Method and system for evaluating drillability of rock in real time

Abstract

The invention discloses a method and system for evaluating rock drillability in real time, and the method comprises the steps: determining a well section with logging data and element logging data at the same time in a target area, and obtaining a rock drillability grade value through the logging data; selecting element types conforming to geological characteristics of a current target area from the element logging data to form optimal element combination data of a corresponding stratum matched with the optimal element types, and based on the optimal element combination data, performing data fitting on a preset multiple regression model in combination with rock drillability levels to obtain a drillability level calculation model; the current drillability grade value calculation model is corrected by utilizing a rock core taken from a target stratum to obtain an experimental rock drillability grade value; and optimal element combination data of a target stratum is obtained in real time in the drilling process, and a dynamic rock drillability grade value is obtained by using the corrected drillability grade value calculation model, so that a rock drillability real-time evaluation result is obtained. According to the invention, real-time evaluation of the drillability of the rock is realized.

Description

Technical Field

[0001] This invention belongs to the field of petroleum engineering technology, and in particular relates to a method and system for real-time evaluation of rock drillability. Background Technology

[0002] The Xujiahe Formation in western Sichuan, China, is rich in natural gas resources. Currently, the exploration area holds proven reserves of 1.02 trillion cubic meters. Among these, the Xuer gas reservoir in the Xinchang-Hexingchang area has submitted proven reserves of 356.5 billion cubic meters (125.04 billion cubic meters proven reserves, 203.99 billion cubic meters controlled reserves, and 27.47 billion cubic meters drilled reserves). Exploration of this reservoir began in 1988, and its development has undergone three phases of development and deterioration, with only 20.097 billion cubic meters of reserves utilized. In other words, this gas reservoir has consistently failed to achieve profitable development, and its reserves are difficult to effectively utilize. One reason for this lack of profitable development is the high drilling cost, slow drilling speed, and long development cycle. Therefore, there is an urgent need for a method that can evaluate rock drillability in real time, allowing for the optimization and adjustment of drilling parameters based on drillability evaluation results during the drilling process to achieve profitable development of the gas reservoir. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides a method for real-time evaluation of rock drillability, comprising: identifying well sections within a target area that simultaneously possess both well logging data and elemental logging data, and obtaining a rock drillability grade value using the well logging data; selecting element types from the elemental logging data that conform to the geological characteristics of the current target area to form optimal element combination data matching the selected element types for the corresponding strata; based on this, combining the rock drillability grade value, performing data fitting on a preset multiple regression model to obtain a drillability grade value calculation model, and using core samples taken from the target strata to obtain experimental rock drillability grade values ​​to correct the current drillability grade value calculation model; acquiring the optimal element combination data of the target strata in real time during drilling, and obtaining a dynamic rock drillability grade value using the corrected drillability grade value calculation model, thereby obtaining a real-time evaluation result of rock drillability.

[0004] Preferably, before selecting the element type that conforms to the geological characteristics of the current target area from the element logging data, the method further includes: performing well depth scale unification processing and well depth calibration processing on the logging data and the element logging data.

[0005] Preferably, the process of unifying the well depth scale includes: configuring sampling intervals for scale unification processing for the well logging data and the elemental logging data respectively; acquiring the original well logging data obtained during the well logging operation and sampling the original well logging data according to a first sampling interval to obtain the well logging data; acquiring the original elemental logging data obtained during the elemental logging operation and sampling the original elemental logging data according to a second sampling interval to obtain the elemental logging data; and integrating the well logging data and the elemental logging data according to the well depth to unify the well logging data and the elemental logging data under the same depth scale.

[0006] Preferably, the well depth calibration process includes: acquiring quantitative cuttings from the well section that simultaneously has logging data and elemental logging data, and measuring the total radioactivity of natural GR; comparing and analyzing the measured natural GR data with the logging data from the logging data; and repositioning the well depth of the logging data and elemental logging data that have undergone well depth scale unification processing according to the comparison and analysis results, so that the repositioned well depth matches the actual geological conditions.

[0007] Preferably, the step of fitting data to a preset multiple regression model to obtain a drillability grade calculation model includes: using the rock drillability grade and the optimal element combination data, and employing a stepwise regression method to fit the multiple regression model.

[0008] Preferably, the step of selecting element types that conform to the geological characteristics of the current target area from the element logging data to form the optimal element combination data matching the selected element types of the corresponding strata includes: calculating the correlation between each element type in the element logging data using a cluster analysis method, screening out element types whose correlation calculation results exceed a preset first threshold, and recording them as the first type of element type; obtaining the selected element type by performing principal component analysis on the first type of element type, and then obtaining the optimal element combination data of the corresponding strata.

[0009] Preferably, the step of obtaining the drillability grade of the experimental rock using core samples taken from the target stratum includes: conducting a micro-drillability test on the core samples taken from the target stratum by applying axial pressure, confining pressure and pore pressure using different types of drill bits to obtain the drillability grade of the experimental rock, wherein the different types of drill bits include, but are not limited to: roller cone drill bits and PDC drill bits.

[0010] On the other hand, the present invention also provides a system for real-time evaluation of rock drillability. The system includes the following modules: a data processing module, which is used to determine well sections in a target area that simultaneously have well logging data and elemental logging data, and to obtain rock drillability grade values ​​using the well logging data; a drillability grade value calculation model generation module, which is used to select element types that conform to the geological characteristics of the current target area from the elemental logging data, so as to form optimal element combination data matching the selected element types in the corresponding strata; based on this, combined with the rock drillability grade values, a preset multiple regression model is fitted to obtain a drillability grade value calculation model, and the current drillability grade value calculation model is corrected by obtaining experimental rock drillability grade values ​​using core samples taken from the target strata; and a drillability evaluation module, which is used to acquire optimal element combination data of the target strata in real time during drilling, and to obtain dynamic rock drillability grade values ​​using the corrected drillability grade value calculation model, thereby obtaining real-time rock drillability evaluation results.

[0011] Preferably, the data processing module includes a well depth calibration processing unit, which is used to perform well depth scale unification processing and well depth calibration processing on the well logging data and the element logging data.

[0012] Preferably, the well depth repositioning processing unit includes: a well depth calibration subunit, which is used to acquire the quantitative cuttings while drilling of the well section that simultaneously has logging data and elemental logging data, and to determine the total radioactivity of natural GR. The measured natural GR data is compared and analyzed with the logging data while drilling data. Based on the comparison and analysis results, the well depth of the logging data and elemental logging data that have completed the well depth scale unification processing is repositioned so that the repositioned well depth is consistent with the actual geological conditions.

[0013] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0014] This invention proposes a method and system for real-time evaluation of rock drillability. The method first combines element-while-drilling (WWD) logging with GR data to construct and correct a drillability grade calculation model for real-time acquisition of the target formation's rock drillability during drilling. Then, it acquires the optimal element combination data of the target formation in real-time during drilling and uses the corrected drillability grade calculation model to obtain the dynamic rock drillability grade, thus yielding a real-time evaluation result of rock drillability. This invention achieves real-time evaluation of rock drillability, providing a theoretical basis for optimizing drilling parameters and selecting drill bits during drilling in deep, difficult-to-drill formations.

[0015] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0017] Figure 1 This is a step diagram of a first example of a method for real-time evaluation of rock drillability according to an embodiment of this application.

[0018] Figure 2 This is a step diagram of a second example of a method for real-time evaluation of rock drillability according to an embodiment of this application.

[0019] Figure 3 This is a module block diagram of a first example of a system for real-time evaluation of rock drillability according to an embodiment of this application.

[0020] Figure 4 This is a module block diagram of a second example of a system for real-time evaluation of rock drillability, as described in this application. Detailed Implementation

[0021] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses 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 and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0022] Furthermore, the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0023] The Xujiahe Formation in western Sichuan, China, is rich in natural gas resources. Currently, the exploration area holds proven reserves of 1.02 trillion cubic meters. Among these, the Xuer gas reservoir in the Xinchang-Hexingchang area has submitted proven reserves of 356.5 billion cubic meters (125.04 billion cubic meters proven reserves, 203.99 billion cubic meters controlled reserves, and 27.47 billion cubic meters drilled reserves). Exploration of this reservoir began in 1988, and its development has undergone three phases of development and deterioration, with only 20.097 billion cubic meters of reserves utilized. In other words, this gas reservoir has consistently failed to achieve profitable development, and its reserves are difficult to effectively utilize. One reason for this lack of profitable development is the high drilling cost, slow drilling speed, and long development cycle. Therefore, there is an urgent need for a method that can evaluate rock drillability in real time, allowing for the optimization and adjustment of drilling parameters based on drillability evaluation results during the drilling process to achieve profitable development of the gas reservoir.

[0024] Therefore, to address the aforementioned problems, this invention proposes a method and system for real-time evaluation of rock drillability. The method first combines elemental logging while drilling (MLD) with GR (Gross Regression) data while drilling to construct and correct a drillability grade calculation model for real-time acquisition of the target formation's rock drillability during drilling. Then, it acquires the optimal element combination data of the target formation in real-time during drilling and uses the corrected drillability grade calculation model to obtain a dynamic rock drillability grade, thereby obtaining a real-time evaluation result of rock drillability. This invention achieves real-time evaluation of rock drillability, providing a theoretical basis for optimizing drilling parameters and selecting drill bits during drilling in deep, difficult-to-drill formations.

[0025] Example 1

[0026] Figure 1 This is a step diagram illustrating a first example of a method for real-time evaluation of rock drillability according to an embodiment of this application. Reference is made below. Figure 1 This will explain each step of the method.

[0027] like Figure 1 As shown, in step S110, well sections within the target area that simultaneously possess both well logging data and elemental logging data are identified, and the rock drillability grade is obtained using the well logging data. Specifically, this embodiment first identifies well sections within the target area that simultaneously possess both well logging data and elemental logging data. Then, the well logging data and elemental logging data of the aforementioned well sections are collected, and based on empirical formulas for the work area, the rock drillability grade for each well section simultaneously possessing both well logging data and elemental logging data—that is, different difficult-to-drill formations—is calculated using the well logging data. The well sections simultaneously possessing both well logging data and elemental logging data are all located on the same platform or adjacent platforms within the same target area, and have similar geological characteristics.

[0028] Furthermore, in step S120, element types that conform to the geological characteristics of the current target area are selected from the element logging data, and the optimal element combination data matching the selected element types of the corresponding strata are formed. Based on this, the preset multiple regression model is fitted with rock drillability grade values ​​to obtain a drillability grade value calculation model. The current drillability grade value calculation model is corrected by using core samples taken from the target strata to obtain experimental rock drillability grade values.

[0029] In practical applications, elemental logging data within a well section typically covers more than 20 element types. However, these elemental logging data often contain elements that are unrelated or weakly correlated with the target area. If the elemental logging data is not preprocessed before application, it will not only increase the error in the rock drillability evaluation results but also increase the computational workload. To improve the reliability of the rock drillability evaluation results and ensure that the evaluation results match the actual situation, preprocessing of the elemental logging data is necessary. Therefore, this embodiment first preprocesses the elemental logging data in step S110, selecting element types that conform to the geological characteristics of the current target area. For each formation, elemental data corresponding to the selected element types are collected, thus forming the optimal element combination data matching the selected element types for the corresponding formation. Then, the optimal element combination data belonging to each formation is used as the independent variable, and the corresponding rock drillability grade value is used as the dependent variable. A pre-defined multiple regression model is then fitted to the data to construct a drillability grade calculation model. Finally, the actual drilling process of the target formation is simulated using core samples taken from the target formation to obtain the experimental rock drillability grade value. At this point, by analyzing and comparing the experimental rock drillability grade value and the actual rock drillability grade value of the target formation under the same drilling conditions, the current drillability grade value calculation model can be corrected.

[0030] In the step of selecting element types that conform to the geological characteristics of the current target area from elemental logging data to form the optimal element combination data that matches the selected element types in the corresponding strata, the correlation between each element type in the elemental logging data is first calculated using cluster analysis. The element types whose correlation calculation results exceed a preset first threshold are selected and recorded as the first type of element type. Then, the preferred element type is obtained by performing principal component analysis on the first type of element type, and then the optimal element combination data of the corresponding strata is obtained.

[0031] Specifically, this embodiment first uses cluster analysis to preliminarily screen for element types with strong correlations. Then, principal component analysis is used to select element types that conform to the geological characteristics of the current target area from the initially screened element types. Based on the selected element types, the optimal element combination data for the corresponding strata is determined. Since cluster analysis can measure the correlation between corresponding data from different data sources, this embodiment uses a systematic clustering algorithm to calculate the correlation between any two elements in the element logging data of the current target area. The correlation calculation results under different element combinations are used to characterize the similarity or closeness between element types. Next, the correlation calculation results under different element combinations are compared with a preset strong correlation threshold for element types. Element types whose correlation calculation results exceed a preset first threshold are selected and marked as the first type of element. In this way, for elements with strong correlations, the preliminary screening of element types in the element logging data is completed, so that the optimal screening of element types conforming to the geological characteristics of the current target area can be further completed based on these strongly correlated elements.

[0032] In this embodiment, based on the principal component analysis method's ability to retain existing information with as few new variables as possible and reduce computational complexity, further optimization and screening are performed on the first category of element types. From each group of first category element types, element types that conform to the geological characteristics of the current target area are selected (i.e., preferred element types).

[0033] In the process of optimizing and screening element types that conform to the geological characteristics of the current target area, the element types included in the first category are first constructed as a candidate set. Then, by adding, subtracting, or replacing elements or element ratios, different quantities and combinations of element types are randomly selected from the current candidate set to form multiple sets of element combinations. Next, the content of each element in each set is combined with the rock drillability grade value to calculate the similarity. The corresponding correlation coefficient is determined for each set of element combinations. Finally, the element combination corresponding to the highest correlation coefficient is determined as the preferred element type. At this point, after obtaining the preferred element type, the content data of each element in the preferred element type is determined as the optimal element combination data.

[0034] For example: In the candidate set, element combinations and corresponding content data sets of elements 1 to 8 are selected, and the correlation coefficient 'a' between the content data of each element in the current element combination and the rock drillability grade is calculated; In the candidate set, element combinations and corresponding content data sets of elements 1 to 9 are selected, and the correlation coefficient 'b' between the content data of each element in the current element combination and the rock drillability grade is calculated. When 'a' is less than 'b', the result of the correlation coefficient calculation is 'b'. The selected element combination is the preferred element type, and the element data of each element in the preferred element type is taken as the optimal element combination data.

[0035] In practical applications, collinearity exists between rock components and logging elements, and the type of logging element exhibiting collinearity with the rock components cannot be determined, nor can the degree of collinearity between the rock components and their corresponding logging element types be determined. Furthermore, cluster analysis cannot eliminate the influence of collinearity between rock components and their corresponding logging element types. Directly using the first element type obtained from cluster analysis will lead to a serious bias in the obtained drillability rating calculation model, thus failing to obtain reliable rock drillability evaluation results. Therefore, in this embodiment, a multiple linear stepwise regression method is used to optimize the basic data for constructing the drillability rating calculation model, thereby determining the optimal drillability rating calculation model.

[0036] In the step of fitting data to a preset multiple regression model to obtain a drillability grade calculation model, the rock drillability grade and the optimal element combination data are used, and a stepwise regression method is employed to fit the multiple regression model. Specifically, in this embodiment, the regression model formed by fitting the content data of each element in the optimal element combination data with the rock drillability grade is used as the drillability grade calculation model in the stepwise regression method.

[0037] In this embodiment, the rock drillability grade value obtained in step S110 and the optimal element combination data obtained in step S120 are substituted into a preset multiple regression model, and the data is fitted using a stepwise regression method according to the following multiple regression model expression:

[0038] Y = α0 + α1X1 + α2X2 + ... + α i X i (1)

[0039] Where Y represents the rock drillability grade value, α0, α1, α2, ..., α k Let X1, X2, ..., X represent the regression coefficients respectively. i These represent the content of different elements.

[0040] In the step of obtaining experimental rock drillability grades using core samples taken from the target formation, micro-drilling tests are conducted on the core samples using different types of drill bits, applying axial pressure, confining pressure, and pore pressure to obtain the experimental rock drillability grades. Specifically, in this embodiment, micro-drilling tests are conducted on core samples from the same target formation in the same work area, applying axial pressure, confining pressure, and pore pressure. Different types of drill bits (e.g., one type on one side, and another type on the opposite side or at other locations) are used to drill at different positions on the core samples to obtain experimental rock drillability grades corresponding to different types of drill bits (used to simulate the drillability characteristics of different drill bits in the target formation). Therefore, this invention effectively avoids experimental errors caused by the heterogeneity of different core samples, and uses the experimental rock drillability grades corresponding to different types of drill bits to complete the correction of the drillability grade calculation model, ensuring the matching degree between the drillability grade calculation results and actual working conditions. In this embodiment, different types of drill bits include, but are not limited to, roller cone bits and PDC bits.

[0041] Furthermore, in step S130, the optimal element combination data of the target formation is acquired in real time during drilling, and the dynamic rock drillability level is obtained using the corrected drillability level calculation model, thereby obtaining a real-time evaluation result of rock drillability. Specifically, in this embodiment, the optimal element combination data of the target formation is acquired in real time during drilling, and the real-time optimal element combination data is simultaneously input into the corrected drillability level calculation model to calculate the real-time drillability level, thereby obtaining the dynamic rock drillability level. Based on this, a real-time evaluation result of rock drillability during drilling is obtained according to the dynamic rock drillability level.

[0042] Example 2

[0043] Based on the above embodiment one, in order to ensure the accuracy of the drillability evaluation results, the method for real-time evaluation of rock drillability provided in this embodiment of the invention further includes the steps of performing well depth scale unification processing and well depth calibration processing on well logging data and elemental logging data in sequence. Figure 2 This is a step diagram illustrating a second example of a method for real-time evaluation of rock drillability according to an embodiment of this application. Reference is made below. Figure 2 A second example of the method for real-time evaluation of rock drillability described in the embodiments of the present invention will be described in detail.

[0044] like Figure 2As shown, step S210 identifies well sections within the target area that simultaneously possess both well logging data and elemental logging data, and uses the well logging data to obtain the rock drillability grade value. Simultaneously, step S220 performs depth-scale unification and depth calibration processing on the well logging data and elemental logging data from step S210. Then, step S230 selects element types from the processed elemental logging data in step S220 that conform to the geological characteristics of the current target area, forming optimal element combination data matching the selected element types for the corresponding strata. Based on this, and combined with the rock drillability grade value obtained from the processed well logging data in step S220, a preset multiple regression model is fitted to obtain a drillability grade value calculation model. Finally, experimental rock drillability grade values ​​obtained from core samples taken from the target strata are used to correct the current drillability grade value calculation model. Finally, in step S240, the optimal element combination data of the target formation is acquired in real time during the drilling process, and the dynamic rock drillability level value is obtained by using the corrected drillability level value calculation model in step S230, thereby obtaining the real-time evaluation result of rock drillability.

[0045] It should be noted that in this embodiment, step S210 is similar to the method described in step S110 above, step S230 is similar to the method described in step S120 above, and step S240 is similar to the method described in step S130 above. Therefore, the embodiments of the present invention will not elaborate on steps S210, S230 and S240 here.

[0046] Step S220 performs depth scale unification and depth calibration processing on the logging data and elemental logging data from step S210. In this embodiment, the logging data and elemental logging data from step S210 are first processed using the depth scale unification method, and then the depth of the corresponding well section is calibrated using the logging data and elemental logging data after depth scale unification processing to obtain the depth data.

[0047] Furthermore, in the process of unifying the well depth scale, sampling intervals for scale unification processing are first configured for both well logging data and elemental logging data. Then, the original well logging data obtained during the well logging operation is acquired and sampled according to the first sampling interval to obtain the well logging data. Similarly, the original elemental logging data obtained during the elemental logging operation is acquired and sampled according to the second sampling interval to obtain the elemental logging data. Finally, the well logging data and elemental logging data are integrated according to the well depth to unify them under the same depth scale.

[0048] In practical applications, the sampling point distance for well logging data is generally 0.1–0.125 m, while the sampling point distance for elemental logging data is generally 1–2 m. In this embodiment, by configuring sampling intervals for scale unification processing for well logging data and elemental logging data respectively, the well logging data and elemental logging data are processed so that the processed well logging data and elemental logging data for the same well section reflect the information of the same layer in that well section.

[0049] Specifically, sampling intervals for scale unification processing are configured for both well logging data and elemental logging data within the same well section. The sampling interval for scale unification processing of well logging data is designated as the first sampling interval, and the sampling interval for scale unification processing of elemental logging data is designated as the second sampling interval. Next, in well sections where both well logging data and elemental logging data coexist, relevant construction data from the well logging and elemental logging processes are extracted. Raw well logging data is obtained from the well logging construction data. Data points containing the raw well logging data are sampled according to the first sampling interval, and the data from each sampled data point in each well section are integrated into a raw well logging dataset. This raw well logging dataset is then used as the well logging data for obtaining rock drillability grades. Similarly, raw elemental logging data is obtained from the elemental logging construction data. Data points containing the raw elemental logging data are sampled according to the second sampling interval, and the data from each sampled data point in each well section are integrated into a raw elemental logging dataset. This raw elemental logging dataset is then used as the elemental logging data for obtaining preferred element types. Based on the aforementioned well depth data, the original logging datasets and original element logging datasets for each well section are integrated separately, thereby unifying the logging data intervals and element logging data intervals for each well section to the same depth scale.

[0050] It should be noted that the embodiments of the present invention do not specifically limit the distance between the designated first sampling interval and the second sampling interval, and those skilled in the art can set it according to the actual situation.

[0051] Furthermore, since well logging depth is the cable depth and elemental logging data is the drill string depth, the depth data obtained using well logging and elemental logging methods are inconsistent due to systematic errors in these two methods. To improve the accuracy of rock drillability evaluation results, this application employs a depth realignment method to process well logging and elemental logging data, thereby calibrating the well depth.

[0052] like Figure 2As shown, in the depth repositioning process, the drilling cuttings of the well section with both logging data and elemental logging data are obtained and the total radioactivity of natural GR is measured. The measured natural GR data is compared and analyzed with the drilling GR data in the logging data. Based on the comparison and analysis results, the well depth of the logging data and elemental logging data that have completed the depth scale unification process is repositioned so that the repositioned well depth is consistent with the actual geological conditions.

[0053] Specifically, in this embodiment, the drilling-while-drilling quantitative cuttings of the well section where the logging data is located in step S210 are first obtained. The natural GR radioactivity of the drilling-while-drilling quantitative cuttings is measured using a natural gamma ray detector to obtain the natural GR data of the corresponding well section. The natural GR data is compared and analyzed with the drilling-while-drilling GR data in the same well section to determine the similar natural GR data and drilling-while-drilling GR data. The actual well depth corresponding to the natural GR data is calibrated below the well depth corresponding to the drilling-while-drilling GR data that is similar to the current natural GR data. In this way, the depth unification processing of logging data and elemental logging data and the well depth calibration of the well section are completed, so that the well depth after repositioning is consistent with the actual geological conditions.

[0054] Example 3

[0055] Based on the method for real-time evaluation of rock drillability described in Embodiment 1 above, this embodiment of the invention also provides a system for real-time evaluation of rock drillability (hereinafter referred to as "rock drillability evaluation system"). Figure 3 This is a module block diagram of a first example of a system for real-time evaluation of rock drillability according to an embodiment of this application.

[0056] like Figure 3As shown, the rock drillability evaluation system in this embodiment of the invention includes: a data processing module 31, a drillability grade value calculation model generation module 32, and a drillability evaluation module 33. Specifically, the data processing module 31 is implemented according to the method described in step S110 above, configured to determine well sections in the target area that simultaneously have well logging data and element logging data, and to obtain rock drillability grade values ​​using the well logging data; the drillability grade value calculation model generation module 32 is implemented according to the method described in step S120 above, configured to select element types that conform to the geological characteristics of the current target area from the element logging data, so as to form the optimal element combination data that matches the selected element types in the corresponding strata. Based on this, combined with the rock drillability grade value, the preset multiple regression model is fitted to obtain the drillability grade value calculation model, and the current drillability grade value calculation model is corrected by obtaining the experimental rock drillability grade value using the core taken from the target strata; the drillability evaluation module 33 is implemented according to the method described in step S130 above, configured to obtain the optimal element combination data of the target strata in real time during drilling, and to obtain the dynamic rock drillability grade value using the corrected drillability grade value calculation model, thereby obtaining the real-time rock drillability evaluation result.

[0057] Example 4

[0058] Based on the method for real-time evaluation of rock drillability described in Embodiment 2 above, this embodiment of the invention also provides a system for real-time evaluation of rock drillability (hereinafter referred to as "rock drillability evaluation system"). Figure 4 This is a module block diagram of a second example of a system for real-time evaluation of rock drillability, as described in this application.

[0059] like Figure 4As shown, the rock drillability evaluation system in this embodiment includes: a data processing module 41, a well depth localization processing unit 411, a drillability grade calculation model generation module 42, and a drillability evaluation module 43. Specifically, the data processing module 41 is implemented according to the method described in step S210 above, configured to determine the well section in the target area that simultaneously has logging data and elemental logging data, and to obtain the rock drillability grade value using the logging data; the well depth localization processing unit 411 is implemented according to the method described in step S220 above, configured to perform well depth scale unification processing and well depth calibration processing on the logging data and elemental logging data; the drillability grade calculation model generation module 42 is implemented according to the method described in step S230 above, configured to select element types that conform to the geological characteristics of the current target area from the elemental logging data. The optimal element combination data matching the preferred element type for the corresponding strata is formed. Based on this, the pre-set multiple regression model is fitted with the rock drillability grade value to obtain the drillability grade value calculation model. The current drillability grade value calculation model is corrected by using the rock core taken from the target strata to obtain the experimental rock drillability grade value. The drillability evaluation module 43 is implemented according to the method described in step S240. It is configured to obtain the optimal element combination data of the target strata in real time during the drilling process, and obtain the dynamic rock drillability grade value using the corrected drillability grade value calculation model, thereby obtaining the real-time evaluation result of rock drillability.

[0060] The well depth calibration unit 411 includes a well depth calibration subunit. This subunit is used to acquire quantitative cuttings data from well sections with both logging and elemental logging data, and to determine the total radioactivity of natural GR (gravelly precipitate). The measured natural GR data is compared and analyzed with the logging data from the drilling data. Based on the comparison and analysis results, the well depth of the logging and elemental logging data, after undergoing unified well depth scale processing, is calibrated to ensure that the calibrated well depth matches the actual geological conditions.

[0061] This invention proposes a method and system for real-time evaluation of rock drillability. The method first combines element-while-drilling (WWD) logging with GR data to construct and correct a drillability grade calculation model for real-time acquisition of the target formation's rock drillability during drilling. Then, it acquires the optimal element combination data of the target formation in real-time during drilling and uses the corrected drillability grade calculation model to obtain the dynamic rock drillability grade, thus yielding a real-time evaluation result of rock drillability. This invention achieves real-time evaluation of rock drillability, providing a theoretical basis for optimizing drilling parameters and selecting drill bits during drilling in deep, difficult-to-drill formations.

[0062] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0063] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the claims of the present invention.

[0064] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps as a single integrated circuit module. Thus, the present invention is not limited to any particular hardware and software combination.

[0065] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for real-time evaluation of rock drillability, characterized in that, include: Identify well sections within the target area that simultaneously possess both well logging data and elemental logging data, and use the well logging data to obtain rock drillability grade values; Element types that conform to the geological characteristics of the current target area are selected from the element logging data to form the optimal element combination data that matches the selected element types in the corresponding strata. Based on this, combined with the rock drillability grade value, the preset multiple regression model is fitted to obtain the drillability grade value calculation model. The current drillability grade value calculation model is corrected by using the rock core taken from the target strata to obtain the experimental rock drillability grade value. During the drilling process, the optimal element combination data of the target formation is acquired in real time, and the dynamic rock drillability level value is obtained by using the corrected drillability level value calculation model, thereby obtaining the real-time evaluation result of rock drillability.

2. The method according to claim 1, characterized in that, Before selecting element types from the elemental logging data that match the geological characteristics of the current target area, the method further includes: The well logging data and the elemental logging data are subjected to well depth scale unification processing and well depth calibration processing.

3. The method according to claim 2, characterized in that, The process of standardizing well depth dimensions includes: Configure sampling intervals for scale unification processing for the well logging data and the elemental logging data respectively; The original logging data obtained during the logging operation is acquired, and the original logging data is sampled according to the first sampling interval to obtain the logging data; the original element logging data obtained during the element logging operation is acquired, and the original element logging data is sampled according to the second sampling interval to obtain the element logging data. According to the well depth, the logging data and the elemental logging data are integrated to unify the logging data and the elemental logging data under the same depth scale.

4. The method according to claim 2 or 3, characterized in that, The process of well depth calibration includes: Quantitative cuttings from well sections with both logging and elemental logging data are obtained during drilling, and the total radioactivity of natural GR is measured. The measured natural GR data is compared and analyzed with the GR data from the logging data. Based on the comparison and analysis results, the well depths of the logging data and elemental logging data that have undergone unified depth scale processing are repositioned so that the repositioned well depths are consistent with the actual geological conditions.

5. The method according to any one of claims 1 to 4, characterized in that, The steps of fitting data to a pre-defined multiple regression model to obtain a drillability level calculation model include: Using the rock drillability rating and the optimal element combination data, the multivariate regression model is fitted with a stepwise regression method.

6. The method according to any one of claims 1 to 5, characterized in that, The step of selecting element types that conform to the geological characteristics of the current target area from the element logging data to form the optimal element combination data that matches the selected element types in the corresponding strata includes: Cluster analysis is used to calculate the correlation between different element types in the element logging data. Element types whose correlation calculation results exceed a preset first threshold are selected and denoted as the first type of element. The preferred element type is obtained by performing principal component analysis on the first type of element, and then the optimal element combination data of the corresponding strata are obtained.

7. The method according to any one of claims 1 to 6, characterized in that, The steps for obtaining the drillability grade of experimental rocks using core samples taken from the target formation include: Micro-drillability tests were conducted on core samples taken from the target formation using different types of drill bits to apply axial pressure, confining pressure, and pore pressure. The drillability grade of the tested rock was obtained. The different types of drill bits include, but are not limited to, roller cone bits and PDC bits.

8. A system for real-time evaluation of rock drillability, characterized in that, The system includes the following modules: The data processing module is used to determine the well section in the target area that has both well logging data and elemental logging data, and to obtain the rock drillability grade value using the well logging data; The drillability grade calculation model generation module is used to select element types that conform to the geological characteristics of the current target area from the element logging data, so as to form the optimal element combination data that matches the selected element types in the corresponding strata. Based on this, combined with the rock drillability grade, the preset multiple regression model is fitted to obtain the drillability grade calculation model, and the current drillability grade calculation model is corrected by using the rock core taken from the target strata to obtain the experimental rock drillability grade. The drillability evaluation module is used to acquire the optimal element combination data of the target formation in real time during the drilling process, and to obtain the dynamic rock drillability level value using the corrected drillability level value calculation model, thereby obtaining the real-time evaluation result of rock drillability.

9. The system according to claim 8, characterized in that, The data processing module includes: The well depth calibration processing unit is used to perform well depth scale unification processing and well depth calibration processing on the well logging data and the element logging data.

10. The system according to claim 9, characterized in that, The well depth repositioning processing unit includes: The well depth calibration subunit is used to acquire quantitative cuttings from well sections that simultaneously have logging data and elemental logging data, and to determine the total radioactivity of natural GR. The obtained natural GR data is compared and analyzed with the logging data from the drilling data. Based on the comparison and analysis results, the well depth of the logging data and elemental logging data that have undergone unified well depth scale processing is repositioned so that the repositioned well depth matches the actual geological conditions.

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