CN111706322A - Rock drilling response prediction method and prediction system - Google Patents
Rock drilling response prediction method and prediction system Download PDFInfo
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- CN111706322A CN111706322A CN202010692453.0A CN202010692453A CN111706322A CN 111706322 A CN111706322 A CN 111706322A CN 202010692453 A CN202010692453 A CN 202010692453A CN 111706322 A CN111706322 A CN 111706322A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
- E21B49/003—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells by analysing drilling variables or conditions
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Abstract
The invention discloses a prediction method and a prediction system of rock drilling response, wherein the prediction method comprises the following steps: drilling parameters of different mileage of a rock mass are obtained, and a relation model of the drilling parameters and intermediate variables is obtained; analyzing the saturated compressive strength of rocks with different mileage of the rock mass to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks; obtaining rock integrity degrees of different mileage of a rock mass while drilling, and correcting an intermediate variable according to the rock integrity degrees and drilling parameters; obtaining the corresponding relation between the drilling parameters and the corrected intermediate variables and the rock saturated compressive strength and the rock integrity degree by using soft calculation; and acquiring the corresponding rock saturated compressive strength and rock integrity degree according to the drilling parameters and the intermediate variables at any position. According to the rock mass prediction method and device, through collecting sample data and theoretical analysis and forming corresponding relations, corresponding rock mass information is obtained through the corresponding relation prediction of arbitrary drilling data, the prediction process is simple and convenient, and the rock mass prediction method and device have universal applicability.
Description
Technical Field
The invention relates to the technical field of rock and soil exploration, in particular to a rock drilling response prediction method and a rock drilling response prediction system.
Background
The acquisition of rock mass characteristic parameters is an important task in rock mass engineering, and the design, construction, operation and maintenance can be reasonably carried out only by fully knowing information such as underground rock strength, rock mass structure and the like, so that the advance geological forecast of the tunnel face in the early stage is indispensable work. Rock strength and structural characteristics need to be obtained when rock engineering is carried out, underground rock and soil body samples are directly obtained through the work, through coring, geotechnical and rock mechanics experiments, the problems of time consumption, long period, high cost and the like exist when rock characteristics are obtained through a direct method based on laboratory analysis, the laboratory state cannot completely simulate the underground state, and discontinuous due to the fact that rock cores cannot be obtained in some well sections (weak interlayers, broken zones and the like) are caused. Although many researches on the aspect of detection of the drilling process are carried out at present, identification of the stratum based on the drilling parameters still remains in the qualitative aspect, and quantitative description on the strength of the rock and evaluation on the breaking condition of the geological condition cannot be carried out at present.
In summary, how to provide a method for conveniently and accurately predicting rock characteristics is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for predicting rock drilling response, which can achieve more accurate prediction of rock characteristics, and are simpler and easier to operate and easy to implement.
In order to achieve the above purpose, the invention provides the following technical scheme:
a method of predicting rock drilling response, comprising:
acquiring drilling parameters of different mileage of a rock mass, and acquiring a relation model of the drilling parameters and an intermediate variable, wherein the intermediate variable is a new dimensionless parameter obtained by combining the drilling parameters and is used for explaining and evaluating geological conditions;
analyzing the saturated compressive strength of rocks with different mileage of the rock mass to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks;
obtaining rock integrity degrees of different mileage of a rock mass while drilling, and correcting the intermediate variable according to the rock integrity degrees and the drilling parameters;
obtaining the corresponding relation between the drilling parameters and the corrected intermediate variables and the rock saturated compressive strength and the rock integrity degree by soft calculation; and acquiring the corresponding rock saturated compressive strength and the rock integrity degree according to the corresponding relation by using the drilling parameters and the intermediate variables at any position.
Preferably, obtaining a relational model of the drilling parameters and the intermediate variables comprises:
theoretically deducing to obtain a mathematical model of the drilling parameters and the intermediate variables;
wherein the drilling parameters comprise feeding speed, striking pressure, propelling pressure, revolving pressure, water pressure and water flow;
the intermediate variable at least comprises one of drilling energy, normalized drilling speed ratio and elastic wave reflection coefficient.
Preferably, the analysis of the saturated compressive strengths of the rocks at different mileage includes:
drilling and coring to obtain a rock mass, analyzing the rock mass, and dividing and marking the rock mass with different mileage according to the saturated compressive strength of the rock;
the saturated compressive strength of rock includes hard rock, harder rock, softer rock, soft rock and extremely soft rock.
Preferably, the rock integrity degrees of different mileage of the rock mass are obtained while drilling, and the rock integrity degrees comprise:
drilling the rock mass, acquiring the rock mass fracture condition, and dividing and marking the rock mass with different mileage according to the rock integrity degree;
the degree of rock integrity includes whole rock, more broken rock, and extremely broken rock.
Preferably, the rock body fracture condition is obtained in real time by drilling shooting and physical exploration while drilling the rock body.
Preferably, modifying the intermediate variable with the degree of rock integrity and the drilling parameter comprises:
and verifying the incidence relation between the intermediate variable and the rock integrity degree according to the rock integrity degree corresponding to each mileage in the drilling process and the corresponding relation between the corresponding drilling parameters, and correcting the intermediate variable according to the incidence relation.
Preferably, the soft computing obtains the corresponding relationship between the drilling parameter, the corrected intermediate variable, the rock saturation compressive strength and the rock integrity degree, and includes:
taking the drilling parameters and the corrected intermediate variables as input data, taking the corresponding rock saturated compressive strength and the rock integrity degree as output data, and performing model training by using soft calculation to establish a prediction model from the drilling parameters to the rock saturated compressive strength and the rock integrity degree; the soft computing comprises at least one of a cross validation least square support vector method, a nonlinear multiple regression analysis, an artificial neural network and an adaptive neural fuzzy inference system;
and acquiring the corresponding rock saturated compressive strength and the rock integrity degree through the corresponding relation by using the drilling parameters and the intermediate variables at any position, wherein the acquiring comprises the following steps:
and inputting the drilling parameters and the intermediate variables of any position into the estimation model, and obtaining the rock saturation compressive strength and the rock integrity degree obtained by the estimation model.
Preferably, before performing model training, the method further includes, with the drilling parameters and the corrected intermediate variables as input data and the corresponding rock saturation compressive strength and the rock integrity degree as output data:
and taking 80% of sample data with the existing corresponding relation as a model training set, and taking 20% of the data with the existing corresponding relation as a model testing set.
A system for predicting rock drilling response, comprising:
the data exploration acquisition module is used for acquiring drilling parameters of different mileage of a rock mass;
the theoretical derivation module is used for acquiring a relation model of the drilling parameters and intermediate variables, and the intermediate variables are used for explaining and evaluating geological conditions;
the theoretical analysis module is used for analyzing the saturated compressive strength of rocks with different mileage to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks;
the exploration while drilling module is used for acquiring the rock integrity degree of different mileage of a rock body while drilling and correcting the intermediate variable according to the rock integrity degree and the drilling parameter;
the soft computing module is used for acquiring the corresponding relation among the drilling parameters, the corrected intermediate variables, the rock saturated compressive strength and the rock integrity degree by using soft computing, and is connected with the theoretical analysis module and the exploration while drilling module;
the prediction module is used for acquiring the corresponding rock saturated compressive strength and the rock integrity degree according to the corresponding relation by using the drilling parameters and the intermediate variables at any position; the prediction module is connected with the soft computing module.
Preferably, the survey while drilling module comprises:
the obtaining submodule is used for obtaining the corresponding relation between the rock integrity degree corresponding to the rock of each mileage and the corresponding drilling parameter;
and the verification submodule is used for verifying the incidence relation between the intermediate variable and the rock integrity degree and correcting the intermediate variable through the incidence relation.
The method provided by the invention can convert the acquired drilling parameters into intermediate variables closely related to geology, obtains the relation with the intermediate variables through theoretical analysis and actual measurement in a laboratory, marks the intermediate variables according to different mileage, and forms a plurality of groups of mapping relations from the drilling parameters to the rock saturated compressive strength and the rock integrity degree, so that after new drilling parameters are actually measured, the rock saturated compressive strength and the rock integrity degree corresponding to the drilling parameters are obtained by utilizing the corresponding relations, and the actual condition of a rock body is obtained.
This application is through gathering sample data, theoretical analysis to form corresponding relation, thereby when conveniently creeping into data wantonly, the rock mass information that the prediction obtained corresponds makes the prediction process simple and convenient, can be applied to the prediction of a plurality of rock masses repeatedly, and has universal suitability.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method of predicting rock drilling response provided herein.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The core of the invention is to provide a prediction method and a prediction system of rock drilling response, the method and the system can realize more accurate prediction of rock characteristics, and the operation is simpler and more convenient and is easy to realize.
The application provides a method for predicting rock drilling response, which is used for realizing the prediction process of actual conditions of rock drilling and can realize the prediction from a common rock mass to a rock mass to be measured, and the method specifically comprises the following steps:
and step S1, obtaining drilling parameters of different mileage of the rock mass, and obtaining a relation model of the drilling parameters and intermediate variables, wherein the intermediate variables are new dimensionless parameters obtained by combining the drilling parameters and are used for explaining and evaluating geological conditions.
And step S2, analyzing the saturated compressive strength of the rocks with different mileage to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks.
And step S3, obtaining rock integrity degrees of different mileage of the rock mass while drilling, and correcting intermediate variables according to the rock integrity degrees and drilling parameters.
S4, obtaining the corresponding relation between the drilling parameters and the corrected intermediate variables and the rock saturated compressive strength and the rock integrity degree by soft calculation; and acquiring the corresponding rock saturated compressive strength and rock integrity degree through the corresponding relation according to the drilling parameters and the intermediate variables at any position.
The acquisition operation refers to a real-time identification technology, namely a sensor technology, and the data of the rock mass are collected and can be further transmitted and stored. Specific parameter composition can be referred to the prior art.
The drilling parameters may include a feeding pressure fluctuation parameter, and when geological evaluation is performed by using the drilling parameters acquired in step S1, the feeding (pushing) pressure fluctuation is generally large in a fracture zone, a fracture development zone, and a fault development zone with poor geological conditions. Therefore, the position of the fracture zone can be inferred by the dimensionless intermediate variable obtained by combining the drilling parameters, and the geological condition is reflected laterally.
Obtaining a model of the relationship of the drilling parameters to the intermediate variables may generally be a mathematical relationship between the two.
In step S2, before analyzing the saturated compressive strength of the rock at different mileage of the rock, the part of the rock is required to be obtained, and the analysis means obtaining high-precision analysis data through laboratory analysis, obtaining the saturated compressive strength of the rock, and further obtaining the relationship between the saturated compressive strength of the rock and the intermediate variable by combining different mileage of the rock. Among them, the rock saturated compressive strength is also referred to as rock uniaxial saturated compressive strength.
In step S3, acquiring while drilling means directly acquiring the integrity of the rock from the rock sample obtained while drilling, and because there are the determined integrity of the rock and the corresponding drilling parameters, mileage, etc., the intermediate variable can be directly corrected to obtain a more accurate intermediate variable that can meet the actual situation.
So far, drilling parameters, intermediate variables, corresponding rock saturated compressive strength and rock integrity degree under different mileage form a plurality of groups of data, and the corresponding relation is also determined. Therefore, the corresponding relation of the drilling parameters and the intermediate variables can be formed into a systematic relation model by using a soft computing method, which is similar to a mapping comparison table, so that when new drilling parameters and intermediate variables are obtained, the corresponding rock saturated compressive strength and rock integrity degree can be obtained through the relation model.
The method can convert the obtained drilling parameters into intermediate variables closely related to geology, obtains the relation between the intermediate variables through theoretical analysis and actual measurement of a laboratory, and marks the intermediate variables according to different mileage, so that a plurality of groups of mapping relations from the drilling parameters to the rock saturated compressive strength and the rock integrity degree are formed, and the rock saturated compressive strength and the rock integrity degree corresponding to the drilling parameters are obtained by utilizing the corresponding relations after new drilling parameters are actually measured, so that the actual condition of a rock body is obtained. This application is through gathering sample data, theoretical analysis to form corresponding relation, thereby when conveniently creeping into data wantonly, the rock mass information that the prediction obtained corresponds makes the prediction process simple and convenient, can be applied to the prediction of a plurality of rock masses repeatedly, and has universal suitability.
On the basis of the above embodiment, in step S1, the method for obtaining the relation model between the drilling parameters and the intermediate variables specifically includes the following steps:
s11, theoretically deducing to obtain a mathematical model of the drilling parameters and the intermediate variables;
wherein, the drilling parameters comprise feeding speed, striking pressure, propelling pressure, revolving pressure, water pressure and water flow; the intermediate variable includes at least one of drilling energy, normalized drilling speed ratio, and elastic wave reflection coefficient.
It should be noted that the relationship between the drilling parameter and the intermediate variable may be a mathematical formula, a mathematical model, a mapping relationship, or the like.
The drilling parameters may include other measurable characteristic parameters for the rock in addition to feed speed, percussion pressure, feed pressure, gyration pressure, water pressure, and water flow. The intermediate variables are to make non-dimensionalization after combining the drilling parameters, so as to better explain and evaluate the parameters of the geological condition, that is, when the drilling parameters are changed into the intermediate variables in the way of mathematical change and the like, the propelling pressure and the revolving pressure do not participate in the consideration.
The intermediate variables include, but are not limited to, drilling energy, normalized drilling speed ratio, and elastic wave reflection coefficient. The intermediate variables may be used to reflect characteristics of lithology, structural planes, and weak interbeds primarily based on drilling parameters.
The above-described manner of converting drilling parameters into intermediate variables requires the combination of common sense indications such as the working principle of the drilling machine, rock breaking chemistry, acoustics, and percussion dynamics. In actual operation, one skilled in the art can analyze the working principle of the drilling machine, the rock breaking process of the drill bit, the acoustic response of the drilling process, and the generation and propagation process of the stress wave of the drill rod, so as to establish a mathematical model between the drilling process parameters and the intermediate variables.
On the basis of the above embodiment, in step S2, the method for analyzing the saturated compressive strength of rocks with different mileage includes the following steps:
step S21, drilling holes and coring to obtain rock masses, analyzing the rock masses, and dividing and marking the rock masses with different mileage according to the saturated compressive strength of the rock;
the saturated compressive strength of rock includes hard rock, harder rock, softer rock, soft rock and extremely soft rock.
Specifically, during actual operation, core can be got through the drilling, underground rock and soil body sample is directly obtained to through laboratory analysis obtain the data of high accuracy, the in-process can obtain the most accurate stratum information, and need mark the sample according to different mileage. Namely, the rock masses with different mileage are subjected to label classification according to the rock saturated compressive strength of the rock masses, and the rock is divided into hard rock, harder rock, softer rock, soft rock and extremely soft rock by the saturated compressive strength.
In step S21, the laboratory analysis is performed by sampling to obtain the soft and hard classifications of the rock at different mileage, and actually, the conventional classification of the soft and hard degrees in the sampled samples is obtained, and the classification is used to obtain the mark of the saturated compressive strength of the rock from the drilling parameters to different mileage by combining the drilling parameters at different mileage, so as to obtain the mark of the saturated compressive strength of the rock through the drilling parameters at the prediction stage.
On the basis of the above embodiment, in step S3, the method for obtaining the integrity degrees of rocks of different mileage of a rock mass while drilling specifically includes the following steps:
step S31, obtaining rock mass fracture conditions while drilling, and dividing and marking rock masses with different mileage according to the integrity degree of the rock;
the degree of rock integrity includes intact rock, more broken rock, and extremely broken rock.
The degree of rock integrity is an important indicator for evaluating the quality of rock mass. In the steps, the rock is divided into complete, more broken, broken and extremely broken rock according to the integrity degree of the rock, the sample is marked as a corresponding label, and the mileage drilled in the rock is marked.
Optionally, in step S31, the rock fracture condition is obtained in real time by drilling image and physical exploration while drilling the rock.
In the embodiment, a method of drilling, shooting and geophysical exploration is provided, so that the actual rock mass fracture condition can be obtained in real time, but the actual operation process is not limited to the above condition.
On the basis of the above embodiment, the method for modifying the intermediate variable according to the rock integrity degree and the drilling parameter in step S3 specifically includes the following steps:
and S32, verifying the incidence relation between the intermediate variable and the rock integrity degree according to the rock integrity degree corresponding to each mileage in the drilling process and the corresponding relation between the corresponding drilling parameters, and correcting the intermediate variable through the incidence relation.
The integrity degree of the rock obtained while drilling is combined with the drilling parameters obtained while drilling measurement, so that the incidence relation between the intermediate variable and the actual condition of the rock is verified, the intermediate variable can be corrected, and the rock mass discrimination based on the intermediate variable is improved by adjusting the intermediate variable.
On the basis of the above embodiment, in step S4, the method for soft computing the corresponding relationship between the obtained drilling parameters and the corrected intermediate variables, the saturated compressive strength of the rock, and the rock integrity degree specifically includes the following steps:
s41, taking the drilling parameters and the corrected intermediate variables as input data, taking the corresponding rock saturated compressive strength and rock integrity degree as output data, performing model training by using soft calculation, and establishing a prediction model from the drilling parameters to the rock saturated compressive strength and the rock integrity degree; the soft calculation comprises at least one of a vector method based on cross validation least square support, nonlinear multiple regression analysis, an artificial neural network and an adaptive neural fuzzy inference system;
in step S4, a method for obtaining the corresponding rock saturation compressive strength and rock integrity degree through the corresponding relationship based on the drilling parameters and the intermediate variables at any position specifically includes the following steps:
and step S42, inputting the drilling parameters and the intermediate variables of any position into the estimation model, and obtaining the rock saturation compressive strength and the rock integrity degree obtained by the estimation model.
In step S41, the parameters are mapped using known data, and the existing data is learned in the artificial neural network. Specifically, a black box model is formed, the drilling parameters and the corrected intermediate variables are used as input data, the corresponding rock saturated compressive strength and rock integrity degree are used as output data, and multiple groups of complete corresponding relations form an estimated model, namely, the corresponding relations from the known drilling parameters, the corrected intermediate variables to the rock saturated compressive strength and the rock integrity degree learn multiple groups of data, and the established mapping relations are stored and used for predicting the process.
The learning process of the neural network is a common mode in the prior art, and in the embodiment, the method is used for realizing the corresponding relation from the drilling parameters to the actual condition of the rock mass.
It should be noted that the above correspondence is that one or a set of drilling parameters corresponds to one of the 5 characteristics of rock integrity, i.e. one of whole rock, more broken rock, broken rock and extremely broken rock, while the drilling parameters can also correspond to the 5 characteristics of hard rock, harder rock, softer rock and extremely soft rock in the saturated compressive strength of the rock, for example one drilling parameter can correspond to broken rock and harder rock.
Step S42 is a process for prediction, and the mapped rock saturation compressive strength and rock integrity degree are directly obtained by inputting drilling parameters, and the step depends on the corresponding relationship obtained in step S41.
On the basis of the above embodiment, in step S41, taking the drilling parameters and the corrected intermediate variables as input data, and taking the corresponding rock saturation compressive strength and rock integrity degree as output data, the method specifically includes the following steps before performing model training:
and S40, taking 80% of the existing corresponding relation sample data as a model training set, and taking 20% of the existing corresponding relation data as a model testing set.
Because the corresponding relation needs to be learned, the test also needs to be performed, and optionally the learning is continued after the test, the sample cannot be used for learning only, and a part of the sample needs to be tested.
The soft computing method provided in the present application is a low cost solution by fault tolerance for uncertainty, inaccuracy and incomplete truth. At present, common modes of soft computing methods include using a cross-validation-based least squares support vector machine, nonlinear multiple regression analysis, artificial neural networks, and adaptive neuro-fuzzy inference systems, which have the advantage of not requiring explicit mathematical equations and derivative expressions. The known input data and output data are generally learned or the matching relationship is determined, so as to establish a regular corresponding relationship, and the regular corresponding relationship is used for predicting other data.
In the method provided above, an estimation model from intermediate variables to rock saturated compressive strength and rock integrity is established by soft calculation. The rock parameter sample data comprises drilling parameter data and corrected intermediate variables as input data or an input matrix, and the rock saturated compressive strength and the rock integrity degree form output data or an output matrix.
Preferably, 80% of the sample data of the sample volume is used for model training, and the remaining 20% of the data is used for model testing. In the training process, the hyper-parameters in the model are updated through continuously accumulated samples, the relation between drilling parameters and rock characteristics (rock saturated compressive strength and rock integrity degree) is established through a formed black box type structure, the value of effective measured data of a drilling machine in drilling is fully utilized, the rock characteristics of a drilling stratum are conveniently obtained, and therefore the workload of drilling coring and indoor physical mechanics tests is effectively reduced.
The above embodiments provide various theoretical analysis and actual detection methods, and are not limited to the method for acquiring rock mass characteristics in a single way in the conventional method. The method combines various modes of measurement while drilling, core drilling and shooting of the drill hole to obtain rock mass data, and derives intermediate variables such as drilling energy, normalized drilling speed ratio, elastic wave reflection coefficient and the like from drilling parameters, thereby acquiring a large number of data samples and providing characteristic input and output of data for a model established by soft computing.
Different measurement and calculation methods have different effects and uses. The in-situ characteristics of the rock can be rapidly acquired in real time through measurement while drilling, and the characteristics of the rock can be acquired in an auxiliary mode through drilling coring and drilling camera shooting. In addition, in order to better explain and evaluate the geological condition, the application also introduces the characteristic of an intermediate variable, the position of the fracture zone is estimated through the intermediate variable, and the geological condition is reflected laterally.
Compared with the traditional statistical regression method, the soft computing method has more advantages in solving the problems of small-scale samples and nonlinear prediction, and can obtain good effect in rock characteristic estimation. The method enriches indirect methods for obtaining rock characteristic parameters, is applied to prediction of hard rocks and soft rocks, and can promote application of a drilling process detection technology and a lithology while drilling identification technology in rock engineering.
In addition to the rock drilling response prediction method provided in the above embodiments, the present invention also provides a rock drilling response prediction system for implementing the above method, wherein each module is specifically used for implementing the steps in the above method, and the connection relationship between each module is based on the data transmission required in the process of implementing the above method.
The application provides a prediction system of rock drilling response, this system mainly includes: the device comprises a data exploration and acquisition module, a theoretical derivation module, a theoretical analysis module, a survey while drilling module, a soft calculation module and a prediction module.
The data exploration and acquisition module is used for acquiring drilling parameters of different mileage of a rock mass;
the theoretical derivation module is used for acquiring a relation model of the drilling parameters and intermediate variables, and the intermediate variables are variables for better explaining and evaluating geological conditions;
the theoretical analysis module is used for analyzing the rock saturated compressive strength of different mileage of the rock mass to obtain the relation between the intermediate variable and the rock saturated compressive strength;
the exploration while drilling module is used for acquiring the rock integrity degree of different mileage of a rock body while drilling and correcting an intermediate variable according to the rock integrity degree and the drilling parameters;
the soft computing module is used for acquiring the corresponding relation among the drilling parameters, the corrected intermediate variables, the rock saturated compressive strength and the rock integrity degree by using soft computing, and is connected with the theoretical analysis module and the exploration while drilling module;
the prediction module is used for acquiring the corresponding rock saturated compressive strength and rock integrity degree according to the corresponding relation by using the drilling parameters and the intermediate variables at any position; the prediction module is connected with the soft computing module.
It should be noted that, since all the modules are used for completing the main steps in the method, the content executed by each module is not specifically described again, please refer to the description in the embodiment of the method.
On the basis of the above embodiment, the exploration while drilling module comprises:
the obtaining submodule is used for obtaining the corresponding relation between the rock integrity degree corresponding to the rock of each mileage and the corresponding drilling parameter;
and the verification submodule is used for verifying the incidence relation between the intermediate variable and the rock integrity degree and correcting the intermediate variable through the incidence relation.
In the method and the system provided by the application, the obtained drilling parameters are converted into intermediate variables such as drilling energy, normalized drilling speed ratio, elastic wave reflection coefficient and the like closely related to geology so as to be used as characteristic items input by a soft calculation model and better explain and evaluate geological conditions;
when the corresponding relation is established, acquiring rock uniaxial saturated compressive strength by means of drilling coring, acquiring rock integrity degree in real time by means of drilling camera shooting and geophysical detection, and establishing a model from an intermediate variable to the rock saturated compressive strength and the rock integrity degree through soft calculation, so that rock characteristics are quantitatively described in situ in the drilling process;
response relation is established between the drilling parameters and the rock characteristics in a soft computing mode, and the prediction advantages of the drilling parameters and the rock characteristics in small samples and nonlinear prediction problems can be remarkably solved; the process of the method is not limited to a single method for obtaining rock mass characteristics, and in the acquisition and derivation process, other modes which are convenient for obtaining characteristics can be selected besides various modes of measurement while drilling, core drilling and shooting of the drill hole, so as to indirectly obtain the data of the rock mass.
In addition to the solutions provided in the above embodiments, for other operations occurring in the method and system, which are all common means or methods in the prior art, the present application document briefly describes these operations, and please refer to the prior art for the structures of other parts, which is not described herein again.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The method and system for predicting rock drilling response provided by the present invention are described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. A method of predicting rock drilling response, comprising:
acquiring drilling parameters of different mileage of a rock mass, and acquiring a relation model of the drilling parameters and an intermediate variable, wherein the intermediate variable is a new dimensionless parameter obtained by combining the drilling parameters and is used for explaining and evaluating geological conditions;
analyzing the saturated compressive strength of rocks with different mileage of the rock mass to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks;
obtaining rock integrity degrees of different mileage of a rock mass while drilling, and correcting the intermediate variable according to the rock integrity degrees and the drilling parameters;
obtaining the corresponding relation between the drilling parameters and the corrected intermediate variables and the rock saturated compressive strength and the rock integrity degree by soft calculation; and acquiring the corresponding rock saturated compressive strength and the rock integrity degree according to the corresponding relation by using the drilling parameters and the intermediate variables at any position.
2. A method of predicting rock drilling response as set forth in claim 1, wherein obtaining a model of the relationship of the drilling parameters to the intermediate variables comprises:
theoretically deducing to obtain a mathematical model of the drilling parameters and the intermediate variables;
wherein the drilling parameters comprise feeding speed, striking pressure, propelling pressure, revolving pressure, water pressure and water flow;
the intermediate variable at least comprises one of drilling energy, normalized drilling speed ratio and elastic wave reflection coefficient.
3. A method of predicting rock drilling response as set forth in claim 1, wherein analyzing the saturated compressive strengths of the rock at different miles of the rock mass comprises:
drilling and coring to obtain a rock mass, analyzing the rock mass, and dividing and marking the rock mass with different mileage according to the saturated compressive strength of the rock;
the saturated compressive strength of rock includes hard rock, harder rock, softer rock, soft rock and extremely soft rock.
4. The method for predicting rock drilling response of claim 1, wherein obtaining rock integrity levels of different miles of the rock mass while drilling comprises:
drilling the rock mass, acquiring the rock mass fracture condition, and dividing and marking the rock mass with different mileage according to the rock integrity degree;
the degree of rock integrity includes whole rock, more broken rock, and extremely broken rock.
5. The method for predicting rock drilling response as set forth in claim 4, wherein the rock mass fracture condition is obtained in real time by means of borehole photography and physical exploration while drilling the rock mass.
6. The method of predicting rock drilling response of claim 1, wherein modifying the intermediate variable with the degree of rock integrity and the drilling parameter comprises:
and verifying the incidence relation between the intermediate variable and the rock integrity degree according to the rock integrity degree corresponding to each mileage in the drilling process and the corresponding relation between the corresponding drilling parameters, and correcting the intermediate variable according to the incidence relation.
7. The method for predicting rock drilling response of any one of claims 1 to 6, wherein the soft computing obtains the corresponding relation between the drilling parameters and the corrected intermediate variables and the rock saturated compressive strength and the rock integrity degree, and comprises the following steps:
taking the drilling parameters and the corrected intermediate variables as input data, taking the corresponding rock saturated compressive strength and the rock integrity degree as output data, and performing model training by using soft calculation to establish a prediction model from the drilling parameters to the rock saturated compressive strength and the rock integrity degree; the soft computing comprises at least one of a cross validation least square support vector method, a nonlinear multiple regression analysis, an artificial neural network and an adaptive neural fuzzy inference system;
and acquiring the corresponding rock saturated compressive strength and the rock integrity degree through the corresponding relation by using the drilling parameters and the intermediate variables at any position, wherein the acquiring comprises the following steps:
and inputting the drilling parameters and the intermediate variables of any position into the estimation model, and obtaining the rock saturation compressive strength and the rock integrity degree obtained by the estimation model.
8. The method for predicting rock drilling response of claim 7, wherein the model training further comprises, before taking the drilling parameters and the corrected intermediate variables as input data and the corresponding rock saturated compressive strength and the rock integrity degree as output data:
and taking 80% of sample data with the existing corresponding relation as a model training set, and taking 20% of the data with the existing corresponding relation as a model testing set.
9. A system for predicting rock drilling response, comprising:
the data exploration acquisition module is used for acquiring drilling parameters of different mileage of a rock mass;
the theoretical derivation module is used for acquiring a relation model of the drilling parameters and intermediate variables, and the intermediate variables are used for explaining and evaluating geological conditions;
the theoretical analysis module is used for analyzing the saturated compressive strength of rocks with different mileage to obtain the relation between the intermediate variable and the saturated compressive strength of the rocks;
the exploration while drilling module is used for acquiring the rock integrity degree of different mileage of a rock body while drilling and correcting the intermediate variable according to the rock integrity degree and the drilling parameter;
the soft computing module is used for acquiring the corresponding relation among the drilling parameters, the corrected intermediate variables, the rock saturated compressive strength and the rock integrity degree by using soft computing, and is connected with the theoretical analysis module and the exploration while drilling module;
the prediction module is used for acquiring the corresponding rock saturated compressive strength and the rock integrity degree according to the corresponding relation by using the drilling parameters and the intermediate variables at any position; the prediction module is connected with the soft computing module.
10. The system for predicting rock drilling response of claim 9, wherein the exploration-while-drilling module comprises:
the obtaining submodule is used for obtaining the corresponding relation between the rock integrity degree corresponding to the rock of each mileage and the corresponding drilling parameter;
and the verification submodule is used for verifying the incidence relation between the intermediate variable and the rock integrity degree and correcting the intermediate variable through the incidence relation.
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