Method and system for predicting sand production of gas well of ultra-deep ultrahigh-pressure fractured low-porosity sandstone gas reservoir

Abstract

The invention belongs to the technical field of gas reservoir development, and discloses an ultra-deep ultrahigh-pressure fractured low-porosity sandstone gas reservoir gas well sand production prediction method and system.The prediction method comprises the steps that it is assumed that a plastic area exists in surrounding rock of a to-be-measured well, and the plastic area is of an oval structure; the method comprises the following steps: acquiring the length of a major semi-axis of a plastic region of an elliptical structure by utilizing the acquired borehole radius, rock cohesive force, rock internal friction angle, bottom hole pressure, maximum horizontal ground stress and minimum horizontal ground stress of a borehole to be measured and combining a pre-constructed projection model of the plastic region of the elliptical structure, and comparing the length of the major semi-axis with the borehole radius, determining whether the to-be-measured well produces sand or not; and when the to-be-measured well produces sand, acquiring the radius of the plastic region by using a pre-constructed plastic region radius model, and completing the sand production prediction of the ultra-deep ultrahigh-pressure fractured low-porosity sandstone gas reservoir gas well. The prediction result of the method is accurate and reliable.

Description

Technical Field

[0001] This invention belongs to the field of gas reservoir development technology and relates to a method and system for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured low-porosity sandstone gas reservoirs. Background Technology

[0002] During the extraction of sandstone gas reservoirs, the production of large amounts of sand can occur due to soft formations or other extraction factors, posing a significant threat to gas well production. Sand particles may settle at the bottom of the well, forming sand plugs, leading to reduced or even halted gas production. Sand-bearing fluids have strong erosive properties, and the formation sand particles carried by high-speed gas can exacerbate the abrasion of downhole and surface equipment. More seriously, under prolonged sand production, large cavities can form outside the casing, causing an imbalance of forces between the internal and external systems. This can lead to sudden formation collapse, causing casing shrinkage and deformation at best, and casing breakage and destruction at worst, rendering the gas well unusable and severely impacting the safe and stable production of the gas field.

[0003] Many factors influence sand production in gas wells, which can be broadly categorized into three main types: ① Geomechanical factors, including in-situ stress state (vertical and original horizontal stress), pore pressure, in-situ temperature, and geological structure; ② Comprehensive properties of sandstone reservoirs, including well depth, sandstone strength and deformation characteristics, porosity, permeability, drainage radius, fluid composition (oil, gas, and water content and distribution), clay content, rock composition, particle size and shape, and compaction (cementation); ③ Engineering and technological factors, including completion type, wellbore structural parameters (well depth, inclination, azimuth, and diameter), performance of completion / fracturing fluids, production enhancement measures (fracturing, acidizing, etc.), production process parameters (flowback regime, production flow rate, differential pressure, and flow rate), reservoir damage (increased skin coefficient), shut-in scheme, artificial lift technology, reservoir depletion, and cumulative sand production. Among these, geomechanical factors and the comprehensive properties of sandstone reservoirs are natural factors; engineering and technological factors (completion factors and production factors) are human factors.

[0004] The geological conditions of ultra-deep, ultra-high-pressure fractured, low-porosity sandstone gas reservoirs are influenced by multiple phases of complex tectonic movements. These reservoirs exhibit well-developed microfractures and faults within regional tectonic zones, and diverse reservoir space types, resulting in extremely complex geological and engineering conditions. Currently, when predicting sand production in gas wells of this type, to reduce the difficulty of prediction, the wellbore rock is assumed to be in a completely elastic state, ignoring the plastic region of the wellbore. This leads to discrepancies between the predicted and actual conditions, affecting the accuracy of the predictions and making it difficult to provide accurate reference for actual sand production prediction in the field. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method and system for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, thereby solving the technical problem of poor accuracy in predicting sand production in gas wells of gas reservoirs in the prior art.

[0006] This invention is achieved through the following technical solution: A method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs includes the following steps: The wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested are obtained, and it is assumed that there is a plastic region in the surrounding rock of the wellbore to be tested, and the plastic region has an elliptical structure. By using the obtained wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the well to be tested, and combined with the pre-constructed projection model of the elliptical plastic region, the length of the major semi-axis of the elliptical plastic region is obtained. The length of the major semi-axis is compared with the wellbore radius to determine whether the well to be tested is producing sand. When sand is produced in the wellbore to be tested, the radius of the plastic region is obtained by using a pre-constructed plastic region radius model, and the sand production prediction of the gas well in the ultra-deep and ultra-high pressure fractured low-porosity sandstone gas reservoir is completed.

[0007] Preferably, the length of the semi-major axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Then, the prediction results are compared using the combined modulus method. When the comparison results are consistent, the plastic region radius is obtained using a pre-constructed plastic region radius model to complete the sand production prediction of the gas well in the ultra-deep ultra-high pressure fractured low-porosity sandstone gas reservoir.

[0008] Preferably, the pre-constructed projection model of the elliptical structure's plastic region is as follows:

[0009]

[0010] in, For the maximum horizontal ground stress, For minimum horizontal ground stress, For rock cohesion, The internal friction angle of the rock. This refers to the bottom hole pressure.

[0011] Preferably, the semi-major axis length of the elliptical plastic region is obtained by combining a pre-constructed projection model of the elliptical plastic region. Specifically, when b > 0, the semi-major axis length of the ellipse is... When b < 0, the semi-major axis of the ellipse is .

[0012] Preferably, the length of the major semi-axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Specifically, when the length of the major semi-axis is greater than the wellbore radius, a plastic zone appears near the well wall and sand is produced in the well; conversely, when the length of the major semi-axis is less than the wellbore radius, no plastic zone appears near the well wall and no sand is produced in the well.

[0013] Preferably, the pre-constructed plastic region radius model is as follows:

[0014] In the formula, The radius of the plastic region, Where is the wellbore radius.

[0015] A sand production prediction system for gas wells in ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs includes: The data acquisition module is used to acquire the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and assumes that there is a plastic region in the surrounding rock of the wellbore to be tested, and that the plastic region has an elliptical structure. The first data processing module is used to obtain the semi-major axis length of the elliptical plastic region by using the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and combining it with the pre-constructed projection model of the elliptical plastic region. The semi-major axis length is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. The second data processing module is used to obtain the radius of the plastic region using a pre-constructed plastic region radius model when the wellbore to be tested produces sand, thereby completing the sand production prediction of the gas well in the ultra-deep, ultra-high pressure fractured low-porosity sandstone gas reservoir.

[0016] A computer device includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.

[0017] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method.

[0018] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0019] Compared with the prior art, the present invention has the following beneficial technical effects: This invention discloses a method for predicting sand production in ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs. First, the method sets the surrounding rock of the wellbore as not perfectly elastic and assumes an elliptical structure for the plastic region. This assumption better reflects the complex mechanical properties of underground rocks, thereby improving the accuracy and reliability of the prediction. Second, this method not only considers the basic factor of the wellbore radius but also comprehensively considers multiple key parameters such as rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress, and minimum horizontal stress. The introduction of these parameters allows the prediction model to more comprehensively and accurately reflect the mechanical state of the surrounding rock and the risk of sand production. Furthermore, by constructing an elliptical plastic region projection model and a plastic region radius model, this method can quickly and accurately calculate the semi-major axis length and radius of the plastic region, effectively determining whether the wellbore is producing sand. This method not only improves prediction efficiency but also significantly enhances prediction accuracy. This method obtains key parameters and combines them with a pre-constructed elliptical structure plastic region projection model and plastic region radius model to accurately predict sand production, ensuring the accuracy and reliability of the prediction results.

[0020] Furthermore, another inventive point of this invention is that the length of the semi-major axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Then, the invention also includes comparing the prediction results using the combined modulus method. When the comparison results are consistent, the plastic region radius is obtained using a pre-constructed plastic region radius model to complete the sand production prediction of the ultra-deep ultra-high pressure fractured low-porosity sandstone gas reservoir. This avoids the prediction limitations of a single method and further improves the accuracy of the prediction. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to the present invention. Figure 2 This is a projection of the plastic zone in the method for predicting sand production in ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs in this invention. Figure 3 This is a schematic diagram of the structure of a sand production prediction system for an ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoir according to the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0025] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0026] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0028] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0029] The present invention will now be described in further detail with reference to the accompanying drawings: Example 1 like Figure 1 As shown, this invention discloses a method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, comprising the following steps: S1: Obtain the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and assume that there is a plastic region in the surrounding rock of the wellbore to be tested, and that the plastic region has an elliptical structure. In a more preferred embodiment, the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal in-situ stress, and minimum horizontal in-situ stress of the well to be tested are obtained. Specifically, the gas reservoir is first divided into regions according to the downhole depth, and then the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal in-situ stress, and minimum horizontal in-situ stress of each region are obtained. The regions can be divided at 10m intervals.

[0030] S2: Using the obtained wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the well to be tested, and combined with the pre-constructed elliptical plastic region projection model, the length of the major semi-axis of the elliptical plastic region is obtained. The length of the major semi-axis is compared with the wellbore radius to determine whether the well to be tested is producing sand, thus realizing the qualitative prediction process of the sand production situation of the well to be tested. The pre-constructed projection model of the elliptical structure's plastic region is as follows:

[0031]

[0032] in, For the maximum horizontal ground stress, For minimum horizontal ground stress, For rock cohesion, The internal friction angle of the rock. This refers to the bottom hole pressure.

[0033] The length of the semi-major axis of the elliptical plastic region is obtained by combining a pre-constructed projection model of the elliptical structure's plastic region. Specifically, when b > 0, the length of the semi-major axis of the ellipse is... The minor semi-axis of the ellipse is And at this time, the major semi-axis of the ellipse in the plastic region is... Axial direction; When b < 0, the semi-major axis of the ellipse is The minor semi-axis of the ellipse For, and at this time the major semi-axis of the ellipse of the plastic region is in Axial direction; When b=0, the ellipse degenerates into a circular region with radius c.

[0034] The length of the major semi-axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Specifically, when the length of the major semi-axis is greater than the wellbore radius, a plastic zone appears near the well wall. The formation stability in the plastic zone is damaged, which leads to sand production in the well. Conversely, if the length of the major semi-axis is less than the well wall radius, no plastic zone appears near the well wall and no sand is produced in the well.

[0035] After this step, the sand production of the wellbore can be predicted using the combined modulus method. When the prediction result of the combined modulus method is consistent with the prediction result of the stress analysis method described above, proceed to step S3 below. If they are inconsistent, first adjust the longitudinal wave sonic transit time of the rock in the combined modulus method. Combined elastic modulus with rock The longitudinal wave transit time of rocks was measured using equipment with higher measurement accuracy. Combined elastic modulus with rock Furthermore, multiple sets of data were collected using a multi-point sampling method, and the average value of these multiple sets of data was taken to obtain the new longitudinal wave sonic transit time of the rock. Combined elastic modulus with rock When adjusting the longitudinal wave time difference of the rock Combined elastic modulus with rock If the result still differs from the prediction in step three, then the wellbore pressure should be reassessed. Testing was conducted, and more precise equipment was used to measure the bottom hole pressure. Simultaneously, multiple sets of data were collected using multi-point sampling to comprehensively calculate the new bottom hole pressure. Then, the semi-major axis of the elliptical plastic region is obtained again using the pre-constructed projection model of the elliptical plastic region, and the sand condition is re-determined until the prediction results of the method in this invention, namely the stress analysis method and the combined modulus method, are consistent. Then, the following step S3 is performed.

[0036] When using the combined modulus method to predict sand production, the prediction formula for the combined modulus method is as follows:

[0037] in, The combined elastic modulus of the rock; The bulk density of the rocks in the strata; The longitudinal wave time difference of the rock.

[0038] The prediction process for whether sand will be produced using the combined modulus method is as follows: when ≥2*10 4 At MPa, it is considered that no sand was produced; when 2*10 4 MPa > >1.5*10 4At MPa, slight sand production is considered. ≤1.5*10 4 At a pressure of MPa, severe sand production is considered.

[0039] S3: When sand is produced in the wellbore to be tested, the radius of the plastic region is obtained by using the pre-constructed plastic region radius model, and the sand production prediction of the gas well in the ultra-deep and ultra-high pressure fractured low-porosity sandstone gas reservoir is completed.

[0040] The pre-constructed plastic region radius model is as follows:

[0041] In the formula, The radius of the plastic region, Where is the wellbore radius.

[0042] Example 2 A method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, the method comprising: Step 1: Area division.

[0043] This invention first divides the gas reservoir into zones based on downhole depth, using 10-meter intervals as the standard division unit. The purpose of this step is to more precisely adapt to changes in geological conditions and provide an accurate regional background for subsequent parameter detection and analysis. Step 2: Key parameter detection.

[0044] Within each defined region, key parameters such as wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress, and minimum horizontal stress were sequentially detected and recorded. These parameters form the basis for assessing wellbore surrounding rock stability and predicting sand production behavior. Step 3: Calculate the radius of the plastic region.

[0045] Using the parameters detected above, the radius of the plastic region is calculated using a specific formula, which is the pre-constructed plastic region radius model in Example 1. This step is crucial for understanding the deformation and failure characteristics of the wellbore surrounding rock after being subjected to stress. Step 4: Stress analysis and establishment of elliptical trajectory equations.

[0046] Non-uniform stress analysis is used to determine the interface between the elastic and plastic regions, assuming that the projection surface of the plastic region is an ellipse, such as... Figure 2 As shown. Further, the trajectory equation of the ellipse is established, namely the pre-constructed elliptical structure plastic region projection model in Example 1. This equation is the key mathematical model for predicting whether a plastic region will appear near the wellbore. Step 5: Predicting and judging sand production.

[0047] By comparing the calculated semi-major axis of the ellipse with the wellbore radius, it is determined whether a plastic zone exists near the wellbore, thereby predicting whether sand will be produced in the well. This step is directly related to gas well safety production and maintenance decisions. If sand production is determined, the radius of the plastic zone is obtained using the pre-constructed plastic zone radius model from step three.

[0048] In this invention, a preferred approach is to introduce a combined modulus method for prediction based on stress analysis, and then compare the prediction results with those of the stress analysis method to verify and improve the accuracy of the prediction. When the prediction results of the combined modulus method are inconsistent with those of the stress analysis method, the longitudinal wave transit time and the combined elastic modulus of the rock are adjusted, and high-precision equipment and multi-point sampling methods are used to obtain more accurate data. During the prediction process, multiple factors are comprehensively considered, including the orifice normal pressure gradient, geostress, load history, rock deformation and failure characteristics, orifice geometry and density, well inclination angle, capillary pressure, and the physicochemical effects of rock water. The introduction of these factors enhances the adaptability and accuracy of the prediction model.

[0049] The technical method in this invention provides a more scientific prediction method for more accurately simulating the actual situation of sand production in gas wells. Through the implementation of the above-mentioned technical means, this invention can effectively improve the accuracy of sand production prediction in gas wells, providing strong technical support for the safe and efficient development of gas reservoirs. This invention sets the surrounding rock of the wellbore as a non-perfectly elastic state and comprehensively utilizes multiple analytical methods and considers multiple influencing factors, significantly improving the scientific nature and practicality of the prediction.

[0050] The sand production prediction method for ultra-deep, ultra-high pressure fractured low-porosity sandstone gas reservoirs provided by this invention sets the surrounding rock of the wellbore as not fully elastic during prediction, which is more in line with the actual situation and thus improves the accuracy of prediction. At the same time, this invention uses stress analysis and combined modulus methods to predict sand production in gas wells, avoiding the limitations of single-method prediction and further improving the accuracy of prediction.

[0051] Example 3 To further explain the method in this invention, the following embodiments are provided: A method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs includes the following steps: Step 1: Sequentially check the wellbore radius Rock cohesion internal friction angle of rock Bottom hole pressure Maximum horizontal ground stress Minimum horizontal stress The interface between the elastic and plastic regions is determined by non-uniform stress, and isotropic, and the projection surface of the plastic region is determined to be an ellipse. Step 2: The equation of the ellipse's trajectory is

[0052] in

[0053] In the formula, For the maximum horizontal ground stress, For minimum horizontal ground stress, For rock cohesion, The internal friction angle of the rock. This refers to the bottom hole pressure.

[0054] When b > 0, the semi-major axis of the ellipse is The minor semi-axis of the ellipse is And at this time, the major half-axis is Axial direction; When b < 0, the semi-major axis of the ellipse is The minor semi-axis of the ellipse is And at this time, the major half-axis is Axial direction; Step 3: Compare the calculated semi-major axis of the ellipse with the wellbore radius. When the semi-major axis of the ellipse is less than or equal to the wellbore radius, no plastic zone appears near the well wall. When the semi-major axis of the ellipse is greater than the wellbore radius, a plastic zone appears near the well wall, and sand is produced in the well at this time.

[0055] Step 4: Divide the gas reservoir into zones based on the downhole depth; Step 5: Calculate the radius of the plastic region using the following formula. ;

[0056] The above steps are the stress analysis method. The stress analysis method can intuitively and accurately predict whether a gas well will produce sand. Moreover, in the prediction, the surrounding rock of the well wall is not set to a completely elastic state. That is, the surrounding rock of the well wall has plastic and elastic regions, which makes the consideration of the surrounding rock of the well wall more in line with the actual situation, thereby improving the accuracy of the prediction.

[0057] In step four, the interval for dividing the gas reservoir into regions is 10m. When the rock strata are clearly defined, the regions are divided according to the rock strata; when the rock strata are densely layered, the division interval is reduced according to the actual situation.

[0058] The internal friction angle ∂ of the rock is calculated using the cotton cloth formula, specifically:

[0059] in It is the dip angle of the rock mass. For the maximum horizontal ground stress, For minimum horizontal ground stress, It is the cohesion of the rock, which is determined by taking multiple samples and averaging them when measuring the dip angle.

[0060] The wellbore radius Rock cohesion Bottom hole pressure Maximum horizontal ground stress Minimum horizontal stress The detection methods all employ existing technologies.

[0061] Example 4 To further explain the method in this invention, the following embodiments are provided: A method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs includes the following steps: Step 1: Sequentially check the wellbore radius Rock cohesion internal friction angle of rock Bottom hole pressure Maximum horizontal ground stress Minimum horizontal stress The interface between the elastic and plastic regions is determined by non-uniform stress, and isotropic, and the projection surface of the plastic region is determined to be an ellipse. Step 2: The equation of the ellipse's trajectory is

[0062] in

[0063] In the formula, For the maximum horizontal ground stress, For minimum horizontal ground stress, For rock cohesion, The internal friction angle of the rock. This refers to the bottom hole pressure.

[0064] When b > 0, the semi-major axis of the ellipse is The minor semi-axis of the ellipse is And at this time, the major half-axis is Axial direction; When b < 0, the semi-major axis of the ellipse is The minor semi-axis of the ellipse is And at this time, the major half-axis is Axial direction; Step 3: Compare the calculated semi-major axis of the ellipse with the wellbore radius. When the semi-major axis of the ellipse is less than or equal to the wellbore radius, no plastic zone appears near the well wall. When the semi-major axis of the ellipse is greater than the wellbore radius, a plastic zone appears near the well wall. At this time, sand is produced in the well, thus completing the qualitative judgment of the sand production situation.

[0065] Following step three, the combined modulus method is used to predict sand production, determining whether sand is being produced in the wellbore. The qualitative results from the combined modulus method are then compared with those from step three to improve the accuracy of the prediction. When the prediction results from the combined modulus method differ from those from those from step three, the longitudinal wave sonic transit time of the rock in the combined modulus method is first adjusted. Combined elastic modulus with rock The longitudinal wave transit time of rocks was measured using equipment with higher measurement accuracy. Combined elastic modulus with rock Furthermore, multiple sets of data were collected using a multi-point sampling method, and the average value of these multiple sets of data was taken to obtain the new longitudinal wave sonic transit time of the rock. Combined elastic modulus with rock When adjusting the longitudinal wave time difference of the rock Combined elastic modulus with rock If the result still differs from the prediction in step three, then the wellbore pressure should be reassessed. Testing was conducted, and more precise equipment was used to measure the bottom hole pressure. Simultaneously, multiple sets of data were collected using multi-point sampling to comprehensively calculate the new bottom hole pressure. Then, the semi-major axis of the elliptical plastic region is obtained again using the pre-constructed projection model of the elliptical plastic region, and the sand condition is re-evaluated until the prediction results of the method in this invention, namely the stress analysis method and the combined modulus method, are consistent.

[0066] When making predictions, factors such as orifice normal pressure gradient, geostress, load history, rock deformation and rock failure characteristics, orifice geometry and density, well inclination angle, capillary pressure and rock water physicochemical effects can be fully considered. One or more factors can be added as variables and introduced into the entire prediction scheme. The introduced variables can be compared to further increase the accuracy of the prediction.

[0067] When using the combined modulus method to predict sand production, the prediction formula for the combined modulus method is as follows:

[0068] in, The combined elastic modulus of the rock; The bulk density of the rocks in the strata; The longitudinal wave time difference of the rock.

[0069] The combined elastic modulus of the rock Bulk density of strata rocks This was determined based on previous well logging data.

[0070] The prediction process for whether sand will be produced using the combined modulus method is as follows: when ≥2*10 4 At MPa, it is considered that no sand was produced; when 2*10 4 MPa > >1.5*10 4 At MPa, slight sand production is considered. ≤1.5*10 4 At a pressure of MPa, severe sand production is considered.

[0071] If the above predictions are consistent, proceed with the following steps.

[0072] Step 4: Divide the gas reservoir into zones based on the downhole depth; Step 5: Calculate the radius of the plastic region using the following formula. Complete the quantitative prediction process for wellbore sand production:

[0073] The above steps are the stress analysis method. The stress analysis method can intuitively and accurately predict whether a gas well will produce sand. Moreover, in the prediction, the surrounding rock of the well wall is not set to a completely elastic state. That is, the surrounding rock of the well wall has plastic and elastic regions, which makes the consideration of the surrounding rock of the well wall more in line with the actual situation, thereby improving the accuracy of the prediction.

[0074] In step four, the interval for dividing the gas reservoir into regions is 10m. When the rock strata are clearly defined, the regions are divided according to the rock strata; when the rock strata are densely layered, the division interval is reduced according to the actual situation.

[0075] The internal friction angle ∂ of the rock is calculated using the cotton cloth formula, specifically:

[0076] in It is the dip angle of the rock mass. For the maximum horizontal ground stress, For minimum horizontal ground stress, It is the cohesion of the rock, which is determined by taking multiple samples and averaging them when measuring the dip angle. The maximum and minimum horizontal ground stresses in this invention can also be expressed as the maximum and minimum horizontal principal stresses.

[0077] The wellbore radius Rock cohesion Bottom hole pressure Maximum horizontal ground stress Minimum horizontal stress The detection methods all employ existing technologies.

[0078] Example 5 Furthermore, such as Figure 3 As shown, the present invention also provides a sand production prediction system for gas wells in ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, comprising: The data acquisition module is used to acquire the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and assumes that there is a plastic region in the surrounding rock of the wellbore to be tested, and that the plastic region has an elliptical structure. The first data processing module is used to obtain the semi-major axis length of the elliptical plastic region by using the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and combining it with the pre-constructed projection model of the elliptical plastic region. The semi-major axis length is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. The second data processing module is used to obtain the radius of the plastic region using a pre-constructed plastic region radius model when the wellbore to be tested produces sand, thereby completing the sand production prediction of the gas well in the ultra-deep, ultra-high pressure fractured low-porosity sandstone gas reservoir.

[0079] Additionally, a schematic diagram of a terminal device according to an embodiment of the present invention is provided. This terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the various method embodiments described above. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the various device embodiments described above.

[0080] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention.

[0081] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0082] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0083] The memory can be used to store the computer program and / or module. The processor implements various functions of the terminal device by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory.

[0084] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals. The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0085] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, characterized in that, Includes the following steps: The wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested are obtained, and it is assumed that there is a plastic region in the surrounding rock of the wellbore to be tested, and the plastic region has an elliptical structure. By using the obtained wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the well to be tested, and combined with the pre-constructed projection model of the elliptical plastic region, the length of the major semi-axis of the elliptical plastic region is obtained. The length of the major semi-axis is compared with the wellbore radius to determine whether the well to be tested is producing sand. When sand is produced in the wellbore to be tested, the radius of the plastic region is obtained by using a pre-constructed plastic region radius model, and the sand production prediction of the gas well in the ultra-deep and ultra-high pressure fractured low-porosity sandstone gas reservoir is completed.

2. The method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to claim 1, characterized in that, The length of the semi-major axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Then, the prediction results are compared using the combined modulus method. When the comparison results are consistent, the plastic region radius is obtained using a pre-constructed plastic region radius model to complete the sand production prediction of the gas well in the ultra-deep ultra-high pressure fractured low-porosity sandstone gas reservoir.

3. The method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to claim 1, characterized in that, The pre-constructed projection model of the elliptical structure's plastic region is as follows: in, For the maximum horizontal ground stress, For minimum horizontal ground stress, For rock cohesion, The internal friction angle of the rock. This refers to the bottom hole pressure.

4. The method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to claim 1, characterized in that, The length of the semi-major axis of the elliptical plastic region is obtained by combining a pre-constructed projection model of the elliptical structure's plastic region. Specifically, when b > 0, the length of the semi-major axis of the ellipse is... When b < 0, the semi-major axis of the ellipse is .

5. The method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to claim 1, characterized in that, The length of the major semi-axis is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. Specifically, when the length of the major semi-axis is greater than the wellbore radius, a plastic zone appears near the well wall and sand is produced in the well. Conversely, when the length of the major semi-axis is less than the wellbore radius, no plastic zone appears near the well wall and no sand is produced in the well.

6. The method for predicting sand production in gas wells of ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs according to claim 1, characterized in that, The pre-constructed plastic region radius model is as follows: In the formula, The radius of the plastic region, Where is the wellbore radius.

7. A sand production prediction system for gas wells in ultra-deep, ultra-high pressure fractured, low-porosity sandstone gas reservoirs, characterized in that, include: The data acquisition module is used to acquire the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and assumes that there is a plastic region in the surrounding rock of the wellbore to be tested, and that the plastic region has an elliptical structure. The first data processing module is used to obtain the semi-major axis length of the elliptical plastic region by using the wellbore radius, rock cohesion, rock internal friction angle, bottom hole pressure, maximum horizontal stress and minimum horizontal stress of the wellbore to be tested, and combining it with the pre-constructed projection model of the elliptical plastic region. The semi-major axis length is compared with the wellbore radius to determine whether the wellbore to be tested is producing sand. The second data processing module is used to obtain the radius of the plastic region using a pre-constructed plastic region radius model when the wellbore to be tested produces sand, thereby completing the sand production prediction of the gas well in the ultra-deep, ultra-high pressure fractured low-porosity sandstone gas reservoir.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in any one of claims 1 to 6.

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