Anti-sloughing drilling fluid optimization method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses an anti-sloughing drilling fluid optimization method and device, electronic equipment and a storage medium. The method comprises the following steps: determining stratum characteristics influencing sand shale stratum well wall collapse and rock mechanics characteristic parameters; constructing a shaft multi-field coupling control model according to the stratum characteristics influencing the collapse of the sand shale stratum well wall, the rock mechanics characteristic parameters and the weak plane failure criterion; determining the window density of the anti-sloughing drilling fluid for stable and safe drilling of the well wall of the sand shale stratum according to the change trend of the stratum strength of the sand shale stratum along with the soaking of the drilling fluid, the weak plane failure criterion and the abnormal collapse phenomenon of the well wall of the sand shale stratum; and selecting a target anti-sloughing drilling fluid system according to drilling scene requirements, and performing performance evaluation on the selected target anti-sloughing drilling fluid system according to the constructed anti-sloughing drilling fluid evaluation numerical model. By adopting the scheme, optimization and optimization analysis of the anti-sloughing drilling fluid are carried out under the condition of multi-field coupling simulation, and the well wall stability of a sand shale stratum is improved.

Description

A method, apparatus, electronic device and storage medium for optimizing drilling fluid to prevent collapse. Technical Field

[0001] The embodiments of the present invention relate to the field of oil and gas field drilling technology, and in particular to a method, apparatus, electronic device and storage medium for optimizing drilling fluid to prevent collapse. Background Technology

[0002] The Sulige Gas Field in North my country is located in the northern central zone of the Yishan Slope in the Ordos Basin. Its main target formations are the He 8 and Shan 1 sections. The He 8 section is a braided river deposit, while the Shan 1 section is a meandering river deposit, characterized by "three lows, two highs, one many, and one strong." Sidetracking and horizontal wells are currently the main wellbore design structures. However, as the development cycle continues, the quality of replacement gas reservoirs deteriorates, the sand body encounter rate decreases, and construction becomes more complex and accidents occur frequently.

[0003] Specifically, in formations such as the Shiqianfeng Formation, Shihezi Formation, and Shanxi Formation, engineers lacked a clear understanding of the collapse cycle and safe drilling fluid density window, leading to unreasonable drilling densities. Furthermore, a lack of understanding of the instability mechanisms of dark brown and carbonaceous mudstone resulted in insufficiently targeted anti-collapse techniques, causing collapse pressures in some well sections to exceed the actual drilling density, leading to wellbore enlargement and even block collapse. Since wellbore instability and complex well leakage have become major technical challenges hindering tight gas drilling and production in the Sulige area, drilling and completion cycles have increased significantly, with extended time losses in some complex wells.

[0004] Therefore, how to improve drilling collapse prevention technology is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] This invention provides a method, apparatus, electronic device, and storage medium for optimizing anti-collapse drilling fluid, thereby optimizing the anti-collapse drilling fluid system and its formulation, improving wellbore stability in sandstone and mudstone formations, and effectively reducing the occurrence of complex downhole accidents such as wellbore instability and well leakage.

[0006] In a first aspect, embodiments of the present invention provide a method for optimizing drilling fluid to prevent collapse, comprising:

[0007] Based on the wellbore instability mechanism of sandstone and mudstone formations and the results of rock mechanics research, the formation characteristics and rock mechanics parameters that affect wellbore collapse in sandstone and mudstone formations were determined.

[0008] Based on the stratigraphic characteristics, rock mechanical parameters, and weak surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for wellbore is constructed.

[0009] Based on the trend of formation strength variation with drilling fluid immersion and the weak surface failure criterion, the minimum and maximum anti-collapse drilling fluid densities for wellbore stability in sandy mudstone formations are determined.

[0010] Based on the abnormal collapse phenomenon of the wellbore in sandy mudstone formations, the anti-collapse drilling fluid window density for stable and safe drilling in sandy mudstone formations was determined.

[0011] Based on the requirements of the drilling scenario, a target anti-collapse drilling fluid system is selected, and the performance of the selected target anti-collapse drilling fluid system is evaluated based on the constructed anti-collapse drilling fluid evaluation numerical model.

[0012] Secondly, embodiments of the present invention also provide an anti-collapse drilling fluid optimization device, comprising:

[0013] The formation collapse prevention parameter determination module is used to determine the formation characteristics and rock mechanics characteristic parameters that affect the collapse of well walls in sandy mudstone formations based on the well wall instability mechanism and rock mechanics research results.

[0014] The multi-field coupling control model construction module is used to construct a multi-field coupling control model for the wellbore based on the formation characteristics, rock mechanical parameters, and weak surface failure criteria that affect the collapse of the wellbore in sandstone and mudstone formations.

[0015] The anti-collapse drilling fluid density determination module is used to determine the minimum and maximum anti-collapse drilling fluid density when the wellbore is stable in sandy mudstone formations, based on the changing trend of formation strength with drilling fluid immersion and the weak surface failure criterion.

[0016] The anti-collapse drilling fluid window density determination module is used to determine the anti-collapse drilling fluid window density for stable and safe drilling in sandy and mudstone formations based on the abnormal collapse phenomenon of the well wall.

[0017] The anti-collapse drilling fluid performance evaluation module is used to select a target anti-collapse drilling fluid system based on the requirements of the drilling scenario, and to evaluate the performance of the selected target anti-collapse drilling fluid system based on the constructed anti-collapse drilling fluid evaluation numerical model.

[0018] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0019] One or more processors;

[0020] Storage device for storing one or more programs;

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the anti-collapse drilling fluid optimization method according to any embodiment of the present invention.

[0022] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the anti-collapse drilling fluid optimization method described in any embodiment of the present invention.

[0023] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the anti-collapse drilling fluid optimization method as described in any embodiment of the present invention.

[0024] This invention provides a method, apparatus, electronic device, and storage medium for optimizing anti-collapse drilling fluid. It identifies formation characteristics and rock mechanics parameters that influence wellbore collapse in sandstone and mudstone formations. Based on these characteristics, parameters, and weak-plane failure criteria, a multi-field coupled control model for the wellbore is constructed. The anti-collapse drilling fluid window density is determined based on the formation strength variation with drilling fluid immersion, the weak-plane failure criteria, and abnormal wellbore collapse phenomena in sandstone and mudstone formations. A target anti-collapse drilling fluid system is selected based on drilling scenario requirements, and its performance is evaluated using the constructed anti-collapse drilling fluid evaluation numerical model. This invention, based on the lithology and characteristics of sandstone and mudstone, optimizes the anti-collapse drilling fluid system and its specific formulation under multi-field coupled simulation conditions to improve wellbore stability in sandstone and mudstone formations and effectively reduce the occurrence of complex downhole accidents such as wellbore instability and lost circulation. Attached Figure Description

[0025] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0026] Figure 1 is a flowchart of an anti-collapse drilling fluid optimization method provided in Embodiment 1 of the present invention;

[0027] Figure 2 is a flowchart of an anti-collapse drilling fluid optimization method provided in Embodiment 2 of the present invention;

[0028] Figure 3 is a schematic diagram of the scanning electron microscope microstructure of each group of argillaceous rock samples provided in Embodiment 2 of the present invention.

[0029] Figure 4 is a schematic diagram of the energy spectrum of a rock sample composition test provided in Embodiment 2 of the present invention;

[0030] Figure 5 is a schematic diagram of a single-well three-pressure profile prediction result provided in Embodiment 2 of the present invention;

[0031] Figure 6 is a schematic diagram of the working principle of a nano-blocking agent provided in Embodiment 2 of the present invention;

[0032] Figure 7 is a structural schematic diagram of an anti-collapse drilling fluid optimization device provided in Embodiment 3 of the present invention;

[0033] Figure 8 is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0034] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0035] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations (or steps) may be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operation is completed, but may also have additional steps not included in the figures. The process may correspond to a method, function, procedure, subroutine, subroutine, etc.

[0036] The acquisition, storage, use, and processing of data in this application comply with relevant national laws and regulations. It should be noted that existing industry solutions such as software, components, or models may be mentioned in the embodiments of this application. These should be considered exemplary and intended only to illustrate the feasibility of implementing the technical solution of this application, but do not imply that the applicant has already used or necessarily used such a solution.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0038] Example 1

[0039] Figure 1 is a flowchart of an anti-collapse drilling fluid optimization method provided in an embodiment of the present invention. This embodiment is applicable to the optimization of anti-collapse drilling fluid for sandstone and mudstone under multi-field coupling conditions. The method of this embodiment can be executed by an anti-collapse drilling fluid optimization device, which can be implemented in hardware and / or software. The device can be configured in a server for anti-collapse drilling fluid optimization. The method specifically includes the following steps:

[0040] S110. Based on the wellbore instability mechanism of sandstone and mudstone formations and the results of rock mechanics research, the formation characteristics and rock mechanics parameters that affect the collapse of wellbore walls in sandstone and mudstone formations were determined.

[0041] Wellbore instability is a common problem in drilling engineering, referring to three basic types of wellbore collapse, narrowing, and formation fracturing during drilling or completion. It is one of the main factors affecting downhole safety. Wellbore instability mechanisms refer to the analysis and explanation of the causes of wellbore collapse, narrowing, or formation fracturing in sandstone and mudstone formations. This invention, through the study of wellbore instability mechanisms in sandstone and mudstone formations, identifies formation characteristics that influence the mechanical-chemical collapse of wellbores in these formations, including but not limited to formation hydrophilicity and formation porosity.

[0042] Rock mechanics research refers to the experimental simulation of the physical and mechanical properties of rocks, allowing for in-depth study of their deformation, strength, and failure characteristics. In this embodiment of the invention, rock mechanics experiments are conducted to determine the rock mechanics characteristic parameters affecting wellbore collapse in sandstone and mudstone formations, including but not limited to elastic modulus, deformation modulus, Poisson's ratio, permeability coefficient, and compressive strength.

[0043] S120. Based on the formation characteristics, rock mechanics parameters, and weak surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for the wellbore is constructed.

[0044] Based on the wellbore instability mechanism of sandstone and mudstone formations, observation of the central region of argillaceous rock samples in the work area revealed a higher probability of fractures. This demonstrates that microfractures not only provide seepage channels for drilling fluid loss but also cause anisotropy in formation properties, affecting wellbore stability. Therefore, the influence of the compressive strength and in-situ stress of the encountered rock formations on wellbore seepage collapse needs to be considered. In this embodiment of the invention, the weak-plane failure criterion is used to determine the influence of the compressive strength and in-situ stress of the rock formations on wellbore seepage collapse. The weak-plane failure criterion can be used to determine whether sandstone and mudstone formations near the wellbore have failed. The strength of sandstone and mudstone formations near the wellbore is often much lower than the strength of the sandstone and mudstone formation itself, and in many cases, it essentially controls the overall strength of the sandstone and mudstone formation.

[0045] Based on the wellbore instability mechanism of sandstone and mudstone formations and the results of rock mechanics research, the formation characteristics and rock mechanics parameters influencing the mechanical-chemical collapse of wellbore walls in sandstone and mudstone formations are determined. The influence of rock compressive strength and geostress on seepage collapse of the wellbore is determined based on the weak-plane failure criterion. Therefore, in this embodiment of the invention, a multi-field coupled control model for the wellbore is constructed based on the formation characteristics, rock mechanics parameters, and weak-plane failure criterion influencing wellbore collapse in sandstone and mudstone formations; this multi-field coupled control model is a mechanical-chemical-seepage multi-field coupled control model.

[0046] S130. Based on the trend of formation strength variation with drilling fluid immersion and the weak surface failure criterion, determine the minimum and maximum anti-collapse drilling fluid density when the wellbore is stable in sandy mudstone formations.

[0047] If the drilling fluid density is too low, it will not meet the drilling requirements; if the drilling fluid density is too high, it will cause wellbore instability in sandstone and mudstone formations. Therefore, it is necessary to determine the minimum and maximum anti-collapse drilling fluid densities that can meet the drilling requirements and maintain wellbore stability in sandstone and mudstone formations.

[0048] The multi-field coupled control model is constructed and modeled in software capable of finite element analysis (FEM) calculations. The software used includes, but is not limited to, finite element analysis software such as ANSYS and Abaqus. In the FEM software, the initial in-situ stress field data of the sandstone and mudstone formation are input into the multi-field coupled control model. Based on the experimentally derived trend of formation strength changes after drilling fluid immersion and the weak-plane failure criterion, it is determined whether shear failure occurs in the wellbore rock, thereby determining the minimum and maximum anti-collapse drilling fluid densities required to maintain wellbore stability.

[0049] S140. Based on the abnormal collapse phenomenon of the well wall in sandy mudstone formations, determine the anti-collapse drilling fluid window density for stable and safe drilling in sandy mudstone formations.

[0050] The anti-collapse drilling fluid window density refers to the range of drilling fluid densities required to ensure stable wellbore and safe drilling in sandstone and mudstone formations. Due to abnormal increases in collapse pressure in local well sections, the determined maximum anti-collapse drilling fluid density needs to be appropriately adjusted to determine the optimal anti-collapse drilling fluid window density for stable wellbore and safe drilling in sandstone and mudstone formations. For example, the determined minimum and maximum anti-collapse drilling fluid densities for wellbore stability in sandstone and mudstone formations are 1.15 g / cm³. 3 and 1.20 g / cm 3 Based on the abnormal wellbore collapse phenomenon in sandstone and mudstone formations, the maximum anti-collapse drilling fluid density is adjusted to accommodate the increased abnormal collapse pressure; the maximum anti-collapse drilling fluid density can be adjusted to 1.30 g / cm³. 3 Therefore, the optimal drilling fluid window density for stable and safe drilling in sandstone and mudstone formations is 1.15 g / cm³. 3 ~1.30g / cm 3

[0051] S150. Select the target anti-collapse drilling fluid system according to the drilling scenario requirements, and evaluate the performance of the selected target anti-collapse drilling fluid system based on the constructed anti-collapse drilling fluid evaluation numerical model.

[0052] Depending on the specific drilling scenario, different anti-collapse drilling fluid systems can be selected. For example, as the contact time between the drilling fluid and the formation increases, the penetration depth of the drilling fluid filtrate extends. Considering the increasing trend of formation water content under multi-field coupling conditions, and matching on-site requirements, an anti-collapse drilling fluid system is preferred. Considering the requirements for effectively sealing microfractures, strong inhibition capabilities, good hydrophobic properties, and reducing the intrusion of pore fluid filtrate, experimental statistics are conducted, and a hydrophobic composite salt drilling fluid system is selected.

[0053] Evaluation of anti-collapse drilling fluid is a crucial step, directly impacting drilling safety and efficiency. Numerical models for anti-collapse drilling fluid evaluation serve as an effective tool, helping engineers better understand and predict drilling fluid performance under different conditions, thereby optimizing drilling fluid formulations and improving drilling quality. In this embodiment of the invention, the performance of anti-collapse drilling fluid can be evaluated based on the constructed numerical model for anti-collapse drilling fluid evaluation, according to the needs of different drilling scenarios, to optimize the anti-collapse drilling fluid formulation and improve wellbore stability in sandstone and mudstone formations.

[0054] This invention provides a method for optimizing anti-collapse drilling fluid. Based on the wellbore instability mechanism of sandstone and mudstone formations and rock mechanics research results, it identifies the formation characteristics and rock mechanics parameters that influence wellbore collapse in sandstone and mudstone formations. Based on these characteristics, parameters, and weak-plane failure criteria, a multi-field coupled control model for the wellbore is constructed. Based on the formation strength variation with drilling fluid immersion and the weak-plane failure criteria, the minimum and maximum anti-collapse drilling fluid densities are determined for wellbore stability in sandstone and mudstone formations. Based on abnormal wellbore collapse phenomena in sandstone and mudstone formations, the anti-collapse drilling fluid window density for stable and safe drilling in these formations is determined. A target anti-collapse drilling fluid system is selected based on drilling scenario requirements, and its performance is evaluated using the constructed anti-collapse drilling fluid evaluation numerical model. The technical solution of this invention, based on the lithology and characteristics of sandstone and mudstone, optimizes the anti-collapse drilling fluid system and its specific formulation under multi-field coupled simulation conditions, so as to improve the wellbore stability of sandstone and mudstone formations and effectively reduce the occurrence of complex downhole accidents such as wellbore instability and well leakage.

[0055] Example 2

[0056] Figure 2 is a flowchart of an anti-collapse drilling fluid optimization method provided in an embodiment of the present invention. The embodiments of the present invention further optimize the aforementioned embodiments based on the above embodiments, and can be combined with various optional solutions in one or more of the above embodiments. As shown in Figure 2, the anti-collapse drilling fluid optimization method provided in the embodiments of the present invention may include the following steps:

[0057] S210. Based on the wellbore instability mechanism of sandstone and mudstone formations and the results of rock mechanics research, the formation characteristics and rock mechanics parameters that affect the collapse of wellbore walls in sandstone and mudstone formations were determined.

[0058] In this embodiment of the invention, core samples of the target well area are obtained, core tests are conducted, the wellbore instability mechanism of sandstone and mudstone formations is summarized, a calculation model of rock mechanical properties parameters of the work area is established based on the test results of rock mechanical properties parameters, a modified model is established based on well logging data, a calculation model of geostress parameters is established, the calculation results are verified by referring to the test results of adjacent wells, and a profile of rock mechanical properties parameters and geostress parameters of multiple wells is constructed.

[0059] As an optional but non-limiting implementation, the method of determining the formation characteristics and rock mechanics parameters that affect wellbore collapse in sandstone and mudstone formations based on wellbore instability mechanisms and rock mechanics research results includes, but is not limited to, steps A1-A3:

[0060] Step A1: Obtain core samples from sandstone and mudstone formations and conduct experiments to study the wellbore instability mechanism and rock mechanics of sandstone and mudstone formations.

[0061] Step A2: Based on the research results on the wellbore instability mechanism of sandstone and mudstone formations, determine the formation characteristics that affect the mechanical-chemical collapse of the wellbore in sandstone and mudstone formations; the formation characteristics include formation hydrophilicity and formation porosity.

[0062] Step A3: Based on the results of rock mechanics research, determine the rock mechanics characteristic parameters that affect the mechanical-chemical collapse of the wellbore in sandstone and mudstone formations; the rock mechanics characteristic parameters include elastic modulus, Poisson's ratio, permeability coefficient, and compressive strength.

[0063] The process involved obtaining core samples from the target well area and conducting core tests. For rock sample composition analysis, the samples were washed with oil until fluorescence level four or below, ground until all particles were less than 40 μm in diameter, with the X-ray emission and scattering slits at an angle of 1°, the receiving slit at 0.3 mm, a scanning speed of 2° / min, a sampling step width of 0.02°, and a scanning range of 5°–45°. The contents of elements such as Si, Al, Fe, Mg, K, and Na were determined, and the contents of components such as quartz, silicate minerals, carbonate minerals, and siderite were calculated. Some statistical data from the rock sample composition analysis are shown in Table 1.

[0064] Table 1. Results of rock sample composition analysis

[0065]

[0066]

[0067] Based on the scanning electron microscope results in Figure 3 and the component test results in Figure 4, it can be clearly found that: the mudstone has well-developed pores and fractures with pore diameters between 50 and 300 nm and microcrack widths between 0.1 and 5.0 μm, which provides seepage channels for liquid phase intrusion; the whole rock composition is mainly clay, quartz and plagioclase, and the clay composition is mainly kaolinite, illite, chlorite and illite / montmorillonite mixed layer, and it does not contain any non-montmorillonite. It is a weakly expansive rock with high quartz content and strong brittleness. It is mainly hydrated on the surface, which makes it likely to peel off along the bedding plane or fracture surface, and easily causes the danger of rockfall and collapse.

[0068] Therefore, the wellbore instability mechanism in sandstone and mudstone formations can be summarized as follows: the micro- and nano-scale pores of mudstone are clear as channels for liquid intrusion; the clay component lacks montmorillonite and is weakly expansive and highly brittle; the test results of cation exchange capacity, linear expansion rate, rolling recovery rate, and specific hydrophilicity all indicate that the expansibility is weak and surface hydration is the main process; under the action of hydrophilicity and capillary force, the filtrate intrudes into the pores, causing the wellbore to undergo mechanical-chemical collapse.

[0069] Specifically, a calculation model for the rock mechanics characteristics of the work area was established based on rock mechanics research results and well logging data. Following the wellbore instability mechanism of sandstone and mudstone formations, actual well parameters were incorporated to verify the calculation model. An improved version of the 75 model was used to establish a geostress parameter calculation model. The rock mechanics characteristics of the work area were then incorporated into the geostress parameter calculation model, and the geostress calculation results were verified by referring to geostress test results from adjacent wells. This resulted in the construction of rock mechanics characteristic parameter and geostress parameter profiles for multiple wells.

[0070] It should be noted that the core samples from the reservoir sections of the work area vary greatly. When core samples are taken from different orientations, it is difficult to obtain complete core samples. The same well area does not meet the conditions for carrying out in-situ stress testing. Therefore, in-situ stress testing should be carried out in adjacent well areas with a generally consistent macroscopic block.

[0071] S220. Based on the formation characteristics, rock mechanics parameters, and weak surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for the wellbore is constructed.

[0072] Based on the wellbore instability mechanism in sandstone and mudstone formations, observation of the central region of argillaceous rock samples in the work area revealed a higher probability of fractures. This demonstrates that microfractures not only provide seepage channels for drilling fluid loss but also cause anisotropy in formation properties, affecting wellbore stability. Considering the influence of the compressive strength of the encountered rock formations and the magnitude of in-situ stress on wellbore stability, this embodiment of the invention first conducts core compressive strength experiments to determine core strength parameters.

[0073] As an optional but non-limiting implementation, the wellbore multi-field coupled control model is constructed based on the formation characteristics, rock mechanical parameters, and weak-surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, including but not limited to steps B1-B2:

[0074] Step B1: Based on the research results on the wellbore instability mechanism of sandstone and mudstone formations, determine the formation strength parameters that affect the seepage collapse of wellbore walls in sandstone and mudstone formations.

[0075] Step B2: Based on the formation characteristics, rock mechanics parameters, formation strength parameters, and weak surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for the wellbore is constructed; the multi-field coupled control model for the wellbore is a mechanical-chemical-seepage multi-field coupled control model.

[0076] Compressive strength tests were conducted under confining pressures of 0, 20, and 40 MPa, with core samples taken perpendicular to and at a 50° angle to the bedding plane normal. Core samples were soaked in water-based polymer drilling fluid for 24 and 48 hours before strength tests to better analyze the influence of the drilling fluid on formation strength. When the applied stress in the compressive strength test formed a certain angle with the bedding plane normal, shear failure occurred along the bedding plane, resulting in a significant decrease in compressive strength. After obtaining the compressive strength data under different confining pressures, the core cohesion and internal friction angle were calculated according to the Mohr-Coulomb strength criterion and then substituted into the weak-plane failure criterion for calculation. If the equation holds, it proves that the core compressive strength test phenomenon conforms to the weak-plane failure criterion. The weak-plane failure criterion can be expressed as:

[0077]

[0078] Where σ1 represents the maximum horizontal stress, MPa; σ3 represents the minimum horizontal stress, MPa; φ W β is the internal friction angle of the weak surface; β is the angle between the maximum principal stress and the normal to the weak surface; C W This represents weak surface cohesion, expressed in MPa.

[0079] Furthermore, under the premise of satisfying the weak surface failure criterion, the deformation and failure process of the mudstone near-wellbore formation is simplified into a mechanical-chemical-permeability coupled process. Using tensor representation, a multi-field coupled control model for the wellbore is established. This multi-field coupled control model can be expressed as:

[0080]

[0081] The momentum equations involved are:

[0082]

[0083] The relevant stratigraphic geometric equations are:

[0084]

[0085] Where σ represents the total formation stress matrix, ε represents its tensor, which is dimensionless; D is the stiffness matrix of the elastic constitutive equation of the formation rock, which is dimensionless; ε represents the total strain matrix of the formation, which is also dimensionless; α is the effective stress coefficient, which is dimensionless. The tensor representing pore pressure is dimensionless; M represents the molar mass of the drilling fluid solute, g / mol; ω is the mudstone expansion coefficient, dimensionless; ω is the wellbore fluid density, g / cm³. 3 R is the ideal gas constant, J / (kg·mol); T represents temperature, K; f represents the solute diffusion coefficient, dimensionless; C S represents the dimensionless drilling fluid solute concentration, dimensionless; u represents the rock displacement matrix, dimensionless.

[0086] S230. Based on the trend of formation strength variation with drilling fluid immersion and the weak surface failure criterion, determine the minimum and maximum anti-collapse drilling fluid density when the wellbore is stable in sandy mudstone formations.

[0087] Specifically, the initial in-situ stress field data of the sandstone and mudstone formation is determined, and the initial in-situ stress field data of the sandstone and mudstone formation is used to determine the variation trend of formation strength of the sandstone and mudstone formation with drilling fluid immersion. Based on the variation trend of formation strength of the sandstone and mudstone formation with drilling fluid immersion and the weak surface failure criterion, the minimum anti-collapse drilling fluid density and the maximum anti-collapse drilling fluid density when the wellbore of the sandstone and mudstone formation is stable are determined.

[0088] In one optional embodiment of the present invention, the in-situ stress field data directly borrows the geostress test results of the target reservoir, the Shihezi Formation. Since the target reservoir has a gentle slope structure and relatively weak geological movement, the geostress orientation is determined by referring to adjacent well areas. The in-situ stress field calculation model can adopt a geostress parameter calculation model, with tectonic stress coefficients set to 0.40 and 0.24, respectively. Coefficients such as solute diffusion in sandstone and mudstone can be fitted based on drilling fluid and core soaking data. The aforementioned multi-field coupled control equations of "mechanics-chemistry-seepage" are discretized, and the wellbore stress distribution under multi-field coupling is derived using the finite element numerical method.

[0089] S240. Based on the abnormal collapse phenomenon of the well wall in sandy mudstone formations, determine the anti-collapse drilling fluid window density for stable and safe drilling in sandy mudstone formations.

[0090] In particular, due to the abnormal increase in collapse pressure in some well sections, it is necessary to appropriately adjust the determined maximum anti-collapse drilling fluid density in order to determine the anti-collapse drilling fluid window density for stable wellbore drilling in sandstone and mudstone formations.

[0091] As an optional but non-limiting implementation, the determination of the anti-collapse drilling fluid window density for stable and safe drilling in sandy and mudstone formations based on the abnormal collapse phenomenon of the wellbore in the sandy and mudstone formation includes, but is not limited to, steps C1-C2:

[0092] Step C1: Based on the abnormal collapse phenomenon of the well wall in the sandstone and mudstone formation, determine the collapse pressure coefficient and the fracture pressure coefficient when the well wall in the sandstone and mudstone formation collapses abnormally.

[0093] Step C2: Based on the collapse pressure coefficient and the fracture pressure coefficient, adjust the minimum and maximum anti-collapse drilling fluid densities when the wellbore is stable in sandy mudstone formations, and determine the anti-collapse drilling fluid window density for stable and safe drilling in sandy mudstone formations.

[0094] Based on core strength parameters and geostress analysis results, a multi-field coupled control model of "mechanics-chemistry-seepage" was established to calculate the collapse pressure. The collapse pressure of the near-wellbore formation at depths of 3500 to 5000 m was calculated. Considering the influence of mechanical, seepage, and chemical factors on wellbore stability, and given that this formation is a normal fault with a geostress mechanism, influenced by formation anisotropy, the equivalent density of collapse pressure in the direction of maximum and minimum horizontal stress was calculated. This yielded an equivalent collapse pressure density of approximately 0.90–1.20 g / cm³ in the mudstone of this stratum. 3 .

[0095] In one optional embodiment of the present invention, a formation pore pressure prediction model for the work area is established based on the modified Eaton method, and a collapse pressure and fracture pressure prediction model for the work area is established based on the principles of shear failure and tensile failure. A single-well three-pressure logging interpretation software is developed using Python programming to automatically generate data charts of the three pressures along the well depth, constructing single-well three-pressure profiles for multiple wells. During the logging data processing, the sonic transit time of pure mudstone is selected to establish a normal compaction trend line, taking the average characteristic value on the mudstone layer curve, excluding peak values ​​and cycle jump values. Based on the curve variation characteristics of the single-well three-pressure profile, the anti-collapse drilling fluid window density for safe drilling in sandstone and mudstone formations is determined.

[0096] Taking a well in the work area as an example, as shown in Figure 5, in the single-well three-pressure profile, the fracturing pressure coefficient is 2.00–2.30, the collapse pressure coefficient is mainly 0.90–1.10, and the drilling fluid density is 1.15–1.20 g / cm³. 3To meet wellbore stability requirements; however, an abnormal increase in collapse pressure (1.25–1.30 g / cm³) exists in a local well section (4390–4410 m). 3 If it is necessary to appropriately increase the drilling fluid density, then the density window for anti-collapse drilling fluid during safe drilling is 1.15–1.30 g / cm³. 3 .

[0097] S250. Based on the hydrophilicity and porosity of the formation, determine the target anti-collapse drilling fluid system corresponding to the requirements of different drilling scenarios.

[0098] Taking the target formation as an example, the target formation mainly consists of seven sub-layers within the Shan 1 section, with a vertical depth of 3200–3300 m. Three wells with a diameter of 152.4 mm were drilled, with a well section length of 3625–4525 m and a horizontal section length of 900 m. The measured pressure coefficient of the target formation is 0.81–0.91, indicating a deficit. The leakage pressure coefficient is unknown, and the reservoir temperature is 102.6℃. Before reaching a depth of 4410 m, the drilling fluid density in the work area was 1.15–1.16 g / cm³. 3 Drilling to 4410m, the drilling fluid density increased to 1.18g / cm³. 3 Because the 4390m–4410m section is composed of mudstone with poor stability, repeated drilling and pump stalling in this section led to an abnormally high wellbore enlargement rate. The density at this point is insufficient for wellbore stability; therefore, it needs to be increased to 1.30 g / cm³. 3 The density of the drilling fluid in the vicinity is controlled to prevent wellbore collapse. The lower limit of the design density for the horizontal section of the overall drilling area is 1.16–1.18 g / cm³. 3 The upper limit range is 1.25–1.30 g / cm³. 3 When entering the target layer, the density is set to the higher of the lower limit; when entering the mudstone section, the density is set to the lower of the upper limit, with a density of 1.25 g / cm³. 3 The wellbore must remain stable for at least 400 hours.

[0099] Based on formation hydrophilicity and porosity, target anti-collapse drilling fluid systems are determined for different drilling scenarios. These target anti-collapse drilling fluid systems include, but are not limited to, anti-collapse drilling fluid systems and hydrophobic composite salt drilling fluid systems. For example, as the contact time between the drilling fluid and the formation increases, the penetration depth of the drilling fluid filtrate prolongs. Considering the increasing trend of formation water content under multi-field coupling conditions, and matching on-site requirements, an anti-collapse drilling fluid system is selected. Considering the requirements for effectively sealing microfractures, strong inhibition ability, good hydrophobic performance, and reducing the intrusion of pore filtrate, experimental statistics are conducted, and a hydrophobic composite salt drilling fluid system is selected.

[0100] In order to increase the negative pressure difference in the wellbore, increase the resistance of the drilling fluid filtrate to entering the formation, and reduce the penetration depth of the filtrate, a mixed nano-plugging agent is considered to be added to the anti-collapse drilling fluid to complement its use. Referring to Figure 6, the flexible shell of the nano-plugging agent is easily deformed and squeezed into the fracture, while the rigid core provides support, exhibiting adaptive plugging characteristics. The flexible polymer shell has adhesiveness, which can enhance the adhesion between the agent and the rock, providing a chemical wall-fixing effect and enhancing the interaction force between the agent and the rock.

[0101] The experimental statistics of anti-collapse drilling fluids of different systems are shown in Table 2.

[0102] Table 2. Experimental statistical data of anti-collapse drilling fluids of different systems

[0103] Core Number | Confining Pressure (MPa) | Peak Strength (MPa) | Elastic Modulus (MPa) | Poisson's Ratio | 0-1 (Original) | 0.11 | 0 | 4.70 | 3 | 2.20 | 0.09 | 1-0 (Composite Salt) | 0.12 | 4.80 | 1 | 3.46 | 0.22 | 1-1 (Composite Salt + 2% NF-1) | 0.16 | 2.10 | 2 | 2.70 | 0.05 | 1-2 (Optimized Compound Salt Formula) | 0.19 | 1.21 | 3 | 4.47 | 0.29 surface

[0104] S260. Construct a numerical model for evaluating anti-collapse drilling fluid, conduct performance evaluation of the target anti-collapse drilling fluid system, and determine the formulation standard of the target anti-collapse drilling fluid system.

[0105] Taking the hydrophobic composite salt drilling fluid system as an example, in the process of configuring the hydrophobic composite salt drilling fluid system, the performance of different anti-collapse drilling fluid formulations is evaluated based on the actual anti-collapse hydrophobic drilling fluid usage requirements by screening and optimizing the dosage of the treatment agent.

[0106] The method for selecting the plugging agent is consistent with the principle of selecting the leak plugging agent. The core issue is how to combine plugging particles of different particle sizes to determine the optimal ratio of the plugging agent through experiments. Based on the results of multi-field coupling simulation, small-diameter barite particles are introduced to select weighting materials with multi-gradient particle size distribution, so as to appropriately adjust the particle size distribution of solid phase in the drilling fluid system.

[0107] It should be noted that a reasonable multi-gradient particle size distribution can not only improve the settling stability of drilling fluid, but also transform the sliding friction between solid phases into rolling friction, thereby improving the rheological properties of the anti-collapse drilling fluid system. At the same time, small-particle barite can form a thin and dense mud filter cake through a "closely packed" wall-building method, enhancing the filtration loss reduction capacity of the anti-collapse drilling fluid system and improving the wellbore stability of sandstone and mudstone formations.

[0108] As an optional but non-limiting implementation, the constructed anti-collapse drilling fluid evaluation numerical model includes, but is not limited to, steps D1-D3:

[0109] Step D1: Determine the near-wellbore collapse pressure before and after using the anti-collapse drilling fluid, and determine the change in near-wellbore collapse pressure before and after using the anti-collapse drilling fluid.

[0110] Step D2: Determine the inlet density of the anti-collapse drilling fluid in the wellbore and the outlet density of the anti-collapse drilling fluid after circulation in the wellbore, and determine the density change of the anti-collapse drilling fluid based on the inlet density and the outlet density.

[0111] Step D3: Based on the changes in near-wellbore collapse pressure before and after using anti-collapse drilling fluid, the near-wellbore collapse pressure before using anti-collapse drilling fluid, the inlet density of anti-collapse drilling fluid in the wellbore, and the changes in density of anti-collapse drilling fluid, construct a numerical model for evaluating anti-collapse drilling fluid.

[0112] In this experiment, a base slurry was prepared using 100% clean water, 0.2%–0.5% caustic soda, 3%–5% KCl, 5%–8% industrial salt, 0.1%–0.3% FA-367, and 2.5%–4% pregelatinized starch, with 0.5%–5% nano-plugging agent added to each. The experimental slurry was aged at 100–120℃ for 16 hours, then cooled to room temperature, and its rheological properties were measured. The stability of the anti-collapse drilling fluid at 100–120℃ was evaluated. A multi-field coupled simulation control model was used to calculate the near-wellbore collapse pressure and its variation at this temperature. The converted near-wellbore collapse pressure variation was compared with the corresponding anti-collapse drilling fluid density variation. If the trends were consistent, it proved that the anti-collapse drilling fluid system with a specific nano-plugging agent formulation was suitable for maintaining wellbore stability in the work area.

[0113] Optionally, the numerical model for evaluating the anti-collapse drilling fluid can be expressed as:

[0114]

[0115] Among them, P S1 This represents the near-wellbore collapse pressure without the use of anti-collapse drilling fluid, obtained from a multi-field coupled control model, in MPa; P S2 This indicates the near-wellbore collapse pressure after the use of anti-collapse drilling fluid, obtained from actual measurements, in MPa; ΔP S ρ1 represents the change in near-wellbore collapse pressure before and after using anti-collapse drilling fluid, in MPa; ρ1 represents the inlet density of the anti-collapse drilling fluid in the wellbore, in g / cm³. 3 ρ2 represents the outlet density of the anti-collapse drilling fluid after circulation within the wellbore, in g / cm³. 3Δρ represents the change in density of the anti-collapse drilling fluid, in g / cm³. 3 ;est is the evaluation value of the anti-collapse drilling fluid, which is calculated purely numerically. The closer this value is to 0, the better the performance of the anti-collapse drilling fluid formula used. It is dimensionless.

[0116] In one optional embodiment of the present invention, based on a specific multi-field coupling condition, the content of different components is adjusted in an applicable anti-collapse drilling fluid system. Using the concept of limit conversion, when the density change of the anti-collapse drilling fluid approaches zero infinitely, the specific formula of the anti-collapse drilling fluid with the evaluation value closest to zero is used as the standard. Based on the actual usage, the content ratio and mixing order of each component of the anti-collapse drilling fluid are optimized.

[0117] Optionally, based on the settings and calculation results of multiple multi-field coupling conditions, and referring to the performance and evaluation results of various series of anti-collapse drilling fluids, the final selected anti-collapse drilling fluid formulation standard is: 100% clean water + 0.2% caustic soda + 3% KCl + 5% industrial salt + 0.1% FA-367 + 2.5% pregelatinized starch + 1% SMP-II + 0.3% XC + 1% solid lubricant graphite + 2% emulsified asphalt + 2% GWNF-1 hydrophobic nano-sealant + 2% GWBY-1 hydrophobic inhibitor + barite.

[0118] This invention provides a method for optimizing anti-collapse drilling fluid. By constructing a multi-field coupled control model, the safe window density of the anti-collapse drilling fluid is determined under multi-field coupled simulation conditions for safe drilling in sandstone and mudstone formations. The established optimization method for anti-collapse drilling fluid in sandstone and mudstone formations makes full use of experimental data, has high accuracy, and lays a theoretical foundation for better evaluation of drilling fluid systems and optimization of formulations. It is beneficial for field use and can effectively reduce the occurrence of complex downhole accidents such as wellbore instability and well leakage.

[0119] Example 3

[0120] Figure 7 is a schematic diagram of a drilling fluid optimization device for preventing collapse provided in an embodiment of the present invention. The technical solution of this embodiment is applicable to the optimization of drilling fluid for preventing collapse in sandstone and mudstone under multi-field coupling conditions. This device can be implemented by software and / or hardware and is generally integrated into any electronic device with network communication function, including but not limited to: servers, computers, personal digital assistants, etc. As shown in Figure 7, the drilling fluid optimization device for preventing collapse provided in this embodiment may include: a formation collapse prevention parameter determination module 710, a multi-field coupling control model construction module 720, a drilling fluid density determination module 730, a drilling fluid window density determination module 740, and a drilling fluid performance evaluation module 750; wherein...

[0121] The formation collapse prevention parameter determination module 710 is used to determine the formation characteristics and rock mechanics characteristic parameters that affect the collapse of the well wall in sandy mudstone formations based on the well wall instability mechanism and rock mechanics research results.

[0122] The multi-field coupling control model construction module 720 is used to construct a multi-field coupling control model for the wellbore based on the formation characteristics, rock mechanical parameters and weak surface failure criteria that affect the collapse of the wellbore in sandstone and mudstone formations.

[0123] The anti-collapse drilling fluid density determination module 730 is used to determine the minimum and maximum anti-collapse drilling fluid density when the wellbore of sandstone and mudstone formation is stable, based on the trend of formation strength variation with drilling fluid immersion and the weak surface failure criterion.

[0124] The anti-collapse drilling fluid window density determination module 740 is used to determine the anti-collapse drilling fluid window density for stable and safe drilling in sandy and mudstone formations based on the abnormal collapse phenomenon of the well wall.

[0125] The anti-collapse drilling fluid performance evaluation module 750 is used to select a target anti-collapse drilling fluid system based on the requirements of the drilling scenario, and to evaluate the performance of the selected target anti-collapse drilling fluid system based on the constructed anti-collapse drilling fluid evaluation numerical model.

[0126] Based on the above embodiments, optionally, the stratum collapse prevention parameter determination module is specifically used for:

[0127] Core samples were obtained from sandstone and mudstone formations, and experiments were conducted to study the wellbore instability mechanism and rock mechanics of sandstone and mudstone formations.

[0128] Based on the research results on the wellbore instability mechanism of sandstone and mudstone formations, the formation characteristics that affect the mechanical-chemical collapse of wellbores in sandstone and mudstone formations were determined; the formation characteristics include formation hydrophilicity and formation porosity.

[0129] Based on the results of rock mechanics research, the rock mechanics characteristic parameters that affect the mechanical-chemical collapse of wellbore in sandstone and mudstone formations were determined; the rock mechanics characteristic parameters include elastic modulus, Poisson's ratio, permeability coefficient, and compressive strength.

[0130] Based on the above embodiments, optionally, the multi-field coupling control model construction module is specifically used for:

[0131] Based on the research results on the wellbore instability mechanism of sandstone and mudstone formations, the formation strength parameters that affect the seepage collapse of wellbore in sandstone and mudstone formations were determined.

[0132] Based on the formation characteristics, rock mechanics parameters, formation strength parameters, and weak surface failure criteria that affect wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for the wellbore is constructed; the multi-field coupled control model for the wellbore is a mechanical-chemical-seepage multi-field coupled control model.

[0133] Based on the above embodiments, optionally, the anti-collapse drilling fluid window density determination module is specifically used for:

[0134] Based on the abnormal collapse phenomenon of the well wall in sandstone and mudstone formations, the collapse pressure coefficient and the fracture pressure coefficient during abnormal well wall collapse in sandstone and mudstone formations were determined.

[0135] Based on the collapse pressure coefficient and the fracture pressure coefficient, the minimum and maximum anti-collapse drilling fluid densities are adjusted for wellbore stability in sandstone and mudstone formations to determine the anti-collapse drilling fluid window density for stable and safe drilling in sandstone and mudstone formations.

[0136] Based on the above embodiments, optionally, the anti-collapse drilling fluid performance evaluation module is specifically used for:

[0137] Based on the hydrophilicity and porosity of the formation, the target anti-collapse drilling fluid system is determined for different drilling scenarios; the target anti-collapse drilling fluid system includes an anti-collapse drilling fluid system and a hydrophobic composite salt drilling fluid system;

[0138] A numerical model for evaluating anti-collapse drilling fluid was constructed to assess the performance of the target anti-collapse drilling fluid system and determine the formulation standards for the target anti-collapse drilling fluid system.

[0139] Based on the above embodiments, optionally, the anti-collapse drilling fluid performance evaluation module is further specifically used for:

[0140] Determine the near-wellbore collapse pressure before and after using the anti-collapse drilling fluid, and determine the change in near-wellbore collapse pressure before and after using the anti-collapse drilling fluid.

[0141] Determine the inlet density of the anti-collapse drilling fluid in the wellbore and the outlet density of the anti-collapse drilling fluid after circulation in the wellbore, and determine the density change of the anti-collapse drilling fluid based on the inlet density and the outlet density;

[0142] A numerical model for evaluating anti-collapse drilling fluid is constructed based on the changes in near-wellbore collapse pressure before and after the use of anti-collapse drilling fluid, the near-wellbore collapse pressure before the use of anti-collapse drilling fluid, the inlet density of anti-collapse drilling fluid in the wellbore, and the changes in density of anti-collapse drilling fluid.

[0143] Based on the above embodiments, optionally, the numerical model for evaluating the anti-collapse drilling fluid can be expressed as:

[0144]

[0145] Among them, P S1 This represents the near-wellbore collapse pressure without the use of anti-collapse drilling fluid, obtained from a multi-field coupled control model, in MPa; P s2 This indicates the near-wellbore collapse pressure after the use of anti-collapse drilling fluid, obtained from actual measurements, in MPa; ΔP S ρ1 represents the change in near-wellbore collapse pressure before and after using anti-collapse drilling fluid, in MPa; ρ1 represents the inlet density of the anti-collapse drilling fluid in the wellbore, in g / cm³. 3 ρ2 represents the outlet density of the anti-collapse drilling fluid after circulation within the wellbore, in g / cm³. 3 Δρ represents the change in density of the anti-collapse drilling fluid, in g / cm³. 3 ;est is the evaluation value of the anti-collapse drilling fluid, which is calculated purely numerically. The closer this value is to 0, the better the performance of the anti-collapse drilling fluid formula used. It is dimensionless.

[0146] The anti-collapse drilling fluid optimization device provided in this embodiment of the invention can execute the anti-collapse drilling fluid optimization method provided in any of the above embodiments of the invention, and has the corresponding functions and beneficial effects of executing the anti-collapse drilling fluid optimization method. For detailed process, please refer to the relevant operations of the anti-collapse drilling fluid optimization method in the foregoing embodiments.

[0147] Example 4

[0148] Figure 8 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0149] As shown in Figure 8, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0150] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0151] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the anti-collapse drilling fluid optimization method.

[0152] In some embodiments, the anti-collapse drilling fluid optimization method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the anti-collapse drilling fluid optimization method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the anti-collapse drilling fluid optimization method by any other suitable means (e.g., by means of firmware).

[0153] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0155] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0156] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0157] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0158] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0159] Example 5

[0160] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the anti-collapse drilling fluid optimization method as provided in any embodiment of this application.

[0161] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0162] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0163] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for optimizing drilling fluid to prevent collapse, characterized in that, The method includes: determining the formation characteristics and rock mechanics parameters that affect wellbore collapse in sandstone and mudstone formations based on wellbore instability mechanisms and rock mechanics research results; constructing a multi-field coupled control model for the wellbore based on the formation characteristics, rock mechanics parameters, and weak-plane failure criteria that affect wellbore collapse in sandstone and mudstone formations; determining the minimum and maximum anti-collapse drilling fluid densities for wellbore stability in sandstone and mudstone formations based on the trend of formation strength variation with drilling fluid immersion and the weak-plane failure criteria; determining the anti-collapse drilling fluid window density for stable and safe drilling in sandstone and mudstone formations based on abnormal wellbore collapse phenomena; selecting a target anti-collapse drilling fluid system according to drilling scenario requirements, and evaluating the performance of the selected target anti-collapse drilling fluid system based on the constructed anti-collapse drilling fluid evaluation numerical model.

2. The method according to claim 1, characterized in that, Based on the wellbore instability mechanism and rock mechanics research results of sandstone and mudstone formations, the formation characteristics and rock mechanics parameters influencing wellbore collapse in sandstone and mudstone formations are determined. This includes: obtaining sandstone and mudstone core samples and conducting experiments on the wellbore instability mechanism and rock mechanics of sandstone and mudstone formations; determining the formation characteristics influencing the mechanical-chemical collapse of sandstone and mudstone formations based on the wellbore instability mechanism research results; these formation characteristics include formation hydrophilicity and formation porosity; and determining the rock mechanics parameters influencing the mechanical-chemical collapse of sandstone and mudstone formations based on the rock mechanics research results; these rock mechanics parameters include elastic modulus, Poisson's ratio, permeability coefficient, and compressive strength.

3. The method according to claim 1, characterized in that, Based on the formation characteristics, rock mechanics parameters, and weak-plane failure criteria that influence wellbore collapse in sandstone and mudstone formations, a multi-field coupled control model for the wellbore is constructed. This model includes: determining the formation strength parameters that influence seepage collapse in sandstone and mudstone formations based on research results on wellbore instability mechanisms; and constructing a multi-field coupled control model for the wellbore based on the formation characteristics, rock mechanics parameters, formation strength parameters, and weak-plane failure criteria that influence wellbore collapse in sandstone and mudstone formations. The multi-field coupled control model for the wellbore is a mechanical-chemical-seepage multi-field coupled control model.

4. The method according to claim 1, characterized in that, The method for determining the anti-collapse drilling fluid window density for stable and safe drilling in sandy and mudstone formations based on the abnormal collapse phenomenon of the wellbore includes: determining the collapse pressure coefficient and the fracturing pressure coefficient during abnormal collapse of the wellbore in sandy and mudstone formations based on the abnormal collapse phenomenon; and adjusting the minimum and maximum anti-collapse drilling fluid densities for stable wellbore in sandy and mudstone formations based on the collapse pressure coefficient and the fracturing pressure coefficient, thereby determining the anti-collapse drilling fluid window density for stable and safe drilling in sandy and mudstone formations.

5. The method according to claim 1, characterized in that, The process involves selecting a target anti-collapse drilling fluid system based on drilling scenario requirements, and evaluating the performance of the selected system using a constructed anti-collapse drilling fluid evaluation numerical model. This includes: determining the target anti-collapse drilling fluid system corresponding to different drilling scenario requirements based on formation hydrophilicity and formation porosity; the target anti-collapse drilling fluid system includes an anti-collapse drilling fluid system and a hydrophobic composite salt drilling fluid system; constructing an anti-collapse drilling fluid evaluation numerical model to evaluate the performance of the target anti-collapse drilling fluid system, and determining the formulation standards for the target anti-collapse drilling fluid system.

6. The method according to claim 1, characterized in that, The constructed numerical model for evaluating anti-collapse drilling fluid includes: determining the near-wellbore collapse pressure before and after using the anti-collapse drilling fluid, and determining the change in near-wellbore collapse pressure before and after using the anti-collapse drilling fluid; determining the inlet density of the anti-collapse drilling fluid in the wellbore and the outlet density of the anti-collapse drilling fluid after circulation in the wellbore, and determining the change in density of the anti-collapse drilling fluid based on the inlet density and outlet density; and constructing the numerical model for evaluating anti-collapse drilling fluid based on the change in near-wellbore collapse pressure before and after using the anti-collapse drilling fluid, the near-wellbore collapse pressure before using the anti-collapse drilling fluid, the inlet density of the anti-collapse drilling fluid in the wellbore, and the change in density of the anti-collapse drilling fluid.

7. The method according to claim 1, characterized in that, The numerical model for evaluating anti-collapse drilling fluid can be expressed as follows: Among them, P S1 This represents the near-wellbore collapse pressure without the use of anti-collapse drilling fluid, obtained from a multi-field coupled control model, in MPa; P S2 This indicates the near-wellbore collapse pressure after the use of anti-collapse drilling fluid, obtained from actual measurements, in MPa; ΔP S ρ1 represents the change in near-wellbore collapse pressure before and after using anti-collapse drilling fluid, in MPa; ρ1 represents the inlet density of the anti-collapse drilling fluid in the wellbore, in g / cm³. 3 ρ2 represents the outlet density of the anti-collapse drilling fluid after circulation within the wellbore, in g / cm³. 3 Δρ represents the change in density of the anti-collapse drilling fluid, in g / cm³. 3 ;est is the evaluation value of the anti-collapse drilling fluid, which is calculated purely numerically. The closer this value is to 0, the better the performance of the anti-collapse drilling fluid formula used. It is dimensionless.

8. A drilling fluid optimization device for preventing well collapse, characterized in that, The device includes: a formation anti-collapse parameter determination module, used to determine the formation characteristics and rock mechanics parameters affecting wellbore collapse in sandy mudstone formations based on wellbore instability mechanisms and rock mechanics research results; a multi-field coupling control model construction module, used to construct a wellbore multi-field coupling control model based on the formation characteristics, rock mechanics parameters, and weak-surface failure criteria affecting wellbore collapse in sandy mudstone formations; and an anti-collapse drilling fluid density determination module, used to determine the formation strength of sandy mudstone formations as a function of drilling fluid immersion. Based on the trend of degradation and the failure criterion of weak surfaces, the minimum and maximum anti-collapse drilling fluid densities are determined when the wellbore is stable in sandstone and mudstone formations. An anti-collapse drilling fluid window density determination module is used to determine the anti-collapse drilling fluid window density for stable and safe drilling in sandstone and mudstone formations based on abnormal wellbore collapse phenomena. An anti-collapse drilling fluid performance evaluation module is used to select a target anti-collapse drilling fluid system according to drilling scenario requirements and to evaluate the performance of the selected target anti-collapse drilling fluid system based on the constructed anti-collapse drilling fluid evaluation numerical model.

9. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the anti-collapse drilling fluid optimization method according to any one of claims 1-7.

10. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the anti-collapse drilling fluid optimization method as described in any one of claims 1-7.

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