Multi-objective Optimization Method of Drilling Parameters Based on Kinetic Stability Constraint

Abstract

The present invention belongs to the field of optimization of drilling parameters, relates to data analysis technology, and is used to solve the problem that the prior art cannot optimize and analyze drilling parameters in combination with the results of dynamic stability analysis. Specifically, it is a multi-objective optimization method for drilling parameters based on dynamic stability constraints, including the following steps: setting drilling parameters before drilling construction; performing stability analysis during drilling construction: dividing the drilling construction process into several analysis periods, obtaining the drilling density data, ground pressure data, and Poisson data of the analysis periods and performing numerical calculations to obtain the stability coefficient of the analysis periods; The present invention can analyze the construction stability of the drilling construction process, evaluate the drilling construction stability state of the analysis period according to the stability coefficient, obtain the fluctuation coefficient after differentially marking the analysis period, and combine the drilling parameters of the drilling construction process to form evaluation data, providing data support for optimization analysis.

Description

Technical Field

[0001] The present invention belongs to the field of drilling parameter optimization, involves data analysis technology, and specifically is a multi-objective optimization method for drilling parameters based on dynamic stability constraints. Background Art

[0002] ‌Drilling stability‌ refers to the ability of the wellbore rock to remain intact and non-collapsing during the drilling process. It is affected by various factors, including geological conditions, drilling fluid properties, and drilling parameters, etc., and is crucial for the safety of oil and gas exploration and development; drilling stability refers to the ability of the wellbore rock to resist external forces and maintain its integrity and stability during the drilling process.

[0003] The invention patent with the publication number CN103177185B discloses a multi-objective optimization method and device for PDC bit drilling parameters. The multi-objective optimization model and genetic optimization algorithm established by this multi-objective optimization method can optimize drilling parameters according to the wishes of the decision maker and various specific constraint conditions, with great flexibility and wide practicability; however, this multi-objective optimization method cannot optimize and analyze drilling parameters by combining the results of dynamic stability analysis, nor can it indent the parameter optimization range by combining the set parameters corresponding to safety events, resulting in the inability to effectively control drilling stability.

[0004] In view of the above technical problems, the present application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide a multi-objective optimization method for drilling parameters based on dynamic stability constraints, which is used to solve the problem that the prior art cannot optimize and analyze drilling parameters by combining the results of dynamic stability analysis;

[0006] The technical problem to be solved by the present invention is: how to provide a multi-objective optimization method for drilling parameters based on dynamic stability constraints that can optimize and analyze drilling parameters by combining the results of dynamic stability analysis.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The multi-objective optimization of drilling parameters based on dynamic stability constraints includes the following steps:

[0009] Step 1: Set the drilling parameter CSi before drilling construction: retrieve the set range SZi corresponding to the drilling parameter CSi, and randomly select a value from the set range SZi to set the drilling parameter CSi;

[0010] Step 2: Conduct stability analysis during the drilling construction process: Divide the drilling construction process into several analysis periods, obtain the drilling density data ZM, formation pressure data DY, and Poisson's ratio data BS for each analysis period, and perform numerical calculations to obtain the stability coefficient WD for the analysis period.

[0011] Step 3: Evaluate and analyze the overall stability of the drilling construction process: Mark the analysis period as a stable period or a fluctuating period based on the stability coefficient WD. Mark the ratio of the number of fluctuating periods to the number of analysis periods during the drilling construction process as the fluctuation coefficient of the drilling construction process. The evaluation data of the drilling construction process is composed of the fluctuation coefficient and the set drilling parameters CSi.

[0012] Step 4: When the number of completed drilling construction processes reaches L1, conduct multi-objective optimization analysis on the drilling parameters of the drilling construction process and obtain the optimization range YHi of the drilling parameters CSi.

[0013] Step 5: Optimize and set the parameters of the drilling construction process according to the optimization range YHi.

[0014] Step 6: Conduct safety event optimization analysis on the optimized data set.

[0015] Furthermore, in Step 2, the process of obtaining the drilling density data ZM includes: Real-time obtain the drilling fluid density within the analysis period, retrieve the drilling fluid density range, mark the average value of the maximum and minimum values of the drilling fluid density range as the density standard value, mark the absolute value of the difference between the drilling fluid density and the density standard value as the density deviation value, and mark the maximum value of the density deviation value within the analysis period as the drilling density data ZM. The process of obtaining the formation pressure data DY includes: Real-time obtain the formation pressure within the analysis period, retrieve the formation pressure range, mark the average value of the maximum and minimum values of the formation pressure range as the formation pressure standard value, mark the absolute value of the difference between the formation pressure and the formation pressure standard value as the formation pressure deviation value, and mark the maximum value of the formation pressure deviation value within the analysis period as the formation pressure data DY. The Poisson's ratio data BS is the maximum value of the Poisson's ratio within the analysis period.

[0016] Furthermore, in Step 3, the specific process of marking the analysis period as a stable period or a fluctuating period includes: Compare the stability coefficient WD of the analysis period with the preset stability threshold WDmax. If the stability coefficient WD is less than the stability threshold WDmax, mark the corresponding analysis period as a stable period. If the stability coefficient WD is greater than or equal to the stability threshold WDmax, mark the corresponding analysis period as a fluctuating period.

[0017] Further, in step four, the process of obtaining the optimization range YHi of the drilling parameter CSi includes: retrieving the evaluation data of all drilling construction processes, arranging the drilling construction processes in ascending order of the fluctuation coefficient to obtain a stable sequence, intercepting the first L2 drilling construction processes in the stable sequence and marking them as the optimization target processes, retrieving the set values of the drilling parameter SCi of the optimization target processes, and forming the optimization range YHi of the drilling parameter CSi from the minimum and maximum values of the set values of the drilling parameter SCi corresponding to the optimization target processes; the optimization ranges YHi of all the drilling parameters SCi form an optimization data set.

[0018] Further, in step five, the specific process of parameter optimization setting for the drilling construction process includes: setting the drilling parameter CSi before the drilling construction, and the setting method is: retrieving the optimization range YHi corresponding to the drilling parameter CSi, and randomly selecting a value from the optimization range YHi for setting the drilling parameter CSi.

[0019] Further, in step six, the specific process of safety event optimization analysis for the optimization data set includes: when a safety event occurs, retrieving the value of the drilling parameter CSi set for the current drilling construction process and marking it as the event set value SDi, and determining whether the event set value SDi is within the optimization range YHi of the corresponding drilling parameter CSi: if not, no processing is performed; if so, an event influence range YXi is generated for the drilling parameter CSi; when setting the value of the drilling parameter CSi subsequently, if the value randomly selected from the optimization range YHi is within the event influence range YXi, the value selection of the drilling parameter CSi is performed again.

[0020] Further, the process of generating the event influence range YXi of the drilling parameter CSi includes: obtaining the event set high value SDid and the event set low value SDix through the formulas SDid = t1×SDi and SDix = t2×SDi, where t1 and t2 are both proportionality coefficients, and 0.95 ≤ t1 ≤ 0.98, 1.02 ≤ t2 ≤ 1.05; the event influence range YXi of the drilling parameter CSi is formed by the event set high value SDid and the event set low value SDix.

[0021] The present invention has the following beneficial effects:

[0022] Through stability analysis, the construction stability of the drilling construction process can be analyzed. Multiple stability parameters are collected in different time periods for comprehensive analysis and calculation to obtain a stability coefficient. According to the stability coefficient, the drilling construction stable state of the analysis period is evaluated. After differential marking of the analysis period, a fluctuation coefficient is obtained, and combined with the drilling parameters of the drilling construction process, evaluation data is formed, providing data support for optimization analysis;

[0023] Through the optimization analysis module, multi-objective optimization analysis can be carried out on the drilling parameters during the drilling construction process. After intercepting the stable sequence, an optimization range is formed according to the drilling parameters in the optimization target process, and then through the optimization setting process, the drilling parameters in the subsequent drilling construction process are set within the optimization range to improve the stability of the drilling construction;

[0024] Through the event optimization module, security event optimization analysis can be carried out on the optimization data set. Numerical processing is performed on the drilling parameters corresponding to the drilling construction process where a security event occurs to obtain the event influence range. Then, in combination with the optimization range and the event influence range, the drilling parameters are set, and the optimization range is further indented to reduce the probability of safety accidents. Brief Description of the Drawings

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0026] Figure 1 It is the flowchart of the method in Embodiment 1 of the present invention;

[0027] Figure 2 It is the system block diagram of Embodiment 2 of the present invention. Detailed Embodiments

[0028] The following will clearly and completely describe the technical solutions of the present invention in combination with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0029] Embodiment 1: As Figure 1 shown, a multi-objective optimization method for drilling parameters based on dynamic stability constraints includes the following steps:

[0030] Step 1: Before the drilling construction, set the drilling parameters CSi, where i = 1, 2,..., n, and n is a positive integer. The drilling parameters CSi include weight on bit, rotary speed, pump rate, pump pressure, and pump efficiency, etc.; The setting method is: retrieve the setting range SZi corresponding to the drilling parameter CSi, and randomly select a value from the setting range SZi to set the drilling parameter CSi;

[0031] Step 2: Conduct stability analysis during the drilling construction process: Divide the drilling construction process into several analysis periods, and obtain the drilling density data ZM, formation pressure data DY, and Poisson data BS for the analysis periods. The process of obtaining the drilling density data ZM includes: obtaining the drilling fluid density in real time during the analysis period, retrieving the range of the drilling fluid density, marking the average value of the maximum and minimum values of the drilling fluid density range as the density standard value, marking the absolute value of the difference between the drilling fluid density and the density standard value as the density deviation value, and marking the maximum value of the density deviation value during the analysis period as the drilling density data ZM. The process of obtaining the formation pressure data DY includes: obtaining the formation pressure in real time during the analysis period, retrieving the range of the formation pressure, marking the average value of the maximum and minimum values of the formation pressure range as the formation pressure standard value, marking the absolute value of the difference between the formation pressure and the formation pressure standard value as the formation pressure deviation value, and marking the maximum value of the formation pressure deviation value during the analysis period as the formation pressure data DY. The Poisson data BS is the maximum value of the Poisson's ratio during the analysis period. Obtain the stability coefficient WD for the analysis period through the formula WD = k1×ZM + k2×DY + k3×BS, where k1, k2, and k3 are all proportionality coefficients, and k1 > k2 > k3 > 1. Collect multiple stability parameters in sub-periods for comprehensive analysis and calculation to obtain the stability coefficient, evaluate the drilling construction stability state of the analysis period based on the stability coefficient, obtain the fluctuation coefficient after differentially marking the analysis period, and combine with the drilling parameters during the drilling construction process to form the evaluation data, providing data support for the optimization analysis;

[0032] Verify and analyze the evaluation results of the drilling construction stability state for the analysis period through the Jacobi matrix algorithm: The Jacobi matrix can be used to analyze the stability of the system. Specifically, by calculating the eigenvalues of the Jacobi matrix, the eigenvalue spectrum of the system can be obtained, thereby understanding the stability of the system. When the real parts of all eigenvalues are less than zero, the system is in a stable state; when there are eigenvalues with real parts greater than zero, the system is in an unstable state. When the verification result of the Jacobi matrix is inconsistent with the drilling construction stability detection result, re-collect the drilling density data ZM, formation pressure data DY, and Poisson data BS and calculate the stability coefficient WD;

[0033] In vector calculus, the Jacobi matrix is a matrix formed by arranging first-order partial derivatives in a certain way, and its determinant is called the Jacobi determinant. The importance of the Jacobi matrix lies in that it reflects the optimal linear approximation of a differentiable equation at a given point;

[0034] Step 3: Evaluate and analyze the overall stability of the drilling construction process: Compare the stability coefficient WD of the analysis period with the preset stability threshold WDmax. If the stability coefficient WD is less than the stability threshold WDmax, mark the corresponding analysis period as a stable period. If the stability coefficient WD is greater than or equal to the stability threshold WDmax, mark the corresponding analysis period as a fluctuating period, and mark the ratio of the number of fluctuating periods in the drilling construction process to the analysis quantity as the fluctuation coefficient of the drilling construction process. The evaluation data of the drilling construction process is composed of the fluctuation coefficient and the set drilling parameters CSi.

[0035] Step 4: When the number of completed drilling construction processes reaches L1 (L1 is a numerical constant, and the specific value of L1 is set by the management personnel themselves), conduct multi-objective optimization analysis on the drilling parameters of the drilling construction process: Retrieve the evaluation data of all drilling construction processes, arrange the drilling construction processes in ascending order of the fluctuation coefficient to obtain a stable sequence, intercept the first L2 drilling construction processes in the stable sequence and mark them as the optimization target processes (L2 is a numerical constant, and the specific value of L2 is set by the management personnel themselves, and L2 < L1). Retrieve the set values of the drilling parameters SCi of the optimization target processes, and the optimization range YHi of the drilling parameter SCi is formed by the minimum and maximum values of the set values of the drilling parameter SCi corresponding to the optimization target processes. The optimization data set is composed of the optimization ranges YHi of all drilling parameters SCi. After intercepting the stable sequence, form the optimization range according to the drilling parameters of the optimization target processes, and then set the drilling parameters of the subsequent drilling construction processes within the optimization range through the optimization setting process to improve the stability of the drilling construction.

[0036] Step 5: Optimize the setting of the parameters of the drilling construction process: Before the drilling construction, set the drilling parameter CSi. The setting method is as follows: Retrieve the corresponding optimization range YHi of the drilling parameter CSi, and randomly select a value from the optimization range YHi to set the drilling parameter CSi.

[0037] Step 6: Conduct safety event optimization analysis on the optimized dataset: When a safety event occurs, the safety events include drill string breakage, pipe sticking, severe well collapse, blowout, etc.; retrieve the value of the drilling parameter CSi set during the current drilling operation and mark it as the event setting value SDi, and determine whether the event setting value SDi is within the optimization range YHi of the corresponding drilling parameter CSi: If not, no processing is performed; if so, obtain the event setting high value SDid and the event setting low value SDix through the formulas SDid = t1×SDi and SDix = t2×SDi, where t1 and t2 are both proportionality coefficients, and 0.95 ≤ t1 ≤ 0.98, 1.02 ≤ t2 ≤ 1.05; the event influence range YXi of the drilling parameter CSi is formed by the event setting high value SDid and the event setting low value SDix; when setting the value of the drilling parameter CSi subsequently, if the value randomly selected from the optimization range YHi is within the event influence range YXi, re-select the value of the drilling parameter CSi; perform numerical processing on the drilling parameters corresponding to the drilling operation where a safety event occurs to obtain the event influence range, and then combine the optimization range and the event influence range to set the drilling parameters, and further indent the optimization range to reduce the occurrence probability of safety accidents.

[0038] Embodiment 2: As Figure 2 shown, the multi-objective optimization system for drilling parameters based on dynamic stability constraints includes a parameter setting module, a stability analysis module, an evaluation analysis module, an optimization analysis module, an optimization setting module, and an event optimization module;

[0039] The parameter setting module is used to set the drilling parameter CSi before the drilling operation;

[0040] The stability analysis module is used to conduct stability analysis during the drilling operation and obtain the stability coefficient WD of the drilling operation;

[0041] The evaluation analysis module is used to evaluate and analyze the overall stability of the drilling operation and obtain the fluctuation coefficient of the drilling operation;

[0042] The optimization analysis module is used to conduct multi-objective optimization analysis on the drilling parameters of the drilling operation according to the evaluation data of the drilling operation;

[0043] The optimization setting module is used to perform parameter optimization setting on the drilling operation through the optimization range YHi;

[0044] The event optimization module is used to conduct safety event optimization analysis on the optimized dataset and obtain the event influence range YXi, and indent the selectable interval of the optimization range YHi through the event influence range YXi.

[0045] Multi-objective optimization method for drilling parameters based on dynamic stability constraints. During operation, before drilling construction, the drilling parameter CSi is set. A value is randomly selected from the setting range SZi for setting the drilling parameter CSi. The drilling construction process is divided into several analysis periods. The drilling density data ZM, ground pressure data DY, and Poisson data BS of the analysis period are obtained and numerical calculations are performed to obtain the stability coefficient WD. The analysis period is marked as a stable period or a fluctuation period through the stability coefficient WD. The ratio of the number of fluctuation periods in the drilling construction process to the analysis quantity is marked as the fluctuation coefficient of the drilling construction process. The drilling construction processes are arranged in ascending order of the fluctuation coefficient to obtain a stable sequence. The first L2 drilling construction processes in the stable sequence are intercepted and marked as the optimization target processes. The optimization range YHi is generated according to the set values of the drilling parameter CSi of the optimization target processes. When a safety event occurs, the corresponding event influence range YXi is obtained. The set value of the drilling parameter CSi is selected by combining the optimization range YHi and the event influence range YXi.

[0046] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should fall within the protection scope of the present invention.

[0047] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formula are set by those skilled in the art according to the actual situation. For example: the formula WD = k1×ZM + k2×DY + k3×BS; those skilled in the art collect multiple groups of sample data and set the corresponding stability coefficient for each group of sample data; substitute the set stability coefficient and the collected sample data into the formula, and any three formulas form a system of linear equations with three variables. The calculated coefficients are screened and the average value is taken to obtain the values of k1, k2, and k3 as 3.52, 2.63, and 2.12 respectively;

[0048] The magnitude of the coefficient is a specific value obtained by quantifying each parameter, which is convenient for subsequent comparison. Regarding the magnitude of the coefficient, it depends on the number of sample data and the initial setting of the corresponding stability coefficient for each group of sample data by those skilled in the art; as long as it does not affect the proportional relationship between the parameter and the quantified value, for example, the stability coefficient is proportional to the value of the drilling density data.

[0049] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0050] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific implementation manners. Obviously, according to the content of this specification, many modifications and changes can be made. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A multi-objective optimization method for drilling parameters based on dynamic stability constraints, characterized in that: The following steps are involved: Step 1: Setting the drilling parameter CSi before drilling construction: Retrieving the setting range SZi corresponding to the drilling parameter CSi, and randomly selecting a value from the setting range SZi to set the drilling parameter CSi; Step 2: Perform stability analysis during the drilling process: divide the drilling process into several analysis periods, obtain the drilling density data ZM, ground pressure data DY and Poisson data BS during the analysis period, and perform numerical calculations to obtain the stability coefficient WD during the analysis period; Step 3: Evaluate and analyze the overall stability of the drilling construction process: mark the analysis period as a stable period or a fluctuation period through the stability coefficient WD, mark the ratio of the number of fluctuation periods in the drilling construction process to the number of analysis periods as the fluctuation coefficient of the drilling construction process, and the fluctuation coefficient and the set drilling parameters CSi constitute the evaluation data of the drilling construction process; Step 4: When the number of completed drilling construction processes reaches L1, a multi-objective optimization analysis is performed on the drilling parameters of the drilling construction process and an optimization range YHi of the drilling parameters CSi is obtained; Step 5: Optimize the parameters of the drilling construction process according to the optimization range YHi; Step 6: Perform security event optimization analysis on the optimized data set; In step six, the specific process of performing security event optimization analysis on the optimized data set includes: when a security event occurs, the value of the drilling parameter CSi set in the current drilling construction process is retrieved and marked as the event setting value SDi, and it is determined whether the event setting value SDi is within the optimization range YHi of the corresponding drilling parameter CSi: if not, no processing is performed; if so, an event influence range YXi is generated for the drilling parameter CSi; when the value of the drilling parameter CSi is subsequently set, if the value randomly selected from the optimization range YHi is within the event influence range YXi, the value of the drilling parameter CSi is reselected; The generation process of the event influence range YXi of the drilling parameter CSi includes: the event setting high value SDid and the event setting low value SDix are obtained by the formulas SDid=t1×SDi and SDix=t2×SDi, wherein t1 and t2 are both proportional coefficients, and 0.95≤t1≤0.98, 1.02≤t2≤1.05; the event setting high value SDid and the event setting low value SDix constitute the event influence range YXi of the drilling parameter CSi.

2. The multi-objective optimization method for drilling parameters based on dynamic stability constraints according to claim 1 is characterized in that: In step 2, the process of obtaining the drilling density data ZM includes: obtaining the drilling fluid density in real time during the analysis period, retrieving the drilling fluid density range, marking the average value of the maximum and minimum values ​​of the drilling fluid density range as the density standard value, marking the absolute value of the difference between the drilling fluid density and the density standard value as the density deviation value, and marking the maximum value of the density deviation value during the analysis period as the drilling density data ZM; the process of obtaining the ground pressure data DY includes: obtaining the formation pressure in real time during the analysis period, retrieving the formation pressure range, marking the average value of the maximum and minimum values ​​of the formation pressure range as the ground pressure standard value, marking the absolute value of the difference between the formation pressure and the ground pressure standard value as the ground pressure deviation value, and marking the maximum value of the ground pressure deviation value during the analysis period as the ground pressure data DY; the Poisson data BS is the maximum value of the Poisson's ratio during the analysis period.

3. The multi-objective optimization method for drilling parameters based on dynamic stability constraints according to claim 2 is characterized in that: In step three, the specific process of marking the analysis period as a stable period or a fluctuating period includes: comparing the stability coefficient WD of the analysis period with the preset stability threshold WDmax: if the stability coefficient WD is less than the stability threshold WDmax, the corresponding analysis period is marked as a stable period; if the stability coefficient WD is greater than or equal to the stability threshold WDmax, the corresponding analysis period is marked as a fluctuating period.

4. The multi-objective optimization method for drilling parameters based on dynamic stability constraints according to claim 3 is characterized in that: In step 4, the process of obtaining the optimization range YHi of the drilling parameter CSi includes: retrieving the evaluation data of all drilling construction processes, arranging the drilling construction processes in order of fluctuation coefficient from small to large to obtain a stable sequence, intercepting the first L2 drilling construction processes in the stable sequence and marking them as optimization target processes, retrieving the drilling parameter SCi setting value of the optimization target process, and the minimum and maximum values ​​of the drilling parameter SCi setting values ​​corresponding to the optimization target process constitute the optimization range YHi of the drilling parameter SCi; the optimization range YHi of all drilling parameters SCi constitutes an optimization data set.

5. The multi-objective optimization method for drilling parameters based on dynamic stability constraints according to claim 4 is characterized in that: In step five, the specific process of optimizing the parameters of the drilling construction process includes: setting the drilling parameter CSi before the drilling construction, the setting method is: calling the optimization range YHi corresponding to the drilling parameter CSi, and randomly selecting a value from the optimization range YHi to set the drilling parameter CSi.

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