A method and system for optimizing drilling tripping speed threshold

Abstract

The present invention discloses a method and system for optimizing the drilling tripping speed threshold value, the method comprising: matching similar adjacent wells similar to the target well from all adjacent wells in the block where the target well is located; acquiring and analyzing the adjacent well data of the matched similar adjacent wells, and determining the tripping speed values ​​of each similar adjacent well in each layer when there is no risk; selecting the highest tripping speed value among the similar adjacent wells layer by layer from the determined tripping speed values ​​according to the stratigraphic stratification of the target well, and forming an optimization scheme for the tripping speed threshold value of the target well; in the process of performing tripping on the target well, analyzing in real time whether the tripping speed threshold value recommended by the optimization scheme will generate drilling risks, and dynamically updating and optimizing the tripping speed threshold value according to the analysis situation. The present invention realizes high-speed tripping under the premise of safe operation, reduces the tripping operation time, improves the drilling operation efficiency and reduces the cost.

Description

Technical Field

[0001] The invention belongs to the field of petroleum engineering, and in particular, relates to a method for optimizing an upper threshold value of a tripping speed of a target well by using historical data of drilling of adjacent wells in a block during the drilling process. Background Art

[0002] With the progress of oil and gas exploration and development, the geological conditions faced by drilling projects are becoming increasingly complex. Under complex geological conditions, low drilling efficiency, frequent complex situations and high drilling costs have seriously affected the efficiency of oil and gas exploration and development. Speeding up and improving efficiency have become important breakthroughs in reducing costs and increasing efficiency in drilling projects. The total drilling operation time includes production time and non-production time, of which production time includes footage work time, logging work time, cementing work time and auxiliary work time. Footage work time includes pure drilling work time, tripping work time, single-root connection work time, eye expansion work time, drill bit replacement work time, and drilling fluid circulation work time; non-production time includes accident handling work time, equipment repair work time, organization downtime, natural downtime, complex situation handling time and other time. The goal of drilling speed and efficiency improvement is to increase the mechanical drilling speed to achieve speed-up on the one hand, and to reduce production time and non-production time as much as possible to achieve efficiency improvement on the other hand.

[0003] The time spent on drilling and drilling operations is mainly affected by the drilling speed. In order to reduce the drilling time in the process of improving drilling efficiency, the drilling speed should be increased as much as possible under the premise of ensuring drilling safety to reach the upper limit of the critical threshold. At present, the upper limit of the drilling speed threshold at the drilling site is based on the specified value in the driller's operation standard. Although the drilling speed threshold specified in the standard is conservative in most cases, it may still cause the well pressure fluctuation to cause well kicks and leakage in some complex formations that are prone to leakage or well flow. On the other hand, in relatively stable formations or casing sections, the conservative drilling speed threshold specified in the standard limits the improvement of drilling and drilling operation efficiency. In the theoretical model calculation method, the existing model can only calculate the pressure fluctuation in the well according to the drilling speed, but cannot calculate and recommend the optimal drilling speed.

[0004] The methods, devices and systems provided in the prior art all have similar problems, and there is no method or system for optimizing the drilling speed threshold. Summary of the invention

[0005] One of the technical problems to be solved by the present invention is the need to provide a method and system that can optimize and recommend the drilling speed threshold, achieve high-speed drilling under the premise of safe operation, reduce the drilling operation time, improve the drilling operation efficiency and reduce the cost.

[0006] In order to solve the above technical problems, an embodiment of the present application first provides a method for optimizing the drilling start-up and downhole speed threshold, the method comprising: step one, matching similar neighboring wells similar to the target well from all neighboring wells in the block where the target well is located; step two, acquiring and analyzing the neighboring well data of the matched similar neighboring wells, and determining the start-up and downhole speed values ​​of each similar neighboring well in each layer when there is no risk; step three, according to the stratigraphic stratification of the target well, selecting the highest start-up and downhole speed value among the similar neighboring wells layer by layer from the determined start-up and downhole speed values, to form an optimization scheme for the start-up and downhole speed threshold of the target well; step four, in the process of executing start-up and downhole on the target well, analyzing in real time whether the start-up and downhole speed threshold recommended by the optimization scheme will generate drilling risks, and dynamically updating and optimizing the start-up and downhole speed threshold according to the analysis results.

[0007] According to an embodiment of the present invention, in step one, based on the data to be matched of all neighboring wells and the target well, a matching algorithm for matching similar neighboring wells is used to calculate and determine similar neighboring wells that match the target well, and the data to be matched includes at least the following: wellbore structure data, wellbore trajectory data, drilling tool assembly data, and formation stratification data.

[0008] According to an embodiment of the present invention, the adjacent well data at least includes real-time logging data, formation stratification data, and drilling risk data; further in the step two, an algorithm for identifying drilling conditions is used to analyze the logging data of similar adjacent wells, and the drilling conditions of similar adjacent wells are determined. Based on the identified drilling conditions, the drilling speed values ​​of similar adjacent wells are calculated in combination with the formation stratification data, and in combination with the risk data, the drilling speed values ​​of each similar adjacent well in each layer when there is no risk are screened out.

[0009] According to an embodiment of the present invention, in step four, the bottom hole pressure fluctuation value during drilling is calculated in real time, and whether the drilling speed threshold of the target well in the current layer needs to be updated is analyzed based on the calculated bottom hole pressure fluctuation value during drilling or in combination with the real-time logging data trend of the target well.

[0010] According to an embodiment of the present invention, it further includes: judging whether the bottom hole pressure fluctuation value calculated in real time during drilling exceeds the fluctuation threshold, if so, updating the drilling speed threshold of the target well in the current layer to the suboptimal value among the drilling speeds of similar adjacent wells; otherwise, analyzing whether drilling risks will occur based on the real-time logging data trend of the target well, if so, updating the drilling speed threshold of the target well in the current layer to the suboptimal value among the drilling speeds of similar adjacent wells.

[0011] According to another aspect of the present invention, a system for optimizing a drilling start-up and downhole speed threshold is provided, the system comprising: a similar adjacent well matching module, which is used to match similar adjacent wells similar to the target well from all adjacent wells in the block where the target well is located; a similar adjacent well start-up and downhole speed determination module, which is used to obtain and analyze the adjacent well data of the matched similar adjacent wells, and determine the start-up and downhole speed values ​​of each similar adjacent well in each layer when there is no risk; an optimization scheme generation module, which is used to select the highest start-up and downhole speed value among the similar adjacent wells layer by layer from the determined start-up and downhole speed values ​​according to the stratigraphic stratification of the target well, and form an optimization scheme for the start-up and downhole speed threshold of the target well; an optimization scheme analysis and update module, which is used to analyze in real time whether the start-up and downhole speed threshold recommended by the optimization scheme will generate drilling risks during the process of executing the start-up and downhole of the target well, and dynamically update and optimize the start-up and downhole speed threshold according to the analysis results.

[0012] According to an embodiment of the present invention, the similar adjacent well matching module calculates and determines the similar adjacent wells that match the target well based on the data to be matched of all adjacent wells and the target well, and the data to be matched includes at least the following: wellbore structure data, wellbore trajectory data, drilling tool assembly data, and formation stratification data.

[0013] According to an embodiment of the present invention, the similar adjacent well drilling speed determination module further includes: a drilling condition identification submodule, which uses an algorithm for drilling condition identification to analyze the logging data of similar adjacent wells to determine the drilling conditions of similar adjacent wells; a similar adjacent well drilling speed calculation submodule, which calculates the drilling speed values ​​of similar adjacent wells based on the identified drilling conditions and in combination with the formation stratification data, and screens out the drilling speed values ​​of each similar adjacent well in each layer when there is no risk in combination with the risk data.

[0014] According to an embodiment of the present invention, the optimization scheme analysis and update module is used to calculate the bottom hole pressure fluctuation value during drilling in real time, and analyze whether it is necessary to update the drilling speed threshold of the target well in the current layer based on the calculated bottom hole pressure fluctuation value during drilling or in combination with the real-time logging data trend of the target well.

[0015] According to an embodiment of the present invention, the optimization scheme analysis and updating module further determines whether the bottom hole pressure fluctuation value calculated in real time during drilling exceeds the fluctuation threshold. If so, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells. Otherwise, based on the real-time logging data trend of the target well, it is analyzed whether there will be drilling risks. If so, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells.

[0016] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0017] The embodiment of the present invention utilizes the real-time logging, formation stratification and risk case data of neighboring wells in the block, matches similar neighboring wells and calculates their tripping speeds at each formation level, selects the highest tripping speed of each formation when there is no operation risk as the upper limit of the tripping speed threshold of the target well, then monitors the abnormal conditions of the parameters of the target well, and updates and optimizes the tripping speed threshold. This method has the following advantages:

[0018] (1) Compared with the speed threshold specified in the driller's operating procedures at the drilling site, the embodiment of the present invention makes full use of the historical data of adjacent wells, and on the premise of ensuring drilling safety, forms an optimized threshold value to recommend to the driller, fully optimizes and improves the drilling tripping speed, thereby achieving the purpose of speeding up and improving the efficiency of drilling tripping operations.

[0019] (2) Compared with the current method in which the on-site driller controls the drilling speed based on his own experience, the embodiment of the present invention makes full use of the historical data of adjacent wells to explore the data patterns of drilling in the block, which can avoid the risk of exceeding the drilling speed limit due to the driller's lack of experience in the target block or being conservative and reducing work efficiency.

[0020] 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 implementing the technical solution of the present invention. The purpose and other advantages of the present invention can be achieved and obtained by the structures and / or processes specifically pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the technical solution of the present application or the prior art, and constitute a part of the specification. Among them, the accompanying drawings expressing the embodiments of the present application are used together with the embodiments of the present application to explain the technical solution of the present application, but do not constitute a limitation on the technical solution of the present application.

[0022] Figure 1 A schematic flow chart of a method for optimizing a drilling tripping speed threshold according to an embodiment of the present application.

[0023] Figure 2 A schematic diagram of a specific flow chart of a method for optimizing a drilling tripping speed threshold according to an embodiment of the present application.

[0024] Figure 3 A system block diagram for optimizing the drilling tripping speed threshold according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] 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 corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present application and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the protection scope of the present invention.

[0026] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a sequence different from that here.

[0027] Increasing drilling speed and efficiency has always been the core issue of drilling engineering. As oil and gas exploration and development move towards deep complex oil and gas reservoirs and unconventional reservoirs, there is an urgent need for simple, reliable, economical and adaptable tools and equipment and technical methods. However, so far, the development of drilling equipment, equipment and tools has entered a bottleneck period, and it is difficult to achieve a major breakthrough in the short term to achieve an increase in drilling speed and efficiency. With the development of big data technology, the optimization method of the drilling speed threshold based on massive historical data can provide significant help for improving drilling efficiency. The present invention mines the historical data of neighboring wells in the block, and proposes a method for optimizing the drilling speed threshold of the target well using the historical data of drilling of neighboring wells in the block during the drilling process. The method optimizes and recommends the drilling speed threshold of the target well, realizes high-speed drilling under the premise of safe operation, reduces the drilling operation time, improves the drilling operation efficiency and reduces the cost.

[0028] The basic principle of the present invention is first explained below. The basic principle is as follows: based on the massive adjacent well data in the block where the target well is located, a similar adjacent well matching algorithm is applied to match adjacent wells similar to the target well, and real-time logging data of similar adjacent wells are extracted. The logging data of similar adjacent wells are analyzed by a working condition recognition model to determine the drilling conditions (drilling and drilling conditions) of similar adjacent wells. The drilling speed values ​​of similar adjacent wells in each formation are calculated in combination with the formation stratification data, and the adjacent well risk record data are combined for screening, and the drilling speed values ​​of each adjacent well in each layer when there is no risk are screened and saved; according to the formation stratification of the target well, the highest drilling speed value among similar adjacent wells is selected layer by layer to form an optimization scheme for the drilling speed threshold of the target well; then, during the drilling process of the target well, the method of fluctuating pressure calculation and logging curve trend analysis is applied to monitor the drilling risk of the target well in real time, that is, the fluctuating pressure calculation model and logging data trend calculation are applied to analyze whether the recommended threshold will generate drilling risk, and the drilling threshold is dynamically updated and optimized according to the analysis. This method can flexibly and reliably guide drillers to adjust the drilling speed according to the actual situation of the block, thereby maximizing drilling efficiency while ensuring safety.

[0029] Figure 1 This is a schematic flow chart of a method for optimizing a drilling tripping speed threshold value (or a method for optimizing a drilling tripping speed threshold value based on adjacent well data) provided by an embodiment of the present invention. Figure 1 To illustrate the various steps to implement this method.

[0030] like Figure 1 As shown, in step S110, similar adjacent wells similar to the target well are matched from all adjacent wells in the block where the target well is located.

[0031] Specifically, based on the data to be matched of all neighboring wells and the target well, a matching algorithm for matching similar neighboring wells is used to calculate and determine similar neighboring wells that match the target well, wherein the data to be matched include but are not limited to the following data: wellbore structure data, borehole trajectory data, drilling tool assembly data, and stratigraphic data. The above matching algorithm can select conventional algorithms in the prior art, such as existing algorithms such as Euclidean distance, Pearson correlation coefficient, and cosine similarity. This application does not limit this. By calculating the similarity of the wellbore structure data, borehole trajectory data, drilling tool assembly data, and stratigraphic data of the neighboring wells to be matched and the target well, similar neighboring wells that reach a certain similarity are classified to obtain similar neighboring well groups, thereby determining similar neighboring wells of the target well. Specifically, in a preferred example, when using the Euclidean distance calculation method, the similarity of two wells is measured by distance. The larger the distance, the smaller the similarity; the smaller the distance, the greater the similarity. In particular, for the text data such as well type (vertical well, inclined well, horizontal well), stratigraphic stratification (Kuqa Formation, Kangcun Formation, Jidike Formation, Basige Formation, etc.) in the adjacent well data, petroleum engineering experts first determine it as a numerical value based on its professional similarity, such as 1 for vertical well, 1.5 for inclined well, and 2 for horizontal well; and stratigraphic stratification is represented by integers 1-20 based on its lithology, so that all the data to be matched are converted into numerical values, and then the Euclidean distance between the data is calculated for similar matching. It is easy to understand that when using different matching algorithms, in addition to the wellbore structure, wellbore trajectory, drilling tool assembly, and stratigraphic stratification mentioned above, other data types that meet the matching algorithm can also be added according to the data items involved in the similar adjacent well matching algorithm.

[0032] In step S120, the adjacent well data of the matched similar adjacent wells are acquired and analyzed to determine the tripping speed values ​​of each similar adjacent well at each layer when there is no risk.

[0033] Specifically, the drilling condition recognition algorithm is used to analyze the logging data of similar adjacent wells, determine the tripping conditions of similar adjacent wells, calculate the tripping speed values ​​of similar adjacent wells based on the identified tripping conditions and combined with the formation layering data, and screen out the tripping speed values ​​of each adjacent well in each layer when there is no risk in combination with the risk data. The above-mentioned application condition recognition algorithm can select existing methods according to needs. The working conditions in normal drilling operations mainly include drilling down (connecting the drill pipe and lowering the drill bit), reaming (encountering irregular well sections during the drilling process, turning on the pump to rotate the drill bit), drilling (pressurizing and rotating the drill bit after lowering it to the bottom of the well and circulating the drilling fluid to drill into the formation), pulling out (removing the drill pipe and lifting the drill bit), and reverse reaming (encountering irregular well sections during the pulling out process, turning on the pump to rotate the drill bit). The methods based on support vector machines and Bayesian networks in existing papers all use the changing rules of data items such as drill bit position, hook load, and drilling pressure in real-time logging data to identify the drilling working conditions at the current time point in real-time logging data, and their recognition accuracy can basically reach more than 95%. According to the logging data items required by the working condition identification model, the historical records of the logging data of adjacent wells are imported into the working condition identification model to complete the identification of the working condition of each logging data. Drilling and drilling is a stable and continuous process. After the drilling or drilling condition is identified, the drill bit position in the logging data is compared with the well depth interval of the formation layer, and the first and last logging data of entering and leaving the formation are extracted. The time item in the logging data is extracted, and the difference is calculated to obtain the time for drilling or drilling in the layer. The drilling or drilling speed in the layer can be calculated by dividing the formation thickness by the time.

[0034] In step S130, according to the formation stratification of the target well, the highest tripping speed value in similar adjacent wells is selected layer by layer from the determined tripping speed values ​​to form an optimization scheme for the tripping speed threshold of the target well.

[0035] Specifically, from the risk-free tripping speed values ​​screened based on the risk record data of adjacent wells, according to the formation division of the target well, the highest tripping speeds of adjacent wells in each formation are selected and used as the tripping speed thresholds of each formation of the target well to form the tripping speed optimization plan for the target well. When performing the tripping operation according to the optimization plan, it is necessary to monitor the tripping risk of the target well in real time.

[0036] In step S140, during the tripping of the target well, a real-time analysis is performed to determine whether the tripping speed threshold recommended by the optimization scheme will generate drilling risks, and the tripping speed threshold is dynamically updated and optimized based on the analysis results.

[0037] Specifically, the bottom hole pressure fluctuation value during drilling is calculated in real time, and whether the drilling speed threshold of the target well in the current layer needs to be updated is analyzed based on the calculated bottom hole pressure fluctuation value during drilling or combined with the real-time logging data trend of the target well. More specifically, it is determined whether the bottom hole pressure fluctuation value during drilling calculated in real time exceeds the fluctuation threshold. If it exceeds, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells; otherwise, based on the real-time logging data trend of the target well, it is analyzed whether there will be drilling risks. If there are, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells. The suboptimal value is the second highest value selected when the highest value is at risk. If the second highest value is still at risk, a value lower than the "second highest value" is selected, and so on.

[0038] Figure 2 This is a schematic diagram of a specific process of the method for optimizing the drilling tripping speed threshold of the embodiment of the present application. Figure 2 The specific implementation process is explained by taking the application in Well X in a certain area of ​​Shengli Oilfield as an example.

[0039] (1) Collect data of all neighboring wells in the block where the target well is located and the data of the target well to build a database, wherein the data of the neighboring wells include but are not limited to real-time logging data, stratigraphic data, drilling risk data, etc.

[0040] For the target well X, data from 215 historical wells in the block of Shengli Oilfield and the target well X were collected and entered into the database. These data included real-time logging data, geological data, drilling design, completion report, drilling risk and treatment plan data of the 215 historical wells, as well as geological data and drilling design of the target well X.

[0041] After the database is built, the following process is used to optimize the drilling tripping speed threshold for the target well X in the block.

[0042] (2) Based on the data items involved in the similar adjacent well matching algorithm, all the adjacent wells and the target well data to be matched are extracted from the database. The data to be matched include but are not limited to the wellbore structure, wellbore trajectory, drilling tool assembly, formation stratification, etc.

[0043] (3) applying a similar adjacent well matching algorithm to determine multiple adjacent wells that have a certain degree of similarity with the target well after calculation, wherein the similar adjacent well matching algorithm may be selected from existing methods in other patent documents according to needs, and the present invention is not limited thereto, such as existing algorithms such as Euclidean distance, Pearson correlation coefficient, and cosine similarity;

[0044] (4) Based on the similar adjacent wells determined in step (3), extracting their historical logging data from the database, applying a working condition recognition algorithm, identifying the tripping and drilling working conditions therein and saving the logging data of the tripping and drilling working conditions, wherein the working condition recognition algorithm may be selected from existing methods in other patent documents according to needs, and the present invention is not limited thereto, such as support vector machine, Bayesian network and other methods;

[0045] (5) Based on the similar adjacent wells determined in step (3), the stratigraphic data thereof are extracted from the database, including but not limited to the stratigraphic formation name, depth range, lithologic composition, etc., and the tripping speeds of the similar adjacent wells in each formation are calculated and saved in combination with the tripping conditions screened and determined in step (4). Because there are multiple trippings in the drilling operation, each adjacent well has multiple tripping speed values ​​in each formation according to the driller's operation conditions;

[0046] (6) Based on the similar adjacent wells determined in step (3), extract the drilling risk data thereof from the database, including but not limited to the risk category, the occurrence well depth, the occurrence formation, etc., and combine the tripping speeds of each formation calculated and saved in step (5), filter out the tripping speed value corresponding to the occurrence of the risk from the multiple tripping speeds at the risk formation, and save the depth and tripping speed values ​​of each formation layer of similar adjacent wells;

[0047] (7) extracting stratigraphic data of the target well from the database, including but not limited to stratigraphic system name, depth range, lithology, etc., and selecting the highest drilling speed as the threshold for each stratigraphic layer from the drilling speed values ​​of similar adjacent wells saved in step (6) according to the stratigraphic conditions of the target well;

[0048] (8) Based on the target well's various formation tripping speed thresholds selected in step (7), a target well tripping speed optimization plan is formed and pushed to the driller for reference and execution;

[0049] (9) Based on the optimization scheme for the tripping speed formed in step (8), combined with relevant real-time data of the target well, including but not limited to real-time logging data, drill bit assembly data, drilling fluid properties, etc., a fluctuation pressure calculation model is used to calculate the bottom hole pressure fluctuation value during the tripping in real time, and analyze whether it exceeds the fluctuation threshold, wherein the fluctuation pressure calculation model can select a method already available in patent literature, which is not limited in the present invention, for example, a method for calculating the steady-state fluctuation pressure of the wellbore;

[0050] (10) Based on step (9), if the fluctuation pressure exceeds the limit, the threshold of the drilling speed of the target well at the layer is updated to the suboptimal value of the drilling speed of the adjacent well in step (6); if the fluctuation pressure is within the normal range, proceed to the next step;

[0051] (11) Based on step (10), during the execution of the optimization scheme for the tripping speed threshold, the logging data trend of the target well is analyzed in real time to predict and identify drilling risks and analyze whether drilling risks will occur. The drilling risk trend analysis method may be a method already known in the patent literature, which is not limited in the present invention. For example, a method of calculating the rate of change of a specific logging parameter within two consecutive time intervals may be used.

[0052] (12) If there is a trend of drilling risk during the analysis of the drilling speed optimization threshold, the drilling speed threshold of the target well at this layer is updated to the suboptimal value of the drilling speed of the adjacent well in step (6); if there is no trend of drilling risk, the optimized threshold solution is continued to be executed.

[0053] The X well drilling team carried out drilling operations according to the recommended tripping speed optimization scheme obtained by the method of the present invention, recorded real-time logging data and identified the tripping conditions, and finally accumulated and calculated the tripping time of the well, and compared the results with the statistical results of the tripping time of 215 historical wells in the block.

[0054] The final result comparison shows that the time taken for the whole well tripping of Well X is lower than that of 215 neighboring wells in the block, which is 1.2 days shorter than the well with the fastest tripping operation in history, and the speed is increased by about 8%. It is 1.8 days shorter than the average tripping time of historical wells in the block, and the speed is increased by about 14%. This proves that the method for optimizing and recommending the threshold value of tripping speed of drilling proposed in the embodiment of the present invention is reliable and effective.

[0055] On the other hand, the embodiment of the present application also proposes a system for optimizing the drilling tripping speed threshold. Figure 3 To explain in detail the composition of the system and the functions of each component.

[0056] like Figure 3 As shown, the system includes a database 30, a similar adjacent well matching module 31, a tripping condition identification module 32, a similar adjacent well tripping speed calculation module 33, an optimization scheme generation module 34, an optimization scheme analysis and update module 35, and an optimization scheme recommendation module 36, wherein the tripping condition identification module 32 and the similar adjacent well tripping speed calculation module 33 constitute a similar adjacent well tripping speed determination module. The functions of these modules are described below.

[0057] Database 30 is used to store drilling data of neighboring wells and target wells in the block, including but not limited to real-time logging data, geological data, drilling design, completion report, drilling risk and treatment plan data of neighboring wells in the block, as well as geological data, drilling design and other contents of target wells.

[0058] The similar adjacent well matching module 31 is used to match similar adjacent wells similar to the target well from all adjacent wells in the block where the target well is located. The module 31 first extracts relevant data items from the database 30, and then applies the similar adjacent well matching algorithm to determine the adjacent wells used for reference in the target well optimization process through calculation and screening. Specifically, based on the data to be matched between all adjacent wells and the target well, the module 31 uses the matching algorithm for matching similar adjacent wells to calculate and determine the similar adjacent wells that match the target well. The data to be matched extracted from the database 30 at least includes the following: wellbore structure data, wellbore trajectory data, drilling tool assembly data, and formation stratification data.

[0059] The similar adjacent well drilling speed determination module is used to obtain and analyze the adjacent well data of the matched similar adjacent wells, and determine the drilling speed values ​​of each similar adjacent well in each layer when there is no risk. Among them, the drilling condition identification module 32 is used to extract the real-time logging data of the selected well in the similar adjacent well matching module 31, and identify the drilling condition therein based on the drilling condition identification algorithm; the similar adjacent well drilling speed calculation module 33 is used to further analyze the identified drilling condition, and filter and calculate its drilling speed in combination with the adjacent well formation stratification data and risk data. Specifically, based on the identified drilling condition, the drilling speed values ​​of similar adjacent wells are calculated in combination with the formation stratification data, and in combination with the risk data, the drilling speed values ​​of each similar adjacent well in each layer when there is no risk are filtered out.

[0060] The optimization scheme generating module 34 is used to select the highest tripping speed value in similar adjacent wells layer by layer from the determined tripping speed values ​​according to the formation stratification of the target well, so as to form an optimization scheme for the tripping speed threshold of the target well.

[0061] The optimization scheme analysis and updating module 35 applies the fluctuation pressure calculation analysis and the logging curve analysis to perform real-time analysis on the generated preliminary optimization of the drilling speed and to update and optimize the unreasonable threshold value selected as the standard for the highest drilling speed. Specifically, the module 35 is used to calculate the bottom hole pressure fluctuation value during drilling in real time, and analyze whether it is necessary to update the drilling speed threshold of the target well in the current layer according to the calculated bottom hole pressure fluctuation value during drilling or in combination with the real-time logging data trend of the target well. It is further determined whether the bottom hole pressure fluctuation value calculated in real time during drilling exceeds the fluctuation threshold. If it exceeds, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells; otherwise, based on the real-time logging data trend of the target well, it is analyzed whether there will be drilling risks. If there are, the drilling speed threshold of the target well in the current layer is updated to the suboptimal value among the drilling speeds of similar adjacent wells.

[0062] The optimization scheme recommendation module 36 pushes and displays the final optimization scheme of the tripping speed threshold of the target well to the on-site driller and engineer and other personnel for reference and execution during the drilling process. The recommendation result may be as shown in the example in Table 1 below.

[0063] Table 1 Recommended solutions for optimizing drilling tripping speed thresholds

[0064]

[0065] In summary, by mining the historical data of neighboring wells in the block, based on the formation division and the comparison and analysis of the drilling speed, the highest drilling speed of the neighboring wells under risk-free conditions is extracted to form a preliminary optimization plan, and the optimization plan is further updated by applying the fluctuation pressure calculation and real-time analysis of the logging curve. Finally, the drilling speed threshold of the target well is optimized and recommended, and the speed and efficiency are improved under the premise of safe operation. This method and system can use historical well data to help the drilling site personnel who enter the block for the first time to flexibly optimize the drilling speed, avoid the risk of well leakage and well kick in complex formations caused by the threshold speed in the standard requirements, and achieve drilling speed and efficiency. This technical solution is applied in the field of petroleum engineering, which can help the drilling site personnel fully explore the value of the drilling data of neighboring wells in the block, quickly form an optimization plan for the drilling speed of the target well, reduce the time of drilling, improve the efficiency of exploration drilling and reduce costs.

[0066] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0067] Although the embodiments disclosed in the present invention are as above, the above contents 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 optimizing a drilling tripping speed threshold, the method comprising: Step 1: matching similar adjacent wells similar to the target well from all adjacent wells in the block where the target well is located; Step 2: Obtain and analyze the matched adjacent well data of similar adjacent wells to determine the tripping and drilling speed values ​​of each similar adjacent well at each layer when there is no risk; Step 3: According to the formation stratification of the target well, the highest tripping speed value in similar adjacent wells is selected layer by layer from the determined tripping speed values ​​to form an optimization scheme for the tripping speed threshold of the target well; Step 4: During the process of drilling the target well, analyze in real time whether the drilling speed threshold recommended by the optimization scheme will cause drilling risks, and dynamically update and optimize the drilling speed threshold based on the suboptimal values ​​of the drilling speeds of similar adjacent wells.

2. The method according to claim 1, characterized in that In the step one, based on the data to be matched of all neighboring wells and the target well, a matching algorithm for matching similar neighboring wells is used to calculate and determine similar neighboring wells that match the target well, and the data to be matched includes at least the following: wellbore structure data, wellbore trajectory data, drilling tool assembly data, and formation stratification data.

3. The method according to claim 1 or 2, characterized in that: The adjacent well data at least include real-time logging data, formation layering data, and drilling risk data; Further in the step 2, an algorithm for identifying drilling conditions is used to analyze the logging data of similar adjacent wells to determine the drilling conditions of the similar adjacent wells. Based on the identified drilling conditions, the drilling speed values ​​of the similar adjacent wells are calculated in combination with the formation stratification data. In combination with the risk data, the drilling speed values ​​of each similar adjacent well in each layer when there is no risk are screened out.

4. The method according to claim 1 or 2, characterized in that: In step four, the bottom hole pressure fluctuation value during drilling is calculated in real time, and whether the drilling speed threshold of the target well in the current layer needs to be updated is analyzed based on the calculated bottom hole pressure fluctuation value during drilling or in combination with the real-time logging data trend of the target well.

5. The method according to claim 4, characterized in that Further including: Determine whether the bottom hole pressure fluctuation value calculated in real time during tripping exceeds the fluctuation threshold, and if so, update the tripping speed threshold of the target well at the current layer to a suboptimal value among the tripping speeds of similar adjacent wells; Otherwise, based on the real-time logging data trend of the target well, analyze whether there is a drilling risk. If so, update the target well's tripping speed threshold at the current layer to a suboptimal value among the tripping speeds of similar adjacent wells.

6. A system for optimizing a drilling tripping speed threshold, the system comprising: A similar adjacent well matching module is used to match similar adjacent wells similar to the target well from all adjacent wells in the block where the target well is located; A similar adjacent well tripping speed determination module is used to obtain and analyze the adjacent well data of the matched similar adjacent wells, and determine the tripping speed value of each similar adjacent well at each layer when there is no risk; An optimization scheme generating module, which is used to select the highest tripping speed value in similar adjacent wells layer by layer from the determined tripping speed values ​​according to the formation stratification of the target well, and form an optimization scheme for the tripping speed threshold of the target well; The optimization scheme analysis and update module is used to analyze in real time whether the drilling speed threshold recommended by the optimization scheme will cause drilling risks during the drilling of the target well, and dynamically update and optimize the drilling speed threshold according to the suboptimal value of the drilling speed of similar adjacent wells.

7. The system according to claim 6, characterized in that The similar adjacent well matching module calculates and determines similar adjacent wells that match the target well based on the data to be matched of all adjacent wells and the target well, using a matching algorithm for matching similar adjacent wells, wherein the data to be matched includes at least the following: wellbore structure data, wellbore trajectory data, drilling tool assembly data, and formation stratification data.

8. The system according to claim 6 or 7, characterized in that: The similar adjacent well tripping speed determination module further includes: The tripping condition identification submodule uses the drilling condition identification algorithm to analyze the logging data of similar adjacent wells and determine the tripping conditions of similar adjacent wells; The submodule for calculating the drilling speed of similar adjacent wells calculates the drilling speed values ​​of similar adjacent wells based on the identified drilling conditions and the formation stratification data, and screens out the drilling speed values ​​of each similar adjacent well in each layer when there is no risk, combined with the risk data.

9. The system according to claim 6 or 7, characterized in that: The optimization scheme analysis and update module is used to calculate the bottom hole pressure fluctuation value during drilling in real time, and analyze whether it is necessary to update the drilling speed threshold of the target well in the current layer based on the calculated bottom hole pressure fluctuation value during drilling or in combination with the real-time logging data trend of the target well.

10. The system according to claim 9, characterized in that The optimization scheme analysis and updating module further determines whether the bottom hole pressure fluctuation value calculated in real time during tripping exceeds the fluctuation threshold value. If it exceeds, the tripping speed threshold value of the target well at the current layer is updated to the suboptimal value among the tripping speeds of similar adjacent wells. Otherwise, based on the real-time logging data trend of the target well, analyze whether there is a drilling risk. If so, update the target well's tripping speed threshold at the current layer to a suboptimal value among the tripping speeds of similar adjacent wells.

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