characteristics in the core. However, traditional evaluation methods are unable to comprehensively consider these factors, resulting in a large deviation between the evaluation results and the actual situation.

[0004] Therefore, it is necessary to provide a core penetration effect evaluation method and system based on digital cores to solve the problem that the core penetration effect evaluation in the existing technology is not comprehensive and accurate enough. Summary of the Invention

[0005] In view of this, the present invention proposes a core penetration effect evaluation method and system based on digital cores, aiming to solve the problem that the core penetration effect evaluation in the prior art is not comprehensive and accurate enough.

[0006] On the one hand, the present invention proposes a core permeability effect evaluation method based on digital core, comprising:

[0007] Scan the core sample, obtain the three-dimensional image data of the core sample, and build a digital core model;

[0008] Calculating the porosity based on the ratio of the pore space of the digital core model to the total volume of the core, and performing a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value;

[0009] Identifying the connected paths between pores in the digital core model, calculating the pore connectivity and the average connected pore diameter, and comprehensively determining whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculating the pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjusting the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value;

[0010] The ambient temperature, ambient humidity and fluid viscosity of the core sample are collected, an environmental influence coefficient is obtained according to the ambient temperature and ambient humidity, a fluid influence coefficient is obtained according to the fluid viscosity, and the evaluation adjustment value is corrected according to the environmental influence coefficient and the fluid influence coefficient to obtain an evaluation final value.

[0011] Furthermore, the porosity is calculated based on the ratio of the pore space of the digital core model to the total volume of the core, including:

[0012] Obtaining the pore space volume in the digital core model and the total volume of the digital core model;

[0013] The porosity is the ratio of the pore space volume to the total volume.

[0014] Furthermore, the preliminary evaluation of the core permeability effect according to the porosity to obtain the initial evaluation value includes:

[0015] Comparing the porosity with the porosity in historical data to calculate similarity, if the similarity is greater than a preset similarity threshold, using the historical initial evaluation value corresponding to the maximum similarity as the initial evaluation value;

[0016] Otherwise, setting a first porosity and a second porosity, wherein the first porosity is greater than the second porosity;

[0017] If the porosity is greater than the first porosity, the initial evaluation value is the first initial evaluation value;

[0018] If the porosity is less than or equal to the first porosity and greater than the second porosity, the initial evaluation value is the second initial evaluation value;

[0019] If the porosity is less than or equal to the second porosity, the initial evaluation value is a third initial evaluation value;

[0020] The first evaluation initial value is greater than the second evaluation initial value, and the second evaluation initial value is greater than the third evaluation initial value.

[0021] Furthermore, the identification of the connection paths between pores in the digital core model and the calculation of the pore connectivity and the average connected pore diameter include:

[0022] The pore connectivity ratio is the ratio of the number of actually connected pores to the total number of pores in the digital core model;

[0023] Several sampling points are set on the connected pores, the pore diameters of the several sampling points are obtained, and the average pore diameter is calculated as the connected pore diameter.

[0024] Furthermore, when comprehensively judging whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter, the method includes:

[0025] Set the minimum value of pore connectivity and the minimum value of connected pore diameter;

[0026] If the pore connectivity is less than or equal to the minimum pore connectivity, and / or the average connected pore diameter is less than or equal to the minimum connected pore diameter, it is determined that the initial evaluation value needs to be adjusted;

[0027] Otherwise, it is determined that there is no need to adjust the initial evaluation value.

[0028] Furthermore, the calculation of the pore influence coefficient according to the pore connectivity and the average connected pore diameter includes:

[0029] If the pore connectivity is less than or equal to the minimum pore connectivity, and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the first influence coefficient;

[0030] If the pore connectivity is less than or equal to the minimum pore connectivity and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the second influence coefficient.

[0031] Obtaining a minimum throat radius in the digital core model, setting a throat radius threshold, and if the minimum throat radius is less than or equal to the throat radius threshold, determining to adjust the pore influence coefficient by the adjustment coefficient, and using the adjusted pore influence coefficient as the final pore influence coefficient; if the minimum throat radius is greater than the throat radius threshold, determining not to adjust the pore influence coefficient, and using the pore influence coefficient as the final pore influence coefficient;

[0032] Among them, 1>second influence coefficient>first influence coefficient>0, 1>adjustment coefficient>0.

[0033] Furthermore, the adjusting the initial evaluation value according to the porosity influence coefficient to obtain the evaluation adjustment value includes:

[0034] The evaluation adjustment value is the product of the final porosity influence coefficient and the initial evaluation value.

[0035] Furthermore, obtaining the environmental influence coefficient according to the ambient temperature and ambient humidity, and obtaining the fluid influence coefficient according to the fluid viscosity, includes:

[0036] Set a temperature threshold and a humidity range. If the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the first environmental impact coefficient; if the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; if the ambient temperature is greater than the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; otherwise, the environmental impact coefficient is the third environmental impact coefficient;

[0037] Setting a fluid viscosity threshold, if the fluid viscosity is higher than the fluid viscosity threshold, the fluid influence coefficient is the first fluid influence coefficient; if the fluid viscosity is equal to the fluid viscosity threshold, the fluid influence coefficient is the second fluid influence coefficient; if the fluid viscosity is lower than the fluid viscosity threshold, the fluid influence coefficient is the third fluid influence coefficient;

[0038] The third environmental impact coefficient is 0.5, 0<first environmental impact coefficient<second environmental impact coefficient<third environmental impact coefficient; the third fluid impact coefficient is 0.5, 0<first fluid impact coefficient<second fluid impact coefficient<third fluid impact coefficient.

[0039] Furthermore, the correction of the assessment adjustment value according to the environmental impact coefficient and the fluid impact coefficient to obtain the assessment final value includes:

[0040] The coefficient sum of the environmental impact coefficient and the fluid impact coefficient is calculated, and the final evaluation value is the product of the evaluation adjustment value and the coefficient sum.

[0041] Compared with the existing technology, the beneficial effect of the present invention is that the present invention takes into account factors in multiple dimensions and provides an accurate and efficient means of evaluating the permeability effect of cores. In terms of accuracy, compared with traditional evaluation methods, this method relies on digital core models to accurately extract key pore structure parameters such as porosity and pore connectivity, avoiding errors caused by manual measurement and subjective judgment. At the same time, it comprehensively considers various parameters such as ambient temperature, humidity, and fluid viscosity for correction, and comprehensively considers various factors affecting the permeability effect under actual working conditions, so that the evaluation results can more realistically reflect the permeability characteristics of the core in the actual environment, greatly improving the accuracy of the evaluation. From an efficiency perspective, the rapid acquisition of core three-dimensional image data and the construction of a model through digital technology, combined with automated parameter calculation and evaluation processes, reduces tedious manual operation links, significantly shortens the evaluation cycle, and can quickly and efficiently obtain results, providing strong support for time-sensitive work such as oil and natural gas exploration and development. In terms of practicality, this method is applicable to a variety of complex geological conditions and different types of core samples. Whether in reservoir evaluation in oil and natural gas exploration and development, or groundwater flow analysis in geological engineering, it can provide a scientific and accurate basis for practical work such as mining plan optimization and engineering design, helping decision makers to formulate more reasonable and effective plans, reduce exploration and development and engineering construction costs, and improve resource utilization efficiency.

[0042] On the other hand, the present application also provides a core penetration effect evaluation system based on digital cores, comprising:

[0043] a model building module configured to scan the core sample, obtain three-dimensional image data of the core sample, and build a digital core model;

[0044] a preliminary evaluation module configured to calculate porosity based on a ratio of pore space in the digital core model to a total core volume, and to perform a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value;

[0045] an adjustment evaluation module configured to identify connected paths between pores in the digital core model, calculate pore connectivity and an average connected pore diameter, and comprehensively determine whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculate a pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjust the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value;

[0046] The evaluation decision module is configured to collect the ambient temperature, ambient humidity and fluid viscosity of the core sample, obtain the environmental influence coefficient according to the ambient temperature and ambient humidity, obtain the fluid influence coefficient according to the fluid viscosity, and correct the evaluation adjustment value according to the environmental influence coefficient and the fluid influence coefficient to obtain the evaluation final value.

[0047] It is understandable that the core permeability effect evaluation method and system based on digital core provided in this application have the same beneficial effects and will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0049] Figure 1 A flowchart of a method for evaluating core permeability based on digital cores provided in an embodiment of the present invention;

[0050] Figure 2 This is a functional block diagram of a digital core-based core permeability evaluation system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0052] In some embodiments of this application, see Figure 1 As shown, this embodiment provides a core permeability effect evaluation method based on digital core, comprising the following steps:

[0053] S100, scanning the core sample, obtaining three-dimensional image data of the core sample, and constructing a digital core model;

[0054] S200, calculating porosity based on the ratio of the pore space of the digital core model to the total volume of the core, and performing a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value;

[0055] S300, identifying the connection paths between pores in the digital core model, calculating the pore connectivity and the average connected pore diameter, and comprehensively determining whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculating the pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjusting the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value;

[0056] S400: Collect the ambient temperature, ambient humidity, and fluid viscosity of the core sample, obtain an environmental influence coefficient based on the ambient temperature and ambient humidity, obtain a fluid influence coefficient based on the fluid viscosity, and correct the assessment adjustment value based on the environmental influence coefficient and the fluid influence coefficient to obtain a final assessment value.

[0057] It can be understood that the present invention takes into account factors in multiple dimensions and provides an accurate and efficient means of evaluating the permeability effect of cores. In terms of accuracy, compared with traditional evaluation methods, this method relies on digital core models to accurately extract key pore structure parameters such as porosity and pore connectivity, avoiding errors caused by manual measurement and subjective judgment. At the same time, it comprehensively considers various parameters such as ambient temperature, humidity, and fluid viscosity for correction, and comprehensively considers various factors affecting the permeability effect under actual working conditions, so that the evaluation results can more realistically reflect the permeability characteristics of the core in the actual environment, greatly improving the accuracy of the evaluation. From an efficiency perspective, the rapid acquisition of core three-dimensional image data and the construction of models through digital technology, combined with automated parameter calculation and evaluation processes, reduces tedious manual operation links, significantly shortens the evaluation cycle, and can quickly and efficiently obtain results, providing strong support for time-sensitive work such as oil and natural gas exploration and development. In terms of practicality, this method is applicable to a variety of complex geological conditions and different types of core samples. Whether in reservoir evaluation in oil and natural gas exploration and development, or groundwater flow analysis in geological engineering, it can provide a scientific and accurate basis for practical work such as mining plan optimization and engineering design, helping decision makers to formulate more reasonable and effective plans, reduce exploration and development and engineering construction costs, and improve resource utilization efficiency.

[0058] In some embodiments of the present application, the porosity is calculated based on the ratio of the pore space of the digital core model to the total volume of the core, including:

[0059] Obtaining the pore space volume in the digital core model and the total volume of the digital core model;

[0060] The porosity is the ratio of the pore space volume to the total volume.

[0061] In some embodiments of the present application, performing a preliminary evaluation on the core permeability effect according to the porosity to obtain an initial evaluation value includes:

[0062] Comparing the porosity with the porosity in historical data to calculate similarity, if the similarity is greater than a preset similarity threshold, using the historical initial evaluation value corresponding to the maximum similarity as the initial evaluation value;

[0063] Otherwise, setting a first porosity and a second porosity, wherein the first porosity is greater than the second porosity;

[0064] If the porosity is greater than the first porosity, the initial evaluation value is the first initial evaluation value;

[0065] If the porosity is less than or equal to the first porosity and greater than the second porosity, the initial evaluation value is the second initial evaluation value;

[0066] If the porosity is less than or equal to the second porosity, the initial evaluation value is a third initial evaluation value;

[0067] The first evaluation initial value is greater than the second evaluation initial value, and the second evaluation initial value is greater than the third evaluation initial value.

[0068] Understandably, during the initial assessment phase, the dual-mode assessment strategy balances data reuse with universal applicability. Based on historical data comparison, it fully leverages accumulated experience and data. When the porosity of a new sample is highly similar to historical data, the corresponding initial assessment value is quickly called, significantly improving assessment efficiency while reducing resource consumption caused by repeated modeling and analysis. In the absence of similar historical data, the initial assessment value is divided into porosity intervals, providing a unified and reasonable assessment framework for various core samples. This makes the assessment process more standardized and universal, effectively improving the efficiency and accuracy of the initial assessment of core permeability.

[0069] Specifically, for example, in the porosity calculation example, for a core sample, a high-precision CT scan is used to obtain its three-dimensional image data to construct a digital core model. The model is analyzed by image processing software to accurately extract the pore space volume of 25mm 3 , the total volume of the digital core model is 100mm 3 Calculated, the core's porosity is 25%. Comparing this 25% porosity with data in the historical database reveals similarities below the set threshold. At this point, the first porosity is pre-set to 30% and the second porosity to 15%. Since 15% < 25% < 30%, the second initial assessment value for this core is determined according to the rule.

[0070] In some embodiments of the present application, the steps of identifying the connection paths between pores in the digital core model and calculating the pore connectivity and the average connected pore diameter include:

[0071] The pore connectivity ratio is the ratio of the number of actually connected pores to the total number of pores in the digital core model;

[0072] Several sampling points are set on the connected pores, the pore diameters of the several sampling points are obtained, and the average pore diameter is calculated as the connected pore diameter.

[0073] In some embodiments of the present application, the comprehensive determination of whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter includes:

[0074] Set the minimum value of pore connectivity and the minimum value of connected pore diameter;

[0075] If the pore connectivity is less than or equal to the minimum pore connectivity, and / or the average connected pore diameter is less than or equal to the minimum connected pore diameter, it is determined that the initial evaluation value needs to be adjusted;

[0076] Otherwise, it is determined that there is no need to adjust the initial evaluation value.

[0077] In some embodiments of the present application, the calculation of the pore influence coefficient based on the pore connectivity and the average connected pore diameter includes:

[0078] If the pore connectivity is less than or equal to the minimum pore connectivity, and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the first influence coefficient;

[0079] If the pore connectivity is less than or equal to the minimum pore connectivity and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the second influence coefficient.

[0080] Obtaining a minimum throat radius in the digital core model, setting a throat radius threshold, and if the minimum throat radius is less than or equal to the throat radius threshold, determining to adjust the pore influence coefficient by the adjustment coefficient, and using the adjusted pore influence coefficient as the final pore influence coefficient; if the minimum throat radius is greater than the throat radius threshold, determining not to adjust the pore influence coefficient, and using the pore influence coefficient as the final pore influence coefficient;

[0081] Among them, 1>second influence coefficient>first influence coefficient>0, 1>adjustment coefficient>0.

[0082] In some embodiments of the present application, adjusting the initial evaluation value according to the porosity influence coefficient to obtain the evaluation adjustment value includes:

[0083] The evaluation adjustment value is the product of the final porosity influence coefficient and the initial evaluation value.

[0084] It can be understood that by setting minimum values ​​for pore connectivity and connected pore diameter, the pore influence coefficient calculation and adjustment process comprehensively considers multiple factors such as pore connectivity, average connected pore diameter, and minimum throat radius. This allows for a hierarchical and multidimensional determination of the pore influence coefficient, fully reflecting the combined effect of pore structure on permeability. Ultimately, the assessment adjustment value is derived by multiplying the coefficient by the initial assessment value, making the assessment results more consistent with the actual permeability of the core, effectively reducing assessment bias caused by insufficient pore structure analysis, and providing a more reliable basis for core permeability assessment.

[0085] Specifically, in the pore connectivity parameter calculation example, a digital core model of a shale core is analyzed. The total number of pores in the model is 500, and the number of actually connected pores is 200. The pore connectivity is 200 ÷ 500 = 0.4. 100 sampling points are evenly spaced across the connected pores, and the pore diameters at each point are averaged, resulting in an average connected pore diameter of 5 μm. In the initial evaluation value adjustment judgment example, the minimum pore connectivity is set to 0.5, and the minimum connected pore diameter is set to 8 μm. For this shale core, since its pore connectivity of 0.4 is less than the minimum value of 0.5, it meets the adjustment conditions, and it is determined that the initial evaluation value needs to be adjusted. In the pore influence coefficient calculation example, since the pore connectivity and average connected pore diameter of the shale core are both less than the corresponding minimum values, the pore influence coefficient is determined to be a first influence coefficient of 0.6. Furthermore, the minimum throat radius is determined to be 2 μm, and the throat radius threshold is set to 3 μm. Because the minimum throat radius is less than the threshold, the pore influence coefficient is adjusted by an adjustment factor of 0.8, resulting in a final pore influence coefficient of 0.7 × 0.8 = 0.56. In the evaluation adjustment value calculation example, if the initial evaluation value of the shale core is 80, the evaluation adjustment value is calculated according to the formula as the product of the final pore influence coefficient of 0.56 and the initial evaluation value of 80, that is, 80 × 0.56 = 44.8, completing the adjustment and optimization of the core permeability evaluation value.

[0086] In some embodiments of the present application, obtaining the environmental impact coefficient according to the ambient temperature and ambient humidity, and obtaining the fluid impact coefficient according to the fluid viscosity, includes:

[0087] Set a temperature threshold and a humidity range. If the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the first environmental impact coefficient; if the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; if the ambient temperature is greater than the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; otherwise, the environmental impact coefficient is the third environmental impact coefficient;

[0088] Setting a fluid viscosity threshold, if the fluid viscosity is higher than the fluid viscosity threshold, the fluid influence coefficient is the first fluid influence coefficient; if the fluid viscosity is equal to the fluid viscosity threshold, the fluid influence coefficient is the second fluid influence coefficient; if the fluid viscosity is lower than the fluid viscosity threshold, the fluid influence coefficient is the third fluid influence coefficient;

[0089] The third environmental impact coefficient is 0.5, 0<first environmental impact coefficient<second environmental impact coefficient<third environmental impact coefficient; the third fluid impact coefficient is 0.5, 0<first fluid impact coefficient<second fluid impact coefficient<third fluid impact coefficient.

[0090] It is understandable that in terms of determining the environmental impact coefficient, by setting the temperature threshold and humidity range, the impact of different environmental condition combinations on the core permeability effect is fully covered, and the impact of changes in environmental factors on the core pore structure, fluid-rock interaction, etc. can be accurately captured, avoiding the evaluation bias caused by differences in environmental conditions. In the determination of the fluid influence coefficient, different influence coefficients are divided according to the fluid viscosity threshold, which intuitively reflects the impact of changes in fluid viscosity on its seepage ability in the core, which is in line with the principles of fluid mechanics. This hierarchical classification method of determining the influence coefficient facilitates the accurate weighing of the contribution of each factor in the comprehensive evaluation, making the evaluation results closer to the actual working conditions, and providing a more scientific decision-making basis for oil and gas exploration and development, geological engineering and other fields.

[0091] Specifically, in the embodiment for determining the environmental impact coefficient, the temperature threshold is set at 25°C and the humidity range is [40%, 60%]. For a core sample, the ambient temperature is 20°C and the humidity is 30%. Because the ambient temperature is less than the temperature threshold and the humidity is not within the specified range, the environmental impact coefficient is determined to be a first environmental impact coefficient of 0.2. In the embodiment for determining the fluid impact coefficient, the fluid viscosity threshold is set at 5 mPa·s. The viscosity of the fluid in the core sample is measured to be 8 mPa·s. Because the fluid viscosity is higher than the threshold, the fluid impact coefficient is determined to be a first fluid impact coefficient of 0.3.

[0092] In some embodiments of the present application, the correction of the evaluation adjustment value according to the environmental impact coefficient and the fluid impact coefficient to obtain the evaluation final value includes:

[0093] The coefficient sum of the environmental impact coefficient and the fluid impact coefficient is calculated, and the final evaluation value is the product of the evaluation adjustment value and the coefficient sum.

[0094] It's understandable that, on the one hand, summing the coefficients of these two key influencing factors, environment and fluid, intuitively reflects the overall impact of external conditions on core permeability, while ensuring that each factor's influence is fully reflected in the final assessment. On the other hand, by multiplying the assessment adjustment value by the sum of the coefficients, a reasonable correction is achieved to the initial assessment results, ensuring that the final assessment value fully incorporates multiple aspects of information, including pore structure, environment, and fluid, thereby improving assessment efficiency.

[0095] Specifically, after the determination of the environmental impact coefficient and the fluid impact coefficient is completed, the evaluation adjustment value is further corrected to obtain the evaluation final value. Assume that in the early pore structure parameter analysis based on the digital core model, the evaluation adjustment value of the core sample has been obtained as 44.8. According to the calculation rules in the embodiment, the coefficient sum of the environmental impact coefficient and the fluid impact coefficient is first calculated, that is, 0.2+0.3=0.5; then the evaluation adjustment value is multiplied by the coefficient sum to obtain the evaluation final value of 44.8×0.5=22.4. It organically combines the influence of environmental and fluid factors, and comprehensively considers the key factors affecting the core permeability effect from multiple dimensions, so that the final evaluation value can more truly and accurately reflect the permeability performance of the core under actual working conditions, providing a quantitative and reliable basis for oil and gas production plan design, geological engineering decision-making, etc.

[0096] On the other hand, see Figure 2 As shown, the present application also provides a core penetration effect evaluation system based on digital cores, which is used to apply the above-mentioned core penetration effect evaluation method based on digital cores, including:

[0097] a model building module configured to scan the core sample, obtain three-dimensional image data of the core sample, and build a digital core model;

[0098] a preliminary evaluation module configured to calculate porosity based on a ratio of pore space in the digital core model to a total core volume, and to perform a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value;

[0099] an adjustment evaluation module configured to identify connected paths between pores in the digital core model, calculate pore connectivity and an average connected pore diameter, and comprehensively determine whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculate a pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjust the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value;

[0100] The evaluation decision module is configured to collect the ambient temperature, ambient humidity and fluid viscosity of the core sample, obtain the environmental influence coefficient according to the ambient temperature and ambient humidity, obtain the fluid influence coefficient according to the fluid viscosity, and correct the evaluation adjustment value according to the environmental influence coefficient and the fluid influence coefficient to obtain the evaluation final value.

[0101] It is understandable that the model building module of the present invention obtains three-dimensional image data by scanning the core sample, thereby constructing an accurate digital core model, laying a solid foundation for subsequent evaluation work. The preliminary evaluation module performs a preliminary evaluation of the permeability effect of the core by calculating the porosity, and quickly obtains an initial evaluation value. The adjustment evaluation module further identifies the connection paths between the pores in the digital core model, calculates the pore connectivity and the average connected pore diameter, comprehensively judges whether the preliminary evaluation value needs to be adjusted, and calculates the pore influence coefficient based on this, accurately adjusts the initial evaluation value, and obtains the evaluation adjustment value. Finally, the evaluation decision module collects environmental and fluid parameters, calculates the environmental influence coefficient and the fluid influence coefficient, corrects the evaluation adjustment value, and obtains the final evaluation result. The entire system works in coordination with multiple modules, which not only improves the accuracy of the evaluation, but also can be dynamically adjusted according to the actual environment and fluid conditions to ensure the reliability and applicability of the evaluation results.

[0102] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may 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, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A core penetration effect evaluation method based on digital core, characterized in that: include: Scan the core sample, obtain the three-dimensional image data of the core sample, and build a digital core model; Calculating the porosity based on the ratio of the pore space of the digital core model to the total volume of the core, and performing a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value; Identifying the connected paths between pores in the digital core model, calculating the pore connectivity and the average connected pore diameter, and comprehensively determining whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculating the pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjusting the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value; The ambient temperature, ambient humidity and fluid viscosity of the core sample are collected, an environmental influence coefficient is obtained according to the ambient temperature and ambient humidity, a fluid influence coefficient is obtained according to the fluid viscosity, and the evaluation adjustment value is corrected according to the environmental influence coefficient and the fluid influence coefficient to obtain an evaluation final value.

2. The method for evaluating core permeability based on digital core according to claim 1, characterized in that: The porosity is calculated based on the ratio of the pore space of the digital core model to the total volume of the core, including: Obtaining the pore space volume in the digital core model and the total volume of the digital core model; The porosity is the ratio of the pore space volume to the total volume.

3. The method for evaluating core permeability based on digital core according to claim 1, characterized in that: The preliminary evaluation of the core permeability effect according to the porosity to obtain the initial evaluation value includes: Comparing the porosity with the porosity in historical data to calculate similarity, if the similarity is greater than a preset similarity threshold, using the historical initial evaluation value corresponding to the maximum similarity as the initial evaluation value; Otherwise, setting a first porosity and a second porosity, wherein the first porosity is greater than the second porosity; If the porosity is greater than the first porosity, the initial evaluation value is the first initial evaluation value; If the porosity is less than or equal to the first porosity and greater than the second porosity, the initial evaluation value is the second initial evaluation value; If the porosity is less than or equal to the second porosity, the initial evaluation value is a third initial evaluation value; The first evaluation initial value is greater than the second evaluation initial value, and the second evaluation initial value is greater than the third evaluation initial value.

4. The method for evaluating core permeability based on digital core according to claim 1, characterized in that: The identification of the connection paths between pores in the digital core model and the calculation of the pore connectivity and the average connected pore diameter include: The pore connectivity ratio is the ratio of the number of actually connected pores to the total number of pores in the digital core model; Several sampling points are set on the connected pores, the pore diameters of the several sampling points are obtained, and the average pore diameter is calculated as the connected pore diameter.

5. The method for evaluating core permeability based on digital core according to claim 4, characterized in that: When comprehensively judging whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter, the following is included: Set the minimum value of pore connectivity and the minimum value of connected pore diameter; If the pore connectivity is less than or equal to the minimum pore connectivity, and / or the average connected pore diameter is less than or equal to the minimum connected pore diameter, it is determined that the initial evaluation value needs to be adjusted; Otherwise, it is determined that there is no need to adjust the initial evaluation value.

6. The method for evaluating core permeability based on digital core according to claim 5, characterized in that: The calculation of the pore influence coefficient according to the pore connectivity and the average connected pore diameter includes: If the pore connectivity is less than or equal to the minimum pore connectivity, and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the first influence coefficient; If the pore connectivity is less than or equal to the minimum pore connectivity and the average connected pore diameter is less than or equal to the minimum connected pore diameter, then the pore influence coefficient is the second influence coefficient. Obtaining a minimum throat radius in the digital core model, setting a throat radius threshold, and if the minimum throat radius is less than or equal to the throat radius threshold, determining to adjust the pore influence coefficient by the adjustment coefficient, and using the adjusted pore influence coefficient as the final pore influence coefficient; if the minimum throat radius is greater than the throat radius threshold, determining not to adjust the pore influence coefficient, and using the pore influence coefficient as the final pore influence coefficient; Among them, 1>second influence coefficient>first influence coefficient>0, 1>adjustment coefficient>0.

7. The method for evaluating core permeability based on digital core according to claim 6, characterized in that: The step of adjusting the initial evaluation value according to the porosity influence coefficient to obtain an evaluation adjustment value includes: The evaluation adjustment value is the product of the final porosity influence coefficient and the initial evaluation value.

8. The method for evaluating core permeability based on digital core according to claim 1, characterized in that: Obtaining the environmental influence coefficient according to the ambient temperature and ambient humidity, and obtaining the fluid influence coefficient according to the fluid viscosity, includes: Set a temperature threshold and a humidity range. If the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the first environmental impact coefficient; if the ambient temperature is less than or equal to the temperature threshold and the ambient humidity is within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; if the ambient temperature is greater than the temperature threshold and the ambient humidity is not within the humidity range, the environmental impact coefficient is the second environmental impact coefficient; otherwise, the environmental impact coefficient is the third environmental impact coefficient; Setting a fluid viscosity threshold, if the fluid viscosity is higher than the fluid viscosity threshold, the fluid influence coefficient is the first fluid influence coefficient; if the fluid viscosity is equal to the fluid viscosity threshold, the fluid influence coefficient is the second fluid influence coefficient; if the fluid viscosity is lower than the fluid viscosity threshold, the fluid influence coefficient is the third fluid influence coefficient; The third environmental impact coefficient is 0.5, 0<first environmental impact coefficient<second environmental impact coefficient<third environmental impact coefficient; the third fluid impact coefficient is 0.5, 0<first fluid impact coefficient<second fluid impact coefficient<third fluid impact coefficient.

9. The method for evaluating core permeability based on digital core according to claim 1, characterized in that: Correcting the assessment adjustment value according to the environmental impact coefficient and the fluid impact coefficient to obtain the assessment final value includes: The coefficient sum of the environmental impact coefficient and the fluid impact coefficient is calculated, and the final evaluation value is the product of the evaluation adjustment value and the coefficient sum.

10. A core penetration effect evaluation system based on digital cores, used for applying the core penetration effect evaluation method based on digital cores according to any one of claims 1 to 9, characterized in that: include: a model building module configured to scan the core sample, obtain three-dimensional image data of the core sample, and build a digital core model; a preliminary evaluation module configured to calculate porosity based on a ratio of pore space in the digital core model to a total core volume, and to perform a preliminary evaluation of the core permeability effect based on the porosity to obtain an initial evaluation value; an adjustment evaluation module configured to identify connected paths between pores in the digital core model, calculate pore connectivity and an average connected pore diameter, and comprehensively determine whether to adjust the initial evaluation value based on the pore connectivity and the average connected pore diameter; if it is determined to be adjusted, calculate a pore influence coefficient based on the pore connectivity and the average connected pore diameter, and adjust the initial evaluation value based on the pore influence coefficient to obtain an evaluation adjustment value; The evaluation decision module is configured to collect the ambient temperature, ambient humidity and fluid viscosity of the core sample, obtain the environmental influence coefficient according to the ambient temperature and ambient humidity, obtain the fluid influence coefficient according to the fluid viscosity, and correct the evaluation adjustment value according to the environmental influence coefficient and the fluid influence coefficient to obtain the evaluation final value.

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