Method and system for improving drilling simulation calculation speed and accuracy

Abstract

The present invention discloses a method for improving the speed and accuracy of drilling simulation calculation, including: predicting the downhole risk of the well to be simulated in the current simulation environment according to the historical case data and simulation data of the well to be simulated, and determining the range of the well section with risks in the well; determining the first grid density required for the wellbore model formed by the simulation environment in the drilling simulation calculation according to the preset simulation accuracy, and adjusting the first grid density corresponding to different risk sections and different risk-free sections according to the downhole risk prediction result; performing drilling simulation calculation according to the calculation step size under the adjusted first grid density corresponding to each section. The present invention realizes the simultaneous improvement of the speed and accuracy of drilling simulation, is low in cost, and is more in line with actual application conditions.

Description

Technical Field

[0001] The invention relates to the field of petroleum engineering, and in particular to a method and a system for improving the speed and accuracy of drilling simulation calculation. Background Art

[0002] As an underground hidden project, drilling engineering has a large number of heterogeneous, uncertain, non-structural and non-numerical problems that constitute the "black box" of drilling engineering. The high temperature and high pressure environment underground, the high frequency vibration of the drill string, the high speed flow of mud in the drill string annulus and the long-term drilling operation all have extremely stringent requirements on sensors, and it is impossible to rely on sensing tools to achieve stable and accurate monitoring of the underground state for a long time. At present, the solution to the "black box" problem of drilling engineering mainly relies on the application of existing theoretical methods to simulate and calculate various underground state parameters such as equivalent circulating density and friction torque. The presentation of the "black box" results relies on demonstration methods such as two-dimensional curves and three-dimensional animations, thereby providing decision-making references for on-site engineers and experts.

[0003] If the simulation calculation of downhole drilling parameters is to be as accurate as possible, the wellbore model needs to be divided into dense grids and long-term massive iterative calculations need to be performed; and the uncertainty of drilling engineering requires on-site engineers and experts to make timely judgments and decisions, that is, to increase the speed of simulation calculations as much as possible. In practical applications, since most users have average computer performance and network conditions, they cannot use cloud computing, distributed computing, etc. to improve computing power, which makes it difficult to improve the speed of drilling simulation and the accuracy of drilling simulation. It is difficult to achieve simultaneous improvement of simulation speed and accuracy. In particular, the deeper the well depth corresponding to the simulation environment, the greater the amount of simulation calculations, and the longer the waiting time for business experts to see the simulation results. There is a large delay, which affects the real-time decision-making of business experts using drilling simulation results.

[0004] In the existing drilling simulation calculation technology, a technical solution that can only improve the calculation speed or the accuracy of the calculation result is often provided, but a technical solution that can improve both the drilling simulation calculation speed and the accuracy is lacking. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method for improving the speed and accuracy of drilling simulation calculations, including: a risk section division step, based on the historical case data of the well to be simulated and the simulation data required for the drilling simulation, the downhole risk prediction of the well to be simulated in the current simulation environment is carried out to determine the range of the well section with risks in the well; a step adjustment step, based on the preset simulation accuracy, determining the first grid density corresponding to the wellbore model formed by the current simulation environment in the drilling simulation calculation, and according to the downhole risk prediction results, adjusting the first grid density corresponding to different risk sections and different risk-free sections; a simulation step, based on the calculation step size under the adjusted first grid density corresponding to each section, performing drilling simulation calculations.

[0006] Preferably, the method further includes: obtaining a second grid density for each well section after adjusting the first grid density, and counting the total number of grids in the well; comparing the total number of grids with the first total number of grids to determine whether the current calculation accuracy exceeds the preset accuracy, and if not, performing simulation calculations according to the second grid density corresponding to each well section, wherein the first total number of grids is the total number of grids corresponding to the uniform grid division of the wellbore formed in the current simulation environment that has not undergone grid adjustment according to the expected simulation accuracy.

[0007] Preferably, the step size adjustment step includes: determining the simulation accuracy of the corresponding well section according to the risk prediction results of different risk well sections in the well; and re-dividing the simulation calculation iteration points in each risk well section according to the simulation accuracy of the corresponding well section and the second grid length or second grid density after the grid adjustment of each well section, so as to obtain the second calculation step size corresponding to each risk well section, wherein the second grid length is smaller than the length corresponding to the first grid density, and the second grid density is larger than the first grid density.

[0008] Preferably, the step size adjustment step also includes: re-dividing the simulation calculation iteration points in different risk-free well sections in the well according to a preset risk-free well grid density threshold and a risk-free well length threshold, to obtain a second calculation step size corresponding to each risk-free well section, wherein the risk-free well length threshold is greater than the length corresponding to the first grid density, and the risk-free well density threshold is less than the first grid density.

[0009] Preferably, the risk section division step includes: establishing a case database for the oil field block where the well to be simulated is located, and using it as the historical case data; collecting the simulation data including drilling design parameters and real-time drilling data; using data mining analysis technology to compare and analyze the simulation data with the risk data in the historical case data; and determining the depth range of the risky sections and the depth range of other risk-free sections based on the comparison and analysis results.

[0010] On the other hand, the present invention also provides a system for improving the speed and accuracy of drilling simulation calculations, including: a risk section division module, which is configured to predict the downhole risk of the well to be simulated in the current simulation environment based on the historical case data of the well to be simulated and the simulation data required for the drilling simulation, and determine the range of the well sections with risks in the well; a step adjustment module, which is configured to determine the first grid density corresponding to the wellbore model formed by the current simulation environment in the drilling simulation calculation according to a preset simulation accuracy, and adjust the first grid density corresponding to different risk sections and different risk-free sections according to the downhole risk prediction results; a simulation module, which is configured to perform drilling simulation calculations according to the calculation step size under the adjusted first grid density corresponding to each well section.

[0011] Preferably, the system also includes a global adjustment module, wherein the global adjustment module includes: a total grid number counting unit, which is configured to obtain a second grid density for each well section after the first grid density is adjusted, and count the total number of grids in the well; a global adjustment unit, which is configured to compare the total number of grids with the first total number of grids to determine whether the current calculation accuracy exceeds the preset accuracy. If not, simulation calculation is performed according to the second grid density corresponding to each well section, wherein the first total number of grids is the total number of grids corresponding to the uniform grid division of the wellbore formed in the current simulation environment that has not undergone grid adjustment according to the expected simulation accuracy.

[0012] Preferably, the step adjustment module includes: a risk section accuracy generation unit, which is configured to determine the simulation accuracy of the corresponding section according to the risk prediction results of different risk sections in the well; a first adjustment unit, which is configured to re-divide the simulation calculation iteration points in each risk section according to the simulation accuracy of the corresponding section and the second grid length or second grid density after adjustment of each section grid, to obtain the second calculation step corresponding to each risk section, wherein the second grid length is smaller than the length corresponding to the first grid density, and the second grid density is larger than the first grid density.

[0013] Preferably, the step adjustment module also includes: a second adjustment unit, which is configured to re-divide the simulation calculation iteration points in different risk-free sections in the well according to a preset risk-free grid density threshold and a risk-free grid length threshold, to obtain a second calculation step corresponding to each risk-free section, wherein the risk-free grid length threshold is greater than the length corresponding to the first grid density, and the risk-free grid density threshold is less than the first grid density.

[0014] Preferably, the risk well section division module includes: a historical case construction unit, which is configured to establish a case database for the oil field block where the well to be simulated is located, and use it as the historical case data; a simulation data generation unit, which is configured to collect the simulation data including drilling design parameters and real-time drilling data; a risk prediction unit, which is configured to use data mining analysis technology to compare and analyze the simulation data with the risk data in the historical case data; a well section division unit, which is configured to determine the depth range of the well section with risk and the depth range of other risk-free well sections based on the comparison and analysis results.

[0015] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0016] The present invention discloses a method and system for improving the speed and accuracy of drilling simulation calculation. The method and system apply data analysis technology to compare and analyze simulation data with historical case data of a large number of complex situations in oil fields, predict potential risk sections, increase the density of calculation grids for sections where risks may occur during simulation calculations, and reduce the density of calculation grids for non-risk sections, thereby achieving a dual improvement in drilling simulation speed and accuracy. Compared with the method of evenly dividing calculation grids in existing drilling simulation methods, the present invention ensures the improvement of simulation calculation speed by appropriately encrypting and loosening the wellbore calculation grid under the condition of certain user computer performance. In addition, the present invention improves the accuracy of simulation calculation by analyzing design data and historical case data, predicting high-risk sections in advance for encrypted simulation calculations. In addition, the improvement of simulation speed of the present invention does not require distributed computing and cloud computing with higher broadband speeds of local area network servers and cloud services, which is lower in cost and more in line with actual application situations.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0019] Figure 1 It is a step diagram of a method for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application.

[0020] Figure 2 It is a schematic diagram of the principle of a method for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application.

[0021] Figure 3 It is a specific flow chart of a method for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application.

[0022] Figure 4 It is a module block diagram of a system for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0024] As an underground hidden project, drilling engineering has a large number of heterogeneous, uncertain, non-structural and non-numerical problems that constitute the "black box" of drilling engineering. The high temperature and high pressure environment underground, the high frequency vibration of the drill string, the high speed flow of mud in the drill string annulus and the long-term drilling operation all have extremely stringent requirements on sensors, and it is impossible to rely on sensing tools to achieve stable and accurate monitoring of the underground state for a long time. At present, the solution to the "black box" problem of drilling engineering mainly relies on the application of existing theoretical methods to simulate and calculate various underground state parameters such as equivalent circulating density and friction torque. The presentation of the "black box" results relies on demonstration methods such as two-dimensional curves and three-dimensional animations, thereby providing decision-making references for on-site engineers and experts.

[0025] If the simulation calculation of downhole drilling parameters is to be as accurate as possible, the wellbore model needs to be divided into dense grids and long-term massive iterative calculations need to be performed; and the uncertainty of drilling engineering requires on-site engineers and experts to make timely judgments and decisions, that is, to increase the speed of simulation calculations as much as possible. In practical applications, since most users have average computer performance and network conditions, they cannot use cloud computing, distributed computing, etc. to improve computing power, which makes it difficult to improve the speed of drilling simulation and the accuracy of drilling simulation. It is difficult to achieve simultaneous improvement of simulation speed and accuracy. In particular, the deeper the well depth corresponding to the simulation environment, the greater the amount of simulation calculations, and the longer the waiting time for business experts to see the simulation results. There is a large delay, which affects the real-time decision-making of business experts using drilling simulation results.

[0026] In the existing drilling simulation calculation technology, a technical solution that can only improve the calculation speed or the accuracy of the calculation result is often provided, but a technical solution that can improve both the drilling simulation calculation speed and the accuracy is lacking.

[0027] In order to solve the defects of the prior art, the present invention proposes a method and system that can simultaneously improve the speed and accuracy of drilling simulation calculations. The method and system use data analysis technology to compare and analyze simulation design data with historical case data of a large number of complex situations in oil fields, predict potential risk sections, increase the calculation grid density for sections where risks may occur, and reduce the calculation grid density for non-risk sections during the simulation calculation process, thereby achieving a dual improvement in drilling simulation speed and accuracy, and providing users with more reliable reference results while performing rapid drilling simulation calculations.

[0028] Before describing the embodiments of the present invention in detail, it is necessary to describe the applicable occasions of the present invention. The method of the present invention can be used for simulation preview of the scheme before drilling or for simulation monitoring during the actual drilling process. In the pre-drilling simulation process, it is necessary to simulate the actual drilling process to push the parameters in the drilling design scheme to the simulation main module at a certain time interval (seconds). The simulation main module displays the downhole state through a vivid three-dimensional scene. After continuous data push and simulation display, the continuous process of drilling can be seen. In this continuous simulation process, for each time point, different categories of drilling key parameters such as wellbore hydraulic parameters, drill friction torque, mechanical drilling speed, drilling risks, etc. can be calculated and quickly fed back to the simulation software, so that the original data is "synchronized" with the calculation results. In the process of real-time drilling simulation monitoring, the parameters (seconds interval) transmitted in real time are collected on site and distributed to the calculation module at the same time to obtain different categories of drilling (key) parameters (calculation results), and the current calculation results are fed back to the simulation main module to ensure the simulation of this high-frequency continuous drilling process.

[0029] In addition, in the drilling simulation system, whether it is pre-drilling simulation or drilling simulation, the drilling simulation results displayed are all based on the results limited by the simulation environment. Among them, the simulation environment includes: starting well depth, ending well depth, and simulation accuracy. Since the ending well depth changes with the continuous deepening of the drilling depth during the drilling simulation process, the simulation environment of the drilling simulation also changes in real time. In addition, the simulation accuracy is the calculation step length (depth step length) of the drilling simulation process.

[0030] Figure 1 1 is a step diagram of a method for improving the speed and accuracy of drilling simulation calculations in an embodiment of the present application. Figure 1 As shown, the method for improving the calculation speed and accuracy of drilling simulation in the present invention (hereinafter referred to as "simulation method") is first described. First, step S110 needs to predict the downhole risk of the well to be simulated under the current simulation environment based on the historical case data of the well to be simulated and the simulation data required for the current drilling simulation, and determine the range of the well section that may be at risk in the current well, as well as the range of the remaining well sections. The simulation data required for drilling simulation include: various measured data collected during the actual drilling process, and various pre-designed static parameters (design parameters). Among them, the measured data include: geological data and drilling engineering data, the geological data include formation pressure, rock physical properties, rock mechanical parameters, etc.; the drilling engineering data include wellbore trajectory, drill bit assembly, drilling fluid performance, drilling construction parameters, etc. Drilling design parameters include: well depth structure, formation stratification, etc.

[0031] In step S110, it is necessary to perform downhole risk prediction calculation for the simulated well under the current simulation environment based on the above-mentioned simulation data and historical case data, and determine the depth range of the risky well section in the well section at different locations downhole, and the depth range of the risk-free well section at different locations. It should be noted that in the embodiment of the present invention, reference Figure 3 The risk section in the whole wellbore can be one or more, which is determined according to the downhole risk prediction results. Each risk section has a corresponding depth range. Among them, the risk section refers to the depth range where any one or more potential risks such as well leakage, well kick, pipe sticking, well wall instability, etc. may occur. In addition, continue to refer to Figure 3 , the other depth ranges in the entire wellbore except for one or more risky sections are divided into corresponding risk-free sections. At this time, the current wellbore is divided into risk-free sections and risky sections of different depth ranges that are alternately distributed.

[0032] After completing the risk section division process, proceed to step S120. Step S120 determines the first grid density required for the wellbore model in the drilling simulation calculation (for example, two grids per meter) according to the preset expected simulation accuracy (for example, one grid point is simulated and calculated every 0.5 meters of depth), and adjusts the first grid density corresponding to different risk sections and different risk-free sections according to the downhole risk prediction results to obtain the second grid density for each section. In conventional drilling simulation calculations, a wellbore model is usually used to simulate the downhole drilling process for simulation calculations. Further, refer to Figure 3 In conventional methods, the wellbore model is evenly divided into several equal-length grids (for example, the grid length is 0.5 meters), which are distributed in turn at different depths in the well. Through the depth accumulation iteration method, the drilling process is simulated in real time as the well depth increases. Using this method, on the one hand, the simulation calculation of the underground distribution of some parameters such as hydraulic parameters and friction torque needs to be repeated iteratively calculated from the wellhead to the bottom of the well and then from the bottom of the well to the wellhead according to the grid division until the error is less than the critical threshold and the iterative calculation converges. The amount of calculation increases sharply with the increase of grid division. On the other hand, the goal of drilling simulation calculation is to predict drilling risks. The uniform division of the whole well grid cannot help drilling simulation to conduct a detailed analysis of the risk-prone well section. When the whole well grid is evenly divided (for example, the grid length is 0.5 meters), the calculation node may cross the risk point, and the risk cannot be predicted through simulation. To this end, in an embodiment of the present invention, it is first necessary to determine the depth step of the current simulation calculation (under the current simulation environment) according to the preset expected simulation accuracy. This depth step represents the expected grid length corresponding to the uniform division of the downhole grid in the conventional simulation calculation. At this time, for the entire wellbore model, the number of grids contained in the unit depth is the first grid density. Then, according to the risk prediction result obtained in step S110, during the simulation calculation process, the calculation grid density is increased for the possible well section to perform grid encryption calculation; for the risk-free well section, the calculation grid density needs to be reduced to perform grid loose calculation. In this way, compared with the fine calculation of the uniform grid of the whole well, the amount of calculation can be greatly reduced. While improving the drilling simulation speed, the calculation accuracy of the drilling simulation can also be improved by encrypting the risk section, and the loose calculation of the risk-free section will not affect the calculation accuracy, thereby achieving a double improvement in the speed and accuracy of the drilling simulation.

[0033] Further, after the grid adjustment operation is completed, the process proceeds to step S130. Step S130 is based on the calculation step length (depth step length) under the adjusted first grid density corresponding to each well section, that is, the drilling simulation calculation needs to be performed according to the second grid density corresponding to each well section obtained in step S120.

[0034] Figure 2It is a schematic diagram of the principle of a method for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application. Figure 3 This is a specific flow chart of the method for improving the speed and accuracy of drilling simulation calculation in the embodiment of the present application. Figure 2 and Figure 3 The simulation method of the present invention is described in detail. In an embodiment of the present invention, downhole risks are continuously implemented as the simulation environment range (especially the depth range) changes during the drilling process. It is necessary to perform real-time risk prediction analysis on the corresponding changing simulation environment in real-time simulation calculation according to the following steps S301 to S304. Step S301 establishes a case database for the oil field block where the current well to be simulated is located, collects historical data of various complex situations and risks, and loads the historical data in the above-mentioned case database to form historical case data containing risk information. Among them, the various complex situations and risks loaded include: well leakage, well kick, stuck drill, well wall instability, etc. The historical case data includes: well number, risk type, formation rock cuttings, risk occurrence well depth, well depth structure, drilling tool assembly, drilling fluid properties, real-time engineering parameters (for example: drilling pressure, rotation speed, displacement, tripping speed, etc.) within a period of time before and after the risk occurs, etc. It should be noted that, in the embodiment of the present invention, the historical case data generated by step S301 is generated based on the established case database and the collected historical data before the drilling process is implemented. Step S302 obtains the simulation data required for the drilling simulation calculation. Among them, the simulation data includes: drilling design parameters (i.e., the various pre-designed static parameters mentioned above), and real-time drilling data. It should be noted that the subsequent steps after step S302 are all implemented in the real-time simulation calculation process under the current simulation environment.

[0035] Further, step S303 utilizes data mining and analysis technology, and adopts data analysis method (for example: spatial distance method) to compare and analyze the current simulation data with a large number of complex situations and risk case data in the historical case data, and predict the well section where potential risks may occur in the current well to be simulated. Specifically, first, it is necessary to extract the data items in the simulation data that are the same as the historical case data, and use data analysis methods such as spatial distance method to calculate the similarity between the measured data in the simulation data and the risk data in different cases (the calculation results are normalized). If the similarity exceeds a certain risk discrimination threshold, it is considered that the simulation well is very likely to have the same risk in this well section (for example, the well leakage risk discrimination threshold is 0.8, the well kick risk discrimination threshold is 0.7, the drill stuck risk discrimination threshold is 0.86, etc.). It should be noted that in the embodiment of the present invention, the risk data in the historical well case data is the risk record that actually occurred during the drilling process of the historical well, and the simulation data is compared with the actual risk data in the historical well.

[0036] Then, step S304 determines the depth range of one or more risky well sections and the depth range of one or more risk-free well sections in the entire wellbore based on the comparative analysis result (risk prediction result) of step S303.

[0037] Then, after completing the above-mentioned risk section and risk-free section division operation, enter step S305. Step S305 determines the first grid density (expected grid density) and the first grid length (calculation depth step, expected grid length) corresponding to the calculation grid that needs to be divided into the wellbore model formed by the current simulation environment according to the expected simulation accuracy set by the user. Among them, the expected simulation accuracy is the simulation accuracy corresponding to the uniform division operation of the full well grid in the conventional method. The grid is formed by each simulation iterative calculation point in the wellbore model. In the conventional grid division operation, the interval length between each adjacent simulation iterative point is equal.

[0038] Further, step S306 performs encryption adjustment on the grid formed by each simulation iteration point in each risk section according to the risk prediction result. Specifically, the simulation accuracy of the corresponding section is determined according to the risk prediction results of different risk sections in the well; then, according to the simulation accuracy of the corresponding section, the simulation calculation iteration points in each risk section are re-divided according to the second grid length or second grid density after the grid adjustment of each section, to obtain the second calculation step corresponding to each risk section. Among them, the second grid length is less than the length corresponding to the first grid density, and the second grid density is greater than the first grid density. In this way, after resetting the grid length and the corresponding grid density for each risk section, the effect of reducing the grid length and increasing the grid density can be achieved, thereby completing the encryption adjustment of the calculation grid, which can simultaneously improve the simulation accuracy and accuracy of the risk section.

[0039] Furthermore, since there may be one or more risk sections in the well, in one embodiment, the same second grid density and its corresponding second grid length can be set for each risk section in the well. The first grid length corresponding to each risk section is adjusted to the second grid length, and the first grid density of each risk section is adjusted to the second grid density, so as to perform simulation calculation with the second grid length in step S309. Among them, the second grid density is greater than the first grid density, and the second grid length is less than the first grid length. For example, if the expected simulation accuracy set by the user is to divide a grid into one grid per 0.5 meters of depth as an iteration point in the simulation calculation, at this time, the expected grid length is 0.5 meters. Then, in step S306, it is necessary to re-divide each risk section according to the second grid density or the second grid length, so as to form multiple simulation iteration points with the second grid density or the second grid length interval characteristics in each risk section to form a new grid structure. For example: the second grid density is 10 grids per 1 meter of depth, and the second grid length is 0.1 meters.

[0040] In another embodiment of step S306, different second grid densities and corresponding second grid lengths can be set for each risk section in the well. Specifically, first, S3061 obtains the depth range of different risk sections in the well, and then, S3062 determines the simulation accuracy of the corresponding section according to the depth range corresponding to each risk section. In the embodiment of the present invention, different depth ranges correspond to different simulation accuracy. Since the number of risk sections in the well will not be too many in the actual application process, the risk sections farther from the wellhead are affected by the increasingly complex environment such as formation pressure and temperature. Compared with the risk sections closer to the wellhead, the risk coefficients faced are higher, and therefore, they should have higher simulation accuracy, so it is necessary to strengthen the simulation monitoring of deeper risk sections. Therefore, in the embodiment of the present invention, different second grid densities and corresponding second grid lengths are usually set for risk sections of different depths. Further, higher simulation accuracy corresponds to higher second grid density and corresponding lower second grid length; on the contrary, lower simulation accuracy corresponds to lower second grid density and corresponding higher second grid length. Next, S3063 re-divides the calculation grid of the corresponding well section according to the simulation accuracy corresponding to different well sections, and sets the second grid density and the second grid length corresponding to the current simulation accuracy for the corresponding well section, so as to achieve the purpose of reducing the length of the first calculation step and increasing the first grid density, and obtains the second calculation step (second grid length) corresponding to each risk well section, so as to perform simulation calculation with the second grid length in step S309.

[0041] refer to Figure 2 ,based on Figure 2In the simulation environment, there are two risk sections, the risk section closest to the wellhead on the upper side is determined as the first risk section, and the risk section farther from the wellhead on the lower side is determined as the second risk section. When adjusting the grid encryption for these two sections, first obtain the depth range of the first risk section and the second risk section. Then, determine the simulation accuracy of the first risk section and the second risk section respectively. Among them, the simulation accuracy of the second risk section is higher than the simulation accuracy of the first risk section, for example: the simulation accuracy of the first risk section is one grid for every 0.25 meters of depth, and the simulation accuracy of the second risk section is one grid for every 0.2 meters of depth. Then, set the second grid density and the corresponding second grid length for the first risk section, and set the second grid density and the corresponding second grid length for the second risk section. Among them, the second grid length of the second risk section is less than the second grid length of the first risk section, and the second grid density of the second risk section is greater than the second grid density of the first risk section. For example: the second grid length of the first risk section is 0.25 meters, the second grid density of the first risk section is 4 grids per 1 meter, the second grid length of the second risk section is 0.2 meters, and the second grid density of the second risk section is 5 grids per 1 meter.

[0042] After the grid adjustment is performed on each risk section, the process proceeds to step S307 to perform grid adjustment on the remaining risk-free sections. Step S307 performs grid loosening adjustment on the risk-free sections at different locations according to the preset risk-free grid density threshold and risk-free grid length threshold. Specifically, it is necessary to re-divide the simulation calculation iteration points in different risk-free sections in the well according to the preset risk-free grid density threshold, and use the risk-free grid density threshold as the second grid density of each risk-free section, and use the risk-free grid length threshold as the second grid length of each risk-free section, so as to achieve the effect of increasing the grid length and reducing the grid density, thereby completing the loose adjustment of the calculation grid, and then performing simulation calculation with the second grid length (second calculation step) in step S309. Among them, the risk-free grid density threshold is less than the first grid density, and the risk-free grid length threshold is greater than the first grid length. Therefore, although this adjustment method will reduce the simulation accuracy of the risk-free section, it will not affect the simulation accuracy. For example, in the embodiment of the present invention, the underground risk-free grid density threshold is 1 grid per 1 meter; the underground risk-free grid length threshold is 1 meter.

[0043] Thus, the above-mentioned grid adjustment process for each risk-free well section and each risk-free well section is completed, and then the process proceeds to step S308. Step S308 performs a global grid adjustment on each risk-free well section and risk-free well section after the grid adjustment process according to the above-mentioned expected simulation accuracy. Specifically, the total number of grids after the grid adjustment process in the current simulation environment is first counted (see Figure 2 According to the current total number of grids, it is determined whether the current calculation accuracy exceeds the preset expected simulation accuracy. If not, the simulation calculation is performed according to the second grid density corresponding to each well section in step S309. Figure 2 Furthermore, if the former is less than or equal to the latter, the current calculation accuracy does not exceed the expected simulation accuracy; if the former is greater than the latter, the current calculation accuracy exceeds the expected simulation accuracy. The above-mentioned first total number of grids is the total number of grids corresponding to the uniform division of the grids of the entire well according to the expected simulation accuracy when the wellbore formed between the starting well depth and the ending well depth corresponding to the current simulation environment that has not undergone grid adjustment (before the grid adjustment process is implemented).

[0044] In addition, if the current calculation accuracy exceeds the expected simulation accuracy, it is necessary to return to step S306 to re-set the simulation accuracy of each risk section, appropriately reduce the simulation accuracy of each risk section, and control the average density of the entire well of the encrypted grid and the loose grid so that it does not exceed the expected grid density (or expected simulation accuracy) required to achieve the user's expected simulation accuracy conditions. Therefore, although the present invention increases the grid density of the risk section, it still monitors the total number of grids of the wellbore formed by the current simulation environment, reduces the number of grid divisions of the entire well, and further reduces the amount of calculation of the drilling simulation calculation on the basis of ensuring the accuracy and rapidity of the simulation results.

[0045] Further, step S309 applies the second calculation step (second grid length) corresponding to all well sections after encryption and loose adjustment to perform drilling simulation calculation, completes the drilling simulation at a faster speed and higher accuracy, and outputs the final drilling simulation results to the user.

[0046] For example, the simulation method described in the embodiment of the present invention is applied in the drilling simulation of Well X in the Northwest Oilfield, and the specific implementation process is as follows:

[0047] (1) Establish a database of drilling complexities and risk cases for the entire Northwest Oilfield and load historical case data for the block where Well X is located;

[0048] (2) Collect various data related to Well X, such as design data and real-time data, and compare and analyze various risk data in historical case data of the block where Well X is located by applying data analysis methods such as spatial distance calculation;

[0049] (3) Through analysis, predict the range of well sections where drilling complications and risks may occur in Well X, as well as the range of risk-free well sections;

[0050] (4) according to the expected drilling simulation accuracy set by the user (for example, one point is simulated and calculated every 0.5 m depth), the first grid density and the total number of first grids for evenly dividing the wellbore of well X are determined;

[0051] (5) According to the potential risk prediction results of Well X, the computational grid of the risk section is adjusted based on the first grid density to improve the simulation precision and accuracy of the section; the computational grid of the risk-free section is adjusted based on the first grid density to reduce the simulation precision of the section, but since it is risk-free, it does not affect the simulation accuracy; the total amount of grids after grid encryption and loose adjustment is controlled to be less than the number of grids evenly divided under the expected drilling simulation accuracy (the total number of first grids), thereby improving the simulation calculation speed;

[0052] (6) By performing drilling simulation on the entire well X, the application effect of the present invention is compared with the conventional uniform grid division simulation effect. The drilling simulation calculation speed can be increased by 35%, the simulation time can be compressed by 25%, and the location and time simulation of complex drilling situations are more accurate. This proves that the method of the present invention can effectively achieve the simultaneous improvement of drilling simulation speed and accuracy.

[0053] On the other hand, based on the above method for improving the speed and accuracy of drilling simulation calculations, the present invention proposes a system for improving the speed and accuracy of drilling simulation calculations (hereinafter referred to as "simulation system"). Figure 4 is a block diagram of a system for improving the speed and accuracy of drilling simulation calculations according to an embodiment of the present application. Figure 4As shown, the simulation system includes: a risk section division module 41, a step adjustment module 42 and a simulation module 43. Among them, the risk section division module 41 is implemented according to the above step S110, and is configured to predict the downhole risk of the well to be simulated in the current simulation environment according to the historical case data of the well to be simulated and the simulation data required for the drilling simulation, and determine the range of the well section with risks in the well. The step adjustment module 42 is implemented according to the above step S120, and is configured to determine the first grid density required for the wellbore model formed by the current simulation environment in the drilling simulation calculation according to the preset simulation accuracy, and adjust the first grid density corresponding to different risk sections and different risk-free sections according to the downhole risk prediction results. The simulation module is implemented according to the above step S130, and is configured to perform drilling simulation calculations according to the calculation step size under the adjusted first grid density corresponding to each well section.

[0054] The simulation system described in the present invention also includes: a global adjustment module 44. The global adjustment module 44 is configured to perform global grid adjustment on each risk section and risk-free section after the grid adjustment process according to the above-mentioned expected simulation accuracy. Further, the global adjustment module 44 includes: a total grid number statistics unit 441 and a global adjustment unit 442. The total grid number statistics unit 441 is configured to obtain the second grid density for each section after the first grid density is adjusted, and to count the total number of grids in the well. The global adjustment unit 442 is configured to compare the current total number of grids with the first total number of grids to determine whether the current calculation accuracy exceeds the preset accuracy. If not, the simulation calculation is performed according to the second grid density corresponding to each section. The first total number of grids is the total number of grids corresponding to the uniform grid division of the wellbore formed in the current simulation environment that has not undergone grid adjustment according to the expected simulation accuracy.

[0055] Furthermore, the step adjustment module 42 includes: a risk section accuracy generation unit 421 and a first adjustment unit 422. The risk section accuracy generation unit 421 is configured to determine the simulation accuracy of the corresponding section according to the risk prediction results of different risk sections in the well. The first adjustment unit 422 is configured to re-divide the simulation calculation iteration points in each risk section according to the simulation accuracy of the corresponding section and the second grid length or second grid density after the grid of each section is adjusted, so as to obtain the second calculation step corresponding to each risk section. The second grid length is less than the length corresponding to the first grid density, and the second grid density is greater than the first grid density.

[0056] Furthermore, the step adjustment module 42 further includes: a second adjustment unit 423. The second adjustment unit 423 is configured to re-divide the simulation calculation iteration points in different risk-free well sections in the well according to the preset risk-free well grid density threshold and the risk-free well grid length threshold, so as to obtain the second calculation step corresponding to each risk-free well section. The risk-free well grid length threshold is greater than the length corresponding to the first grid density, and the risk-free well grid density threshold is less than the first grid density.

[0057] Furthermore, the above-mentioned risk section division module 41 includes: a historical case construction unit 411, a simulation data generation unit 412, a risk prediction unit 413 and a section division unit 414. The historical case construction unit 411 is configured to establish a case database for the oil field block where the well to be simulated is located, and use it as historical case data. The simulation data generation unit 412 is configured to collect simulation data including drilling design parameters and real-time drilling data. The risk prediction unit 413 is configured to use data mining analysis technology to compare and analyze the simulation data with the risk data in the historical case data. The section division unit 414 is configured to determine the depth range of the risky section and the depth range of other risk-free sections based on the comparative analysis results.

[0058] The present invention discloses a method and system for improving the speed and accuracy of drilling simulation calculation. The method and system apply data analysis technology to compare and analyze simulation data with historical case data of a large number of complex situations in oil fields, predict potential risk sections, increase the density of calculation grids for sections where risks may occur during simulation calculations, and reduce the density of calculation grids for non-risk sections, thereby achieving a dual improvement in drilling simulation speed and accuracy. Compared with the method of evenly dividing calculation grids in existing drilling simulation methods, the present invention ensures the improvement of simulation calculation speed by appropriately encrypting and loosening the wellbore calculation grid under the condition of certain user computer performance. In addition, the present invention improves the accuracy of simulation calculation by analyzing design data and historical case data, predicting high-risk sections in advance for encrypted simulation calculations. In addition, the improvement of simulation speed of the present invention does not require distributed computing and cloud computing with higher broadband speeds of local area network servers and cloud services, which is lower in cost and more in line with actual application situations.

[0059] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for improving the speed and accuracy of drilling simulation calculations, characterized in that: include: The risk section division step is to predict the downhole risk of the well to be simulated under the current simulation environment based on the historical case data of the well to be simulated and the simulation data required for drilling simulation, and determine the scope of the well section with risks in the well; The step of adjusting the step size is to determine the first grid density corresponding to the wellbore model formed by the current simulation environment in the drilling simulation calculation according to the preset simulation accuracy, and to adjust the first grid density corresponding to different risk sections and different risk-free sections according to the downhole risk prediction result; Simulation step, performing drilling simulation calculation according to the calculation step length under the adjusted first grid density corresponding to each well section; The step length adjustment step comprises: According to the risk prediction results of different risk sections in the well, the simulation accuracy of the corresponding sections is determined; According to the simulation accuracy of the corresponding well section, the simulation calculation iteration points in each risk well section are re-divided according to the second grid length or the second grid density after the grid of each well section is adjusted, so as to obtain a second calculation step length corresponding to each risk well section, wherein the second grid length is smaller than the length corresponding to the first grid density, and the second grid density is larger than the first grid density; According to the preset downhole risk-free grid density threshold and the downhole risk-free grid length threshold, the simulation calculation iteration points in different risk-free well sections in the downhole are re-divided to obtain a second calculation step corresponding to each risk-free well section, wherein the downhole risk-free grid length threshold is greater than the length corresponding to the first grid density, and the downhole risk-free grid density threshold is less than the first grid density.

2. The method according to claim 1, characterized in that The method further comprises: After adjusting the first grid density, a second grid density for each well section is obtained, and the total number of grids in the well is counted; The total number of grids is compared with the total number of the first grids to determine whether the current calculation accuracy exceeds the preset accuracy. If not, simulation calculation is performed according to the second grid density corresponding to each well section, wherein the total number of the first grids is the total number of grids corresponding to the uniform grid division of the wellbore formed in the current simulation environment that has not been grid adjusted according to the expected simulation accuracy.

3. The method according to claim 1 or 2, characterized in that: The risk well section division step includes: Establishing a case database of the oil field block where the well to be simulated is located, and using it as the historical case data; Collecting the simulation data including drilling design parameters and real-time drilling data; Using data mining analysis technology, compare and analyze the simulation data with the risk data in the historical case data; Based on the comparative analysis results, the depth range of the risky well section and the depth range of other risk-free well sections are determined.

4. A system for improving the speed and accuracy of drilling simulation calculations, characterized in that: include: The risk section division module is configured to predict the downhole risk of the well to be simulated under the current simulation environment according to the historical case data of the well to be simulated and the simulation data required for drilling simulation, and determine the scope of the well section with risks in the well; A step size adjustment module, configured to determine a first grid density corresponding to a wellbore model formed by the current simulation environment in a drilling simulation calculation according to a preset simulation accuracy, and adjust the first grid density corresponding to different risk sections and different risk-free sections according to a downhole risk prediction result; A simulation module configured to perform drilling simulation calculations according to a calculation step length corresponding to each well section under an adjusted first grid density; The step size adjustment module comprises: A risk section accuracy generating unit configured to determine the simulation accuracy of the corresponding section according to the risk prediction results of different risk sections in the well; A first adjustment unit is configured to re-divide the simulation calculation iteration points in each risk well section according to the simulation accuracy of the corresponding well section and the second grid length or the second grid density after the grid of each well section is adjusted, so as to obtain a second calculation step length corresponding to each risk well section, wherein the second grid length is smaller than the length corresponding to the first grid density, and the second grid density is larger than the first grid density; The second adjustment unit is configured to re-divide the simulation calculation iteration points in different risk-free well sections in the well according to a preset risk-free well density threshold and a risk-free well length threshold, so as to obtain a second calculation step length corresponding to each risk-free well section, wherein the risk-free well length threshold is greater than the length corresponding to the first grid density, and the risk-free well density threshold is less than the first grid density.

5. The system according to claim 4, characterized in that The system further includes a global adjustment module, wherein the global adjustment module includes: A total grid number counting unit, configured to obtain a second grid density for each well section after adjusting the first grid density, and count the total number of grids in the well; A global adjustment unit is configured to compare the total number of grids with the first total number of grids to determine whether the current calculation accuracy exceeds the preset accuracy. If not, simulation calculation is performed according to the second grid density corresponding to each well section, wherein the first total number of grids is the total number of grids corresponding to the uniform grid division of the wellbore formed in the current simulation environment that has not undergone grid adjustment according to the expected simulation accuracy.

6. The system according to claim 4 or 5, characterized in that: The risk well section division module includes: A historical case building unit, configured to establish a case database of the oil field block where the well to be simulated is located, and use it as the historical case data; A simulation data generating unit configured to collect the simulation data including drilling design parameters and drilling real-time data; a risk prediction unit configured to compare and analyze the simulation data with risk data in the historical case data using data mining analysis technology; The well section division unit is configured to determine the depth range of the well section with risk and the depth range of other well sections without risk according to the comparative analysis result.

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