Friction prediction method and device

Abstract

The application discloses a friction prediction method and device, and the method comprises the following steps: obtaining drilling data of measuring points contained in a target open well section; determining measuring point parameters corresponding to the measuring points based on the drilling data, wherein the measuring point parameters comprise well diameter concave-convex degree parameters, well bore curvature parameters and well bore gap ratio parameters; determining well bore roughness values corresponding to the measuring points according to the measuring point parameters; determining basic friction values corresponding to the measuring points according to the well bore roughness values and a preset correction mechanical model, wherein the correction mechanical model is obtained by correcting a conventional mechanical model by taking the roughness degree of an irregular well bore as an influencing factor; and determining comprehensive friction values corresponding to the measuring points according to the well bore roughness values and the basic friction values. The application is helpful to improve the accuracy of friction prediction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploitation, and in particular, relates to a friction prediction method and device. BACKGROUND

[0002] With the continuous development of oil and gas exploitation technology, horizontal well and extended reach well technology are widely used. Since the horizontal well and the extended reach well can significantly increase the contact area with the oil layer, the yield of a single well and the oil recovery rate can be effectively improved. However, since the well structure of the horizontal well and the extended reach well is very complex, there is a well section with a large inclination angle and a long build-up section (i.e. a high angle deviated well section). The contact area between the casing and the well wall increases accordingly at the high angle deviated well section, thereby increasing the friction between the casing and the well wall. In addition, at the high angle deviated well section, the rock debris bed formed due to poor hole cleaning effect also increases the resistance when the casing is run in. Therefore, as the casing running depth increases, the friction that the casing needs to overcome also increases, thereby causing the casing to be difficult to run to the target depth smoothly. Therefore, before the casing is run in, the friction of the casing running in needs to be predicted to determine whether there will be risks in the casing running in process.

[0003] At present, the friction of the casing running in is usually predicted based on a soft rod model and a rigid rod model. When the friction of the casing running in is predicted based on the soft rod model and the rigid rod model, it is assumed that the wellbore is a regular geometric shape. However, in actual application, the wellbore of the horizontal well and the extended reach well is an irregular shape such as an expanded diameter, a necked hole and a keyway. Therefore, the prediction result obtained by the existing friction prediction method is not accurate and has a large error. The prior art lacks a more accurate friction prediction method. SUMMARY

[0004] In order to solve at least one of the technical problems in the background art, the present application provides a friction prediction method and device.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a friction prediction method is provided, which comprises:

[0006] obtaining drilling data of a measurement point contained in a target open hole section;

[0007] determining a measurement point parameter corresponding to the measurement point based on the drilling data, wherein the measurement point parameter comprises a well diameter concave-convex degree parameter, a wellbore curvature parameter and a wellbore clearance ratio parameter;

[0008] determining a wellbore roughness value corresponding to the measurement point according to the measurement point parameter;

[0009] determine a basic friction value corresponding to the measuring point according to the borehole roughness value and a preset correction mechanics model, wherein the correction mechanics model is obtained by correcting a conventional mechanics model by taking the roughness degree corresponding to the irregular borehole as an influencing factor;

[0010] determine a comprehensive friction value corresponding to the measuring point according to the borehole roughness value and the basic friction value.

[0011] Optionally, the determining the measuring point parameter corresponding to the measuring point based on the drilling data comprises:

[0012] determine a predicted hole diameter corresponding to the measuring point according to the borehole type corresponding to the measuring point;

[0013] determine a hole diameter concave-convex degree parameter corresponding to the measuring point according to the predicted hole diameter corresponding to the measuring point, the measured hole diameter, the measured hole diameter of the associated measuring point and a hole diameter concave-convex degree determination model;

[0014] determine a borehole curvature parameter corresponding to the measuring point according to the inclination angle change rate corresponding to the measuring point, the azimuth angle change rate, the inclination angle, the characteristic length and a borehole curvature determination model;

[0015] determine a borehole clearance ratio parameter corresponding to the measuring point according to the measured hole diameter, the casing diameter and a borehole clearance ratio determination model.

[0016] Optionally, the determining the borehole roughness value corresponding to the measuring point according to the measuring point parameter comprises:

[0017] determine the borehole roughness value corresponding to the measuring point according to the hole diameter concave-convex degree parameter, the borehole curvature parameter, the borehole clearance ratio parameter and a borehole roughness determination model.

[0018] Optionally, the determining the borehole roughness value corresponding to the measuring point according to the measuring point parameter comprises:

[0019] normalize the hole diameter concave-convex degree parameter of each measuring point to obtain a normalized hole diameter concave-convex degree parameter corresponding to each measuring point;

[0020] normalize the borehole curvature parameter of each measuring point to obtain a normalized borehole curvature parameter corresponding to each measuring point;

[0021] normalize the borehole clearance ratio parameter of each measuring point to obtain a normalized borehole clearance ratio parameter corresponding to each measuring point;

[0022] determine the borehole roughness value corresponding to each measuring point according to the normalized hole diameter concave-convex degree parameter, the normalized borehole curvature parameter and the normalized borehole clearance ratio parameter.

[0023] Optionally, the determining the basic friction value corresponding to the measuring point according to the borehole roughness value and the preset correction mechanical model comprises:

[0024] For any one target measuring point included in the target open hole well section, a mechanical resistance value corresponding to the target measuring point is determined according to a borehole roughness value corresponding to the target measuring point and a preset mechanical resistance coefficient.

[0025] The basic friction value corresponding to the previous measuring point of the target measuring point, the microelement section length corresponding to the target measuring point, the bending stiffness of the drill string, the normalized borehole curvature parameter, the linear weight of the drill string, the inclination angle and the mechanical resistance value are substituted into the correction mechanical model to calculate the drill string axial force corresponding to the target measuring point.

[0026] The additional contact force corresponding to the target measuring point is determined according to the drill string axial force, and the basic friction value corresponding to the target measuring point is determined according to the additional contact force.

[0027] Optionally, the determining the additional contact force corresponding to the target measuring point according to the drill string axial force comprises:

[0028] The additional contact force corresponding to the target measuring point is determined according to the drill string axial force, the drill string borehole radial gap corresponding to the target measuring point, the bending stiffness of the drill string corresponding to the target measuring point and a determination model of the additional contact force.

[0029] Optionally, the determining the basic friction value corresponding to the target measuring point according to the additional contact force comprises:

[0030] The unit length casing contact force corresponding to the target measuring point is determined.

[0031] The total contact distribution force corresponding to the target measuring point is determined according to the unit length casing contact force and the additional contact force corresponding to the target measuring point.

[0032] The basic friction value corresponding to the target measuring point is determined according to the axial friction coefficient corresponding to the target open hole well section and the total contact distribution force.

[0033] Optionally, the friction prediction method further comprises:

[0034] A friction curve corresponding to the target open hole well section is determined according to the comprehensive friction values of the measuring points.

[0035] According to a preset friction threshold and the friction curve, a risk area included in the target open hole well section and a risk level corresponding to each of the risk areas are determined.

[0036] In order to achieve the above object, according to another aspect of the present application, there is provided a friction prediction device, comprising:

[0037] A drilling data acquisition unit is configured to acquire drilling data of measuring points included in a target open hole section;

[0038] A measuring point parameter determination unit is configured to determine measuring point parameters corresponding to the measuring points based on the drilling data, wherein the measuring point parameters include hole diameter bump and dent degree parameters, hole curvature parameters and hole gap ratio parameters;

[0039] A hole roughness value determination unit is configured to determine hole roughness values corresponding to the measuring points according to the measuring point parameters;

[0040] A basic friction value determination unit is configured to determine basic friction values corresponding to the measuring points according to the hole roughness values and a preset correction mechanics model, wherein the correction mechanics model is obtained by correcting a conventional mechanics model by taking the roughness degree of an irregular hole as an influencing factor;

[0041] A comprehensive friction value determination unit is configured to determine comprehensive friction values corresponding to the measuring points according to the hole roughness values and the basic friction values.

[0042] In order to achieve the above object, according to another aspect of the present application, there is also provided a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to realize the steps of the above friction prediction method.

[0043] In order to achieve the above object, according to another aspect of the present application, there is also provided a computer readable storage medium, which stores a computer program / instruction executable by a processor to realize the steps of the above friction prediction method.

[0044] In order to achieve the above object, according to another aspect of the present application, there is also provided a computer program product, which comprises a computer program / instruction executable by a processor to realize the steps of the above friction prediction method.

[0045] The present application has the following advantages:

[0046] The present application considers that the roughness of the irregular wellbore causes additional mechanical resistance in the casing running process, and affects the friction value in the casing running process, so that the roughness corresponding to the irregular wellbore is taken as an influencing factor to modify the conventional mechanical model, a modified mechanical model is obtained, and based on the modified mechanical model and the wellbore roughness value corresponding to each measuring point contained in the target open hole section, the comprehensive friction value corresponding to the measuring point is predicted, so that the friction value in the casing running process of the target open hole section can be accurately predicted, and the beneficial effect of improving the friction prediction accuracy is realized. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. In the drawings:

[0048] Figure 1 is a flow chart of the friction prediction method of the present application;

[0049] Figure 2 is a flow chart of the present application for determining the measuring point parameters;

[0050] Figure 3 is a flow chart of the present application for determining the wellbore roughness value;

[0051] Figure 4 is a flow chart of the present application for determining the basic friction value;

[0052] Figure 5 is a flow chart of the present application for determining the basic friction value of the target measuring point according to the additional contact force;

[0053] Figure 6 is a flow chart of the present application for determining the risk area and risk level;

[0054] Figure 7 is a structural block diagram of the friction prediction device of the present application;

[0055] Figure 8 is a schematic diagram of the computer equipment of the present application. DETAILED DESCRIPTION

[0056] In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort should fall within the protection scope of the present application.

[0057] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification and claims of the present application and the above drawings are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device containing a series of steps or units does not have to be limited to the clearly listed steps or units, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0059] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0060] Currently, the commonly used casing running friction prediction methods in the industry are mainly based on the soft rod model and the rigid rod model. Such methods usually assume that the wellbore is an ideal regular geometric shape for modeling and calculation. However, in actual drilling operations, especially in horizontal wells and extended reach wells, the wellbore often has various irregular shapes such as expansion, necking, keyway, etc. Since the existing friction prediction methods do not fully consider the actual impact of these irregular wellbores, the prediction accuracy of the casing running friction is low, often deviating greatly from the actual situation, and it is difficult to provide effective guidance for field operations. Therefore, the present application proposes a friction prediction method that can be corrected for irregular wellbore conditions and improve prediction accuracy.

[0061] Figure 1 is a flowchart of the friction prediction method of the embodiments of the present application, as shown in Figure 1 In one embodiment of the present application, the friction prediction method of the present application includes steps S101 to S105.

[0062] Step S101, obtain the drilling data of the measuring points contained in the target open hole section.

[0063] In the present application, the target open hole section is the section in the target wellbore that needs to be cased, and the target open hole section contains a plurality of micro-element sections, each of which corresponds to a measuring point. For example, if the length of the target open hole section is 2000 meters, the target open hole section can be divided into 2000 micro-element sections, each of which is 1 meter long.

[0064] For any measuring point, the corresponding drilling data can include, but is not limited to, the wellbore type corresponding to the measuring point, the measured hole diameter, the inclination angle change rate, the azimuth angle change rate, the inclination angle, the casing diameter, the bending stiffness of the drill string, the linear weight of the drill string, the drill string-hole radial clearance, etc.

[0065] When it is necessary to predict the friction value during casing running into the target open hole section, the drilling data corresponding to the target open hole section is first obtained, which can include, but is not limited to, the mud logging data, the logging data, the drilling history and the drilling log corresponding to the target open hole section. Then the drilling data corresponding to each measuring point is extracted from the drilling data corresponding to the target open hole section.

[0066] Step S102, determining the measuring point parameters corresponding to the measuring points based on the drilling data, wherein the measuring point parameters include the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore clearance ratio parameter.

[0067] In the present application, the hole diameter concave-convex degree parameter is used to indicate the slight undulation and irregularity of the inner wall surface of the wellbore; the wellbore curvature parameter is the curvature of the wellbore trajectory, which is used to indicate the bending degree of the wellbore trajectory; and the wellbore clearance ratio parameter is used to indicate the ratio of the annular clearance area between the casing and the drilled wellbore to the area of the drilled wellbore at the same depth.

[0068] Due to the wellbore roughness of the irregular wellbore, additional mechanical resistance is generated during the casing running process, thereby affecting the friction value during the casing running process. For any measuring point, the mechanical resistance at the measuring point can be calculated according to the wellbore roughness at the measuring point.

[0069] After the characteristic parameter screening process, it can be concluded that the mutual information value between the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore clearance ratio parameter and the wellbore roughness is the largest, i.e., the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore clearance ratio parameter are the three parameters that are most relevant to the wellbore roughness, so that for any measuring point, the wellbore roughness corresponding to the measuring point can be calculated based on the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore clearance ratio parameter corresponding to the measuring point. Therefore, after obtaining the drilling data corresponding to each measuring point, the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore clearance ratio parameter corresponding to each measuring point need to be calculated according to the drilling data corresponding to each measuring point.

[0070] In step S103, the borehole roughness value corresponding to the measuring point is determined according to the measuring point parameters.

[0071] In an embodiment of the present application, the borehole roughness value corresponding to the measuring point can be determined according to the borehole caliper concave-convex degree parameter, the borehole curvature parameter, the borehole gap ratio parameter and a borehole roughness determination model.

[0072] In an embodiment of the present application, the borehole roughness determination model can be a mathematical model, specifically a first preset formula, and in this step, the borehole caliper concave-convex degree parameter, the borehole curvature parameter and the borehole gap ratio parameter corresponding to each measuring point are substituted into the first preset formula to calculate the borehole roughness value corresponding to each measuring point. The first preset formula is specifically as follows:

[0073]

[0074] wherein, is the borehole roughness value corresponding to the measuring point, is the borehole caliper concave-convex degree parameter corresponding to the measuring point, k b is the borehole curvature parameter corresponding to the measuring point, is the borehole gap ratio parameter corresponding to the measuring point, γ1, γ2 and γ3 are weight coefficients corresponding to the borehole caliper concave-convex degree parameter, the borehole curvature parameter and the borehole gap ratio parameter respectively.

[0075] In another embodiment of the present application, the borehole roughness determination model can also be a machine learning model. Specifically, first, historical data with known borehole roughness values are collected, and training samples are constructed based on these data. The feature vector of each training sample includes the borehole caliper concave-convex degree parameter, the borehole curvature parameter and the borehole gap ratio parameter, and the label is the actual borehole roughness value. Then, the above training samples are input into a preset machine learning model for training. The machine learning model can be a regression model known in the prior art, such as support vector regression (SVR), random forest regression, neural network, etc. After training, a borehole roughness prediction model is obtained. In actual prediction, the relevant parameters of the measuring point to be measured are input into the trained model, and the borehole roughness value of the corresponding measuring point can be obtained. This embodiment can make full use of historical experience data and machine learning technology, effectively improve the prediction accuracy and adaptability of the borehole roughness value, and provide more accurate basic data for subsequent frictional resistance value calculation. The present application can set multiple preset values for each weight coefficient in advance, and then perform orthogonal test on the multiple preset values of each weight coefficient based on the rule that the absolute value of the objective function is the smallest, and determine the value of each weight coefficient according to the orthogonal test result, wherein the objective function is specifically as follows:

[0076]

[0077] F irre is a measured hook load corresponding to the irregular wellbore, F re is a predicted hook load corresponding to the irregular wellbore, the predicted hook load corresponding to the irregular wellbore being calculated based on the modified mechanical model.

[0078] After the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore gap ratio parameter corresponding to each measuring point are calculated, the hole diameter concave-convex degree parameter, the wellbore curvature parameter and the wellbore gap ratio parameter corresponding to each measuring point are respectively substituted into the first preset formula, so as to calculate the wellbore roughness value corresponding to each measuring point.

[0079] In step S104, the basic friction value corresponding to the measuring point is determined according to the wellbore roughness value and a preset modified mechanical model, wherein the modified mechanical model is obtained by modifying a conventional mechanical model by taking the roughness degree corresponding to the irregular wellbore as an influencing factor.

[0080] After the wellbore roughness value corresponding to each measuring point is calculated, the basic friction value corresponding to each measuring point is calculated according to the wellbore roughness value corresponding to each measuring point and the modified mechanical model.

[0081] In step S105, the comprehensive friction value corresponding to the measuring point is determined according to the wellbore roughness value and the basic friction value.

[0082] After the basic friction value corresponding to each measuring point is calculated, the comprehensive friction value corresponding to each measuring point is calculated according to the wellbore roughness value corresponding to each measuring point and the basic friction value. The specific process is as follows: for any measuring point, first, the mechanical resistance value corresponding to the measuring point is calculated according to the wellbore roughness value corresponding to the measuring point and a preset mechanical resistance coefficient, that is, the product of the wellbore roughness value corresponding to the measuring point and the preset mechanical resistance coefficient is determined as the mechanical resistance value corresponding to the measuring point; and then, the comprehensive friction value corresponding to the measuring point is calculated according to the basic friction value corresponding to the measuring point and the mechanical resistance value, that is, the basic friction value corresponding to the measuring point and the mechanical resistance value are summed up, and the calculation result is determined as the comprehensive friction value corresponding to the measuring point.

[0083] As can be seen, by introducing the wellbore roughness of the irregular wellbore as a correction factor, the actual influence of the complex wellbore structure on the friction value in the casing running process is effectively reflected. Specifically, the wellbore roughness parameter is introduced into the conventional mechanical model to modify the model, so as to build a mechanical model that can adapt to the conditions of the irregular wellbore. Based on the modified model and in combination with the wellbore roughness values of the measuring points, the comprehensive friction value in the casing running process can be more accurately predicted, and the accuracy of the friction prediction is effectively improved.

[0084] AsFigure 2 In one embodiment of the present application, the step S102 of determining the point parameter corresponding to each of the measuring points based on the drilling data comprises steps S201 to S204.

[0085] In step S201, the predicted hole diameter corresponding to the measuring point is determined according to the hole type corresponding to the measuring point.

[0086] In the present application, the predicted hole diameter corresponding to the measuring point is determined according to the hole type corresponding to the measuring point, wherein when the hole type corresponding to the measuring point is a big-belly hole, the predicted hole diameter corresponding to the measuring point is equal to D b (1+K), when the hole type corresponding to the measuring point is a reduced-diameter hole, the predicted hole diameter corresponding to the measuring point is equal to D b , and when the hole type corresponding to the measuring point is other irregular hole (such as bare hole keyhole, etc.), the predicted hole diameter corresponding to the measuring point is equal to D .

[0087] , wherein D b is the design size of the drill bit, K is a preset expansion rate threshold, which can be 0.1, 0.15, etc., is the average of the measured hole diameter corresponding to the measuring point and the measured hole diameters corresponding to the associated measuring points.

[0088] In step S202, the hole concave-convex degree parameter corresponding to the measuring point is determined according to the predicted hole diameter corresponding to the measuring point, the measured hole diameter, the measured hole diameters of the associated measuring points, and the hole concave-convex degree determination model.

[0089] The associated measuring points of a measuring point are specifically the first N measuring points and the last N measuring points adjacent to the measuring point, and N is a positive integer.

[0090] In one embodiment of the present application, the hole concave-convex degree determination model can be a mathematical model, specifically a second preset formula, and in this step, the predicted hole diameter corresponding to the measuring point, the measured hole diameter, and the measured hole diameters corresponding to each of the associated measuring points of the measuring point are substituted into the second preset formula, so as to calculate the hole concave-convex degree parameter corresponding to the target measuring point, wherein the second preset formula is specifically:

[0091]

[0092] , wherein is the hole concave-convex degree parameter corresponding to the measuring point, n is the total number of the measuring point and the associated measuring points, D wv is the predicted hole diameter corresponding to the measuring point, D wi is the i-th measuring point in the measuring point and the associated measuring points.

[0093] In another embodiment of the present application, the hole diameter concave-convex degree determination model can also be a machine learning model. Specifically, first, historical drilling data is collected to build a training data set, and the feature vector of each sample includes the predicted hole diameter, the measured hole diameter and the measured hole diameter of the associated measuring points, and the label is the actual hole diameter concave-convex degree parameter. The above training data is used to train a preset machine learning model (such as a support vector machine, a random forest, a neural network, etc. Common models) to obtain a machine learning model that can automatically predict the hole diameter concave-convex degree parameter. In actual application, only the predicted hole diameter, the measured hole diameter of the to-be-measured measuring point and the measured hole diameter of the associated measuring points are input into the trained model, and the hole diameter concave-convex degree parameter of the measuring point can be output. By introducing the machine learning model, the complex relationship between the historical data and various parameters can be fully utilized, the prediction accuracy and model adaptability of the hole diameter concave-convex degree parameter are improved, and more reliable basic data are provided for subsequent accurate calculation of the hole roughness and the friction value. In step S203, the hole curvature parameter corresponding to the measuring point is determined according to the hole inclination rate of change, the azimuth rate of change, the hole inclination, the characteristic length and the hole curvature determination model corresponding to the measuring point.

[0094] In an embodiment of the present application, the hole curvature determination model can be a mathematical model, specifically a third preset formula. In this step, the hole inclination rate of change, the azimuth rate of change, the hole inclination and the characteristic length corresponding to the measuring point are substituted into the third preset formula to calculate the hole curvature parameter corresponding to the measuring point. The third preset formula is specifically:

[0095]

[0096] wherein k b is the hole curvature parameter corresponding to the target measuring point, L is the characteristic length, which can be specifically 1, k a is the hole inclination rate of change corresponding to the measuring point, is the azimuth rate of change corresponding to the measuring point, is the hole inclination corresponding to the measuring point.

[0097] In another embodiment of the present application, the wellbore curvature determination model can also be a machine learning model. Specifically, a large amount of historical measurement point data is first collected to build a training data set, the feature vector of each sample includes the rate of change of the inclination angle, the rate of change of the azimuth angle, the inclination angle and the characteristic length, and the label is the actual measured wellbore curvature parameter. The above training data is input into a preset machine learning model for training, and the model can be a common regression model in the prior art, such as support vector regression, random forest regression, neural network, etc. After training, a machine learning model capable of automatically predicting the wellbore curvature according to the related characteristic parameters is obtained. In actual application, only the related parameters of the target measurement point need to be input into the model, and the corresponding wellbore curvature parameter can be output. In this embodiment, the machine learning model is introduced to fully exploit and utilize the nonlinear relationship between the parameters in the historical data, thereby improving the prediction accuracy of the wellbore curvature parameter and the adaptability of the model, and laying a good foundation for the subsequent accurate calculation of the wellbore roughness and the friction value. In step S204, a model is determined according to the measured hole diameter, the casing diameter and the wellbore clearance ratio of the measurement point, and the wellbore clearance ratio parameter corresponding to the measurement point is determined.

[0098] In an embodiment of the present application, the wellbore clearance ratio determination model can be a mathematical model, specifically a fourth preset formula. In this step, the measured hole diameter and the casing diameter corresponding to the measurement point are substituted into the fourth preset formula to calculate the wellbore clearance ratio parameter corresponding to the measurement point, wherein the fourth preset formula is specifically:

[0099]

[0100] wherein, is the wellbore clearance ratio parameter corresponding to the measurement point, D w is the measured hole diameter corresponding to the measurement point, D c is the casing diameter corresponding to the measurement point.

[0101] In another embodiment of the present application, the wellbore clearance ratio determination model can also be a machine learning model. Specifically, historical measurement point data with known wellbore clearance ratio parameters are first collected to build a training data set, the feature vector of each sample includes the measured hole diameter and the casing diameter, and the label is the actual wellbore clearance ratio parameter. The above training data is used to train a preset machine learning model (such as support vector regression, random forest, neural network, etc.) to obtain a machine learning model capable of automatically predicting the wellbore clearance ratio parameter. In actual application, the measured hole diameter and the casing diameter of the target measurement point are input into the trained model to output the wellbore clearance ratio parameter of the measurement point. By introducing the machine learning model, the complex relationship between the historical data and the multiple parameters can be fully utilized to improve the prediction accuracy of the wellbore clearance ratio parameter and provide more reliable basic data for the subsequent accurate calculation of the wellbore roughness and the friction value. For example, Figure 3As shown, in one embodiment of the present application, the step S103 of determining the borehole roughness value corresponding to each measuring point according to the measuring point parameters specifically comprises steps S301 to S304.

[0102] In step S301, the hole diameter bump degree parameters of each measuring point are normalized to obtain the normalized hole diameter bump degree parameters corresponding to each measuring point.

[0103] In the present application, the hole diameter bump degree parameters of each measuring point are normalized to obtain the normalized hole diameter bump degree parameters corresponding to each measuring point. In one embodiment of the present application, the Min-Max normalization formula can be used to normalize the hole diameter bump degree parameters of each measuring point to obtain the normalized hole diameter bump degree parameters corresponding to each measuring point.

[0104] In step S302, the borehole curvature parameters of each measuring point are normalized to obtain the normalized borehole curvature parameters corresponding to each measuring point.

[0105] In the present application, the borehole curvature parameters of each measuring point are normalized to obtain the normalized borehole curvature parameters corresponding to each measuring point. In one embodiment of the present application, the Min-Max normalization formula can be used to normalize the borehole curvature parameters of each measuring point to obtain the normalized borehole curvature parameters corresponding to each measuring point.

[0106] In step S303, the borehole gap ratio parameters of each measuring point are normalized to obtain the normalized borehole gap ratio parameters corresponding to each measuring point.

[0107] In the present application, the borehole gap ratio parameters of each measuring point are normalized to obtain the normalized borehole gap ratio parameters corresponding to each measuring point. In one embodiment of the present application, the Min-Max normalization formula can be used to normalize the borehole gap ratio parameters of each measuring point to obtain the normalized borehole gap ratio parameters corresponding to each measuring point.

[0108] In step S304, the borehole roughness values corresponding to each measuring point are determined according to the normalized hole diameter bump degree parameters, the normalized borehole curvature parameters, and the normalized borehole gap ratio parameters.

[0109] In one embodiment of the present application, the borehole roughness values corresponding to each measuring point can be determined according to the normalized hole diameter bump degree parameters, the normalized borehole curvature parameters, the normalized borehole gap ratio parameters, and a borehole roughness determination model.

[0110] In one embodiment of the present application, the normalized hole diameter bump parameter, the normalized hole curvature parameter and the normalized hole gap ratio parameter corresponding to each measuring point are substituted into the first preset formula respectively, so as to calculate the hole roughness value corresponding to each measuring point.

[0111] As shown in the figure, in one embodiment of the present application, the step S104 of determining the basic friction value corresponding to each measuring point according to the hole roughness value and the preset correction mechanical model specifically includes steps S401 to S403. Figure 4

[0112] In step S401, for any one target measuring point included in the target open hole section, the mechanical resistance value corresponding to the target measuring point is determined according to the hole roughness value corresponding to the target measuring point and the preset mechanical resistance coefficient.

[0113] In the present application, the target measuring point can be any one of all the measuring points included in the target open hole section.

[0114] In one embodiment of the present application, the product of the hole roughness value corresponding to the target measuring point and the preset mechanical resistance coefficient is specifically determined as the mechanical resistance value corresponding to the target measuring point.

[0115] In step S402, the basic friction value corresponding to the previous measuring point of the target measuring point, the microelement segment length corresponding to the target measuring point, the bending stiffness of the drill string, the normalized hole curvature parameter, the linear weight of the drill string, the inclination angle and the mechanical resistance value are substituted into the correction mechanical model, so as to calculate the drill string axial force corresponding to the target measuring point.

[0116] In the present application, the previous measuring point is adjacent to the target measuring point, and the well depth of the microelement segment corresponding to the previous measuring point is greater than the well depth of the microelement segment corresponding to the target measuring point.

[0117] In one embodiment of the present application, the correction mechanical model is specifically as follows:

[0118]

[0119] Wherein, F is the drill string axial force corresponding to the target measuring point, s is the length of the microelement segment corresponding to the target measuring point, EI is the bending stiffness of the drill string corresponding to the target measuring point, k b is the normalized hole curvature parameter corresponding to the target measuring point, q is the linear weight of the drill string corresponding to the target measuring point, is the inclination angle corresponding to the target measuring point, is the basic friction value corresponding to the previous measuring point, is the mechanical resistance value corresponding to the target measuring point, k f is the preset mechanical resistance coefficient, is the hole roughness value corresponding to the target measuring point.​

[0120] Step S403, determining the additional contact force corresponding to the target measuring point according to the drill string axial force, and determining the basic friction value corresponding to the target measuring point according to the additional contact force.

[0121] In an embodiment of the present application, the additional contact force corresponding to the target measuring point is determined according to the drill string axial force corresponding to the target measuring point. The drill string axial force corresponding to the target measuring point, the drill string borehole radial clearance and the drill string bending stiffness are substituted into a fifth preset formula, so as to calculate the additional contact force corresponding to the target measuring point. The fifth preset formula is specifically:

[0122]

[0123] Wherein, W b is the additional contact force corresponding to the target measuring point, r b is the drill string borehole radial clearance corresponding to the target measuring point, F is the drill string axial force corresponding to the target measuring point, and EI is the drill string bending stiffness corresponding to the target measuring point. The additional contact force corresponding to the target measuring point is caused by the buckling of the pipe string with a joint or a centralizer.

[0124] In an embodiment of the present application, the basic friction value corresponding to the target measuring point is determined according to the additional contact force corresponding to the target measuring point. The specific process can be: first, determining the unit length casing contact force corresponding to the target measuring point; then, calculating the total contact distribution force corresponding to the target measuring point according to the unit length casing contact force corresponding to the target measuring point and the additional contact force, that is, summing the unit length casing contact force corresponding to the target measuring point and the additional contact force, and determining the calculation result as the total contact distribution force corresponding to the target measuring point; finally, calculating the basic friction value corresponding to the target measuring point according to the axial friction coefficient corresponding to the target open hole well section and the total contact distribution force corresponding to the target measuring point. That is, the product of the axial friction coefficient corresponding to the target open hole well section and the total contact distribution force corresponding to the target measuring point is determined as the basic friction value corresponding to the target measuring point. The axial friction coefficient corresponding to the target open hole well section is obtained by inversion according to the drilling data corresponding to the target open hole well section. It should be noted that the specific method for determining the unit length casing contact force corresponding to the target measuring point can refer to the prior art, and the embodiments of the present application will not be described here.

[0125] In addition, it should be noted that, since the drill string axial force corresponding to the measuring point closest to the drill bit is 0, steps S401 and S402 can be omitted to directly execute S403, so as to determine the basic friction value corresponding to the measuring point closest to the drill bit.

[0126] In an embodiment of the present application, the additional contact force corresponding to the target measuring point is determined according to the drill string axial force in step S403, comprising:

[0127] According to the drill string axial force, the drill string borehole radial clearance corresponding to the target measuring point, the drill string bending stiffness corresponding to the target measuring point, and the additional contact force determination model, the additional contact force corresponding to the target measuring point is determined.

[0128] In an embodiment of the present application, the additional contact force determination model can be a mathematical model, specifically the fifth preset formula described above. In this step, the drill string axial force, the drill string borehole radial clearance, and the drill string bending stiffness corresponding to the target measuring point are substituted into the fifth preset formula to calculate the additional contact force corresponding to the target measuring point.

[0129] In another embodiment of the present application, the additional contact force determination model can also be a machine learning model. Specifically, first, historical measuring point data with known additional contact forces are collected to construct a training data set. The feature vector of each training sample includes the drill string axial force, the drill string borehole radial clearance, and the drill string bending stiffness, and the label is the actual additional contact force. The training data described above is used to train a preset machine learning model, which can be a support vector regression, a random forest, a neural network, or the like in the prior art. After training, a machine learning model that can automatically predict the additional contact force according to the input parameters is obtained. In actual application, only the drill string axial force, the drill string borehole radial clearance, and the drill string bending stiffness of the target measuring point need to be input into the trained model, and the corresponding additional contact force can be output. By using a machine learning model, the complex relationships between parameters in historical data can be more fully mined, the accuracy of additional contact force prediction and the adaptability of the model can be improved, and more reliable data basis can be provided for subsequent calculation of the basic friction value and the comprehensive friction value. As shown in FIG. 5, in an embodiment of the present application, the determination of the basic friction value corresponding to the target measuring point according to the additional contact force in step S403 specifically includes steps S501 to S503. Figure 5

[0130] Step S501, determining the unit length casing contact force corresponding to the target measuring point.

[0131] It should be noted that the specific method of determining the unit length casing contact force corresponding to the target measuring point in this step is in the prior art, and the present application embodiment will not be described again.

[0132] Step S502, determining the total contact distribution force corresponding to the target measuring point according to the unit length casing contact force and the additional contact force corresponding to the target measuring point.

[0133] In an embodiment of the present application, this step can specifically sum the unit length casing contact force and the additional contact force corresponding to the target measuring point, and determine the calculation result as the total contact distribution force corresponding to the target measuring point. ​

[0134] Step S503, determining the basic friction value corresponding to the target measuring point according to the axial friction coefficient corresponding to the target open hole section and the total contact distribution force.

[0135] In an embodiment of the present application, the product of the axial friction coefficient corresponding to the target open hole section and the total contact distribution force corresponding to the target measuring point can be determined as the basic friction value corresponding to the target measuring point. The axial friction coefficient corresponding to the target open hole section is obtained by inverting the drilling data corresponding to the target open hole section.

[0136] As shown in FIG. 6, in an embodiment of the present application, the friction prediction method of the present application further comprises steps S601 and S602. Figure 6

[0137] Step S601, determining the friction curve corresponding to the target open hole section according to the comprehensive friction values of the measuring points.

[0138] Step S602, determining the risk areas contained in the target open hole section and the risk levels corresponding to each of the risk areas according to the preset friction threshold and the friction curve.

[0139] In an embodiment of the present application, after determining the comprehensive friction value corresponding to each measuring point, the present application can further draw the friction curve corresponding to the target open hole section according to the comprehensive friction value corresponding to each measuring point and the depth of the infinitesimal section where each measuring point is located, and determine the multiple risk areas contained in the target open hole section and the risk levels corresponding to each of the risk areas according to the multiple preset friction thresholds and the friction curve corresponding to the target open hole section. In this way, when the casing running work of the target open hole section is performed, the worker can select the appropriate casing running mode and operation parameters according to the friction curve corresponding to the target open hole section, the multiple risk areas and the risk levels corresponding to each of the risk areas, so as to improve the efficiency and safety of the casing running, and further ensure that the casing can be smoothly run to the target depth.

[0140] ​For example, three preset friction thresholds A, B and C are preset, when the integrated friction values corresponding to the continuous multiple measuring points are all greater than A, the region formed by the microelement segments corresponding to the multiple measuring points is determined as a risk region, and the risk level corresponding to the risk region is determined as level one, when the integrated friction values corresponding to the continuous multiple measuring points are all greater than B and less than or equal to A, the region formed by the microelement segments corresponding to the multiple measuring points is determined as a risk region, and the risk level corresponding to the risk region is determined as level two, when the integrated friction values corresponding to the continuous multiple measuring points are all greater than C and less than or equal to B, the region formed by the microelement segments corresponding to the multiple measuring points is determined as a risk region, and the risk level corresponding to the risk region is determined as level three, when the integrated friction values corresponding to the continuous multiple measuring points are all less than C, the region formed by the microelement segments corresponding to the multiple measuring points is determined as a non-risk region.

[0141] As can be seen from the above embodiments, the friction prediction method of the present application at least achieves the following beneficial effects:

[0142] 1、The present application considers that the roughness of the irregular wellbore causes additional mechanical resistance in the casing running process, which affects the friction value in the casing running process, so that the roughness corresponding to the irregular wellbore is taken as an influencing factor to modify the conventional mechanical model, to obtain a modified mechanical model, and based on the modified mechanical model and the wellbore roughness value corresponding to each measuring point contained in the target open hole section, the integrated friction value corresponding to each measuring point is predicted, so that the friction value in the casing running process of the target open hole section can be accurately predicted.

[0143] 2、The present application determines multiple risk regions contained in the target open hole section and the risk level corresponding to each risk region according to the integrated friction value corresponding to each measuring point. Thereby, the field engineering personnel can intuitively master the friction risk distribution at each place in the well section before the casing running operation, and identify and warn the high-risk section that may cause casing sticking or running difficulty in advance. The field engineering personnel can accordingly optimize the running parameters, adjust the operation scheme or take preventive measures, so as to reduce the engineering risk and improve the success rate of casing running and operation safety.

[0144] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0145] Based on the same inventive concept, the embodiments of the present application also provide a friction prediction device which can be used to implement the friction prediction method described in the above embodiments, as described in the following embodiments. Since the principle of solving problems of the friction prediction device is similar to that of the friction prediction method, the embodiments of the friction prediction device can refer to the embodiments of the friction prediction method, and the repeated parts will not be described herein. The term "unit" or "module" used below can be a combination of software and / or hardware which can implement a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware or a combination of software and hardware is also possible and conceived.

[0146] Figure 7 is a structural block diagram of the friction prediction device of the embodiments of the present application, as Figure 7 shown, in an embodiment of the present application, the friction prediction device of the present application comprises:

[0147] a drilling data acquisition unit 1 configured to acquire drilling data of a measuring point included in a target open hole section;

[0148] a measuring point parameter determination unit 2 configured to determine a measuring point parameter corresponding to the measuring point based on the drilling data, wherein the measuring point parameter comprises a hole diameter bumpiness parameter, a hole curvature parameter and a hole clearance ratio parameter;

[0149] a hole roughness value determination unit 3 configured to determine a hole roughness value corresponding to the measuring point according to the measuring point parameter;

[0150] a basic friction value determination unit 4 configured to determine a basic friction value corresponding to the measuring point according to the hole roughness value and a preset correction mechanics model, wherein the correction mechanics model is obtained by correcting a conventional mechanics model by taking the roughness degree corresponding to the irregular hole as an influencing factor;

[0151] a comprehensive friction value determination unit 5 configured to determine a comprehensive friction value corresponding to the measuring point according to the hole roughness value and the basic friction value.

[0152] In an embodiment of the present application, the measuring point parameter determination unit 2 comprises:

[0153] a predicted hole diameter determination module configured to determine a predicted hole diameter corresponding to the measuring point according to a hole type corresponding to the measuring point;

[0154] a hole diameter bumpiness parameter determination module configured to determine a hole diameter bumpiness parameter corresponding to the measuring point according to the predicted hole diameter corresponding to the measuring point, a measured hole diameter, a measured hole diameter of an associated measuring point and a hole diameter bumpiness determination model;

[0155] The wellbore curvature parameter determination module is configured to determine the wellbore curvature parameter corresponding to the measuring point according to the well inclination rate of change corresponding to the measuring point, the azimuth angle rate of change, the well inclination angle, the characteristic length and a wellbore curvature determination model.

[0156] The wellbore gap ratio parameter determination module is configured to determine the wellbore gap ratio parameter corresponding to the measuring point according to the measured hole diameter corresponding to the measuring point, the casing diameter and a wellbore gap ratio determination model.

[0157] In an embodiment of the present application, the wellbore roughness value determination unit 3 comprises:

[0158] The first wellbore roughness value determination module is configured to determine the wellbore roughness value corresponding to the measuring point according to the hole diameter concave-convex degree parameter corresponding to the measuring point, the wellbore curvature parameter, the wellbore gap ratio parameter and a wellbore roughness determination model.

[0159] In an embodiment of the present application, the wellbore roughness value determination unit 3 comprises:

[0160] The first normalization processing module is configured to perform normalization processing on the hole diameter concave-convex degree parameter of each measuring point to obtain the normalized hole diameter concave-convex degree parameter corresponding to each measuring point.

[0161] The second normalization processing module is configured to perform normalization processing on the wellbore curvature parameter of each measuring point to obtain the normalized wellbore curvature parameter corresponding to each measuring point.

[0162] The third normalization processing module is configured to perform normalization processing on the wellbore gap ratio parameter of each measuring point to obtain the normalized wellbore gap ratio parameter corresponding to each measuring point.

[0163] The second wellbore roughness value determination module is configured to determine the wellbore roughness value corresponding to each measuring point according to the normalized hole diameter concave-convex degree parameter, the normalized wellbore curvature parameter and the normalized wellbore gap ratio parameter.

[0164] In an embodiment of the present application, the basic friction value determination unit 4 comprises:

[0165] The mechanical resistance value determination module is configured to, for any one target measuring point included in the target open hole section, determine the mechanical resistance value corresponding to the target measuring point according to the wellbore roughness value corresponding to the target measuring point and a preset mechanical resistance coefficient.

[0166] The drill string axial force determination module is configured to substitute the basic friction value corresponding to the previous measuring point of the target measuring point, the microelement section length corresponding to the target measuring point, the drill string bending stiffness, the normalized wellbore curvature parameter, the drill string linear weight, the inclination angle and the mechanical resistance value into the modified mechanical model to calculate the drill string axial force corresponding to the target measuring point.

[0167] The basic friction value determination module is configured to determine an additional contact force corresponding to the target measuring point according to the drill string axial force, and determine a basic friction value corresponding to the target measuring point according to the additional contact force.

[0168] In an embodiment of the present application, the basic friction value determination module comprises:

[0169] The additional contact force determination sub-module is configured to determine the additional contact force corresponding to the target measuring point according to the drill string axial force, a drill string borehole radial clearance corresponding to the target measuring point, a drill string bending stiffness corresponding to the target measuring point, and an additional contact force determination model.

[0170] In an embodiment of the present application, the basic friction value determination module comprises:

[0171] The unit length casing contact force determination sub-module is configured to determine a unit length casing contact force corresponding to the target measuring point.

[0172] The total contact distribution force determination sub-module is configured to determine a total contact distribution force corresponding to the target measuring point according to the unit length casing contact force and the additional contact force corresponding to the target measuring point.

[0173] The basic friction value determination sub-module is configured to determine the basic friction value corresponding to the target open hole section according to an axial friction coefficient corresponding to the target open hole section and the total contact distribution force.

[0174] In an embodiment of the present application, the friction prediction device further comprises:

[0175] The friction curve determination unit is configured to determine a friction curve corresponding to the target open hole section according to the comprehensive friction values of the measuring points.

[0176] The risk area determination unit is configured to determine a risk area contained in the target open hole section and a risk level corresponding to each of the risk areas according to a preset friction threshold and the friction curve.

[0177] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a computer device is also provided. As shown in the accompanying drawings, the computer device comprises a memory, a processor, a communication interface and a communication bus, and a computer program capable of running on the processor is stored on the memory, and the processor implements the steps in the above-mentioned embodiment method when executing the computer program. Figure 8

[0178] ​The processor can be a central processing unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, or a combination thereof.

[0179] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs, non-transitory computer executable programs and units, such as the corresponding program units in the above-mentioned method embodiments of the application. The processor executes various functions and work data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, that is, the method in the above-mentioned method embodiments is realized.

[0180] The memory can include a program storage area and a data storage area. The program storage area can store an operating system and at least one application required by a function. The data storage area can store data created by the processor and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged with respect to the processor, and these remote memories can be connected to the processor through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0181] The one or more units are stored in the memory, and when executed by the processor, the method in the above-mentioned embodiments is executed.

[0182] The above-mentioned computer device specific details can be understood by referring to the corresponding related description and effects in the above-mentioned embodiments, which will not be repeated here.

[0183] To achieve the above object, according to another aspect of the present application, there is further provided a computer readable storage medium storing a computer program, which, when executed on a computer processor, implements the steps of the above friction prediction method. It is understood by those skilled in the art that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid state drive (SSD), etc. The storage medium can also include a combination of the above-mentioned types of memories.

[0184] To achieve the above object, according to another aspect of the present application, there is further provided a computer program product, comprising computer program / instructions, which, when executed by a processor, implements the steps of the above friction prediction method.

[0185] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present application can be realized by general computing devices, which can be concentrated on a single computing device or distributed on a network composed of multiple computing devices, and optionally, they can be realized by program codes executable by computing devices, so that they can be stored in storage devices and executed by computing devices, or they can be respectively manufactured into individual integrated circuit modules, or multiple modules or steps among them can be manufactured into a single integrated circuit module to realize. Thus, the present application is not limited to any specific combination of hardware and software.

[0186] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for predicting friction resistance, characterized in that, include: Obtain drilling data for measuring points included in the target open hole section. The drilling data includes: wellbore type, measured well diameter, rate of change of inclination angle, rate of change of azimuth angle, inclination angle, casing diameter, drill string bending stiffness, drill string linear weight, and drill string-wellbore radial clearance. Based on the drilling data, the corresponding measuring point parameters are determined, wherein the measuring point parameters include: wellbore concavity parameters, wellbore curvature parameters, and wellbore clearance ratio parameters; Determine the wellbore roughness value corresponding to the measuring point based on the measuring point parameters; Based on the wellbore roughness value and the preset modified mechanical model, the basic friction value corresponding to the measuring point is determined. The modified mechanical model is obtained by modifying the conventional mechanical model by taking the roughness of the irregular wellbore as an influencing factor. Based on the wellbore roughness value and the basic friction value, determine the comprehensive friction value corresponding to the measuring point; Determining the wellbore roughness value corresponding to the measuring point based on the measuring point parameters includes: Substituting the wellbore roughness parameters, wellbore curvature parameters, and wellbore clearance ratio parameters corresponding to each measuring point into the first preset formula, the wellbore roughness value corresponding to each measuring point is calculated. The first preset formula is as follows: in, The roughness value of the wellbore corresponding to the measuring point. k represents the wellbore concavity parameter corresponding to the measuring point. b The wellbore curvature parameter corresponding to the measuring point. γ1, γ2, and γ3 are the wellbore clearance ratio parameters corresponding to the measuring points, and the weighting coefficients corresponding to the wellbore concavity parameter, wellbore curvature parameter, and wellbore clearance ratio parameter, respectively. The modified mechanical model is specifically as follows: Where F is the axial force of the drill string corresponding to the target measuring point, s is the length of the micro-element corresponding to the target measuring point, EI is the bending stiffness of the drill string corresponding to the target measuring point, and k b Here, q represents the normalized wellbore curvature parameter corresponding to the target measuring point, and q represents the drill string weight corresponding to the target measuring point. The well inclination angle corresponding to the target measuring point. This represents the basic friction value corresponding to the previous measuring point. k represents the mechanical resistance value corresponding to the target measuring point. f To preset the mechanical resistance coefficient, The wellbore roughness value corresponding to the target measuring point; The step of determining the comprehensive friction value corresponding to the measuring point based on the wellbore roughness value and the basic friction value includes: For any given measuring point, the product of the wellbore roughness value corresponding to that measuring point and the preset mechanical resistance coefficient is determined as the mechanical resistance value corresponding to that measuring point. The basic friction value and the mechanical resistance value corresponding to that measuring point are summed and the calculation result is determined as the comprehensive friction value corresponding to that measuring point.

2. The friction prediction method according to claim 1, characterized in that, The step of determining the measuring point parameters corresponding to the measuring point based on the drilling data includes: Based on the wellbore type corresponding to the measuring point, determine the predicted well diameter corresponding to the measuring point; Based on the predicted well diameter, measured well diameter, measured well diameter of associated well points, and well diameter concavity and convexity of the measuring points, a model is determined to determine the well diameter concavity and convexity parameters corresponding to the measuring points. Based on the well inclination angle change rate, azimuth angle change rate, well inclination angle, characteristic length, and wellbore curvature corresponding to the measuring point, a model is determined to determine the wellbore curvature parameters corresponding to the measuring point; The model is determined based on the measured well diameter, casing diameter, and wellbore clearance ratio corresponding to the measuring point, and the wellbore clearance ratio parameter corresponding to the measuring point is determined.

3. The friction prediction method according to claim 1, characterized in that, Determining the wellbore roughness value corresponding to the measuring point based on the measuring point parameters includes: The wellbore concavity parameters of each measuring point are normalized to obtain the normalized wellbore concavity parameters corresponding to each measuring point. The wellbore curvature parameters of each measuring point are normalized to obtain the normalized wellbore curvature parameters corresponding to each measuring point. The wellbore clearance ratio parameters of each measuring point are normalized to obtain the normalized wellbore clearance ratio parameters corresponding to each measuring point. The wellbore roughness value corresponding to each measuring point is determined based on the normalized wellbore concavity parameter, the normalized wellbore curvature parameter, and the normalized wellbore clearance ratio parameter.

4. The friction prediction method according to claim 3, characterized in that, The step of determining the basic friction value corresponding to the measuring point based on the wellbore roughness value and a preset modified mechanical model includes: For any target measuring point included in the target open hole section, the mechanical resistance value corresponding to the target measuring point is determined based on the wellbore roughness value corresponding to the target measuring point and the preset mechanical resistance coefficient. Substitute the basic friction value corresponding to the previous measuring point of the target measuring point, the length of the micro-segment corresponding to the target measuring point, the bending stiffness of the drill string, the normalized wellbore curvature parameter, the linear weight of the drill string, the well inclination angle and the mechanical resistance value into the modified mechanical model to calculate the axial force of the drill string corresponding to the target measuring point. The additional contact force corresponding to the target measuring point is determined based on the axial force of the drill string, and the basic friction value corresponding to the target measuring point is determined based on the additional contact force.

5. The friction prediction method according to claim 4, characterized in that, The step of determining the additional contact force corresponding to the target measuring point based on the axial force of the drill string includes: The additional contact force corresponding to the target measuring point is determined by a model based on the axial force of the drill string, the radial clearance of the drill string corresponding to the target measuring point, the bending stiffness of the drill string corresponding to the target measuring point, and the additional contact force.

6. The friction prediction method according to claim 4, characterized in that, The step of determining the basic friction value corresponding to the target measuring point based on the additional contact force includes: Determine the contact force per unit length of the sleeve corresponding to the target measuring point; The total contact force corresponding to the target measuring point is determined based on the contact force per unit length of the sleeve and the additional contact force corresponding to the target measuring point. The basic friction value corresponding to the target measuring point is determined based on the axial friction coefficient corresponding to the target open hole section and the total contact distribution force.

7. The friction prediction method according to any one of claims 1 to 6, characterized in that, Also includes: The friction curve corresponding to the target open hole section is determined based on the comprehensive friction value of each measuring point. Based on the preset friction threshold and the friction curve, the risk areas contained in the target open-hole section and the risk level corresponding to each risk area are determined.

8. A friction prediction device, characterized in that, include: The drilling data acquisition unit is used to acquire drilling data of measuring points contained in the target open hole section. The drilling data includes: wellbore type, measured well diameter, well inclination angle change rate, azimuth angle change rate, well inclination angle, casing diameter, drill string bending stiffness, drill string linear weight, and drill string wellbore radial clearance. The measuring point parameter determination unit is used to determine the measuring point parameters corresponding to the measuring point based on the drilling data, wherein the measuring point parameters include: well diameter concavity parameter, wellbore curvature parameter and wellbore clearance ratio parameter; A wellbore roughness value determination unit is used to determine the wellbore roughness value corresponding to the measuring point based on the measuring point parameters. The basic friction value determination unit is used to determine the basic friction value corresponding to the measuring point based on the wellbore roughness value and the preset modified mechanical model. The modified mechanical model is obtained by modifying the conventional mechanical model by taking the roughness of the irregular wellbore as an influencing factor. The comprehensive friction value determination unit is used to determine the comprehensive friction value corresponding to the measuring point based on the wellbore roughness value and the basic friction value. The wellbore roughness value determination unit is specifically used to substitute the wellbore diameter concavity parameter, wellbore curvature parameter, and wellbore clearance ratio parameter corresponding to each measuring point into a first preset formula to calculate the wellbore roughness value corresponding to each measuring point. The first preset formula is as follows: in, The roughness value of the wellbore corresponding to the measuring point. k represents the wellbore concavity parameter corresponding to the measuring point. b The wellbore curvature parameter corresponding to the measuring point. γ1, γ2, and γ3 are the wellbore clearance ratio parameters corresponding to the measuring points, and the weighting coefficients corresponding to the wellbore concavity parameter, wellbore curvature parameter, and wellbore clearance ratio parameter, respectively. The modified mechanical model is specifically as follows: Where F is the axial force of the drill string corresponding to the target measuring point, s is the length of the micro-element corresponding to the target measuring point, EI is the bending stiffness of the drill string corresponding to the target measuring point, and k b Here, q represents the normalized wellbore curvature parameter corresponding to the target measuring point, and q represents the drill string weight corresponding to the target measuring point. The well inclination angle corresponding to the target measuring point. This represents the basic friction value corresponding to the previous measuring point. k represents the mechanical resistance value corresponding to the target measuring point. f To preset the mechanical resistance coefficient, The wellbore roughness value corresponding to the target measuring point; The comprehensive friction value determination unit is specifically used to determine the mechanical resistance value corresponding to any measuring point by multiplying the wellbore roughness value corresponding to the measuring point with the preset mechanical resistance coefficient, summing the basic friction value and mechanical resistance value corresponding to the measuring point, and determining the calculation result as the comprehensive friction value corresponding to the measuring point.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 7.

11. 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 according to any one of claims 1 to 7.

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