1. A deep-layer fine optimization method while drilling of drilling speed based on data driving is characterized by comprising the following steps:

step S1: determining the limit time of the drilling speed while drilling optimization processing processDrilling speed acceleration amplitude；

Step S2: determining a unit operation time period or a unit operation footage of the while-drilling data, and establishing a corresponding unit data set while drilling according to the unit operation time period or the unit operation footage;

step S3: and optimizing the drilling rate of the data set established in the step S2 according to a peak interval average value method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling rate optimization.

2. The data-driven deep refinement while drilling optimization method based on penetration rate is characterized in that the unit while drilling data set in the step S2 includes parameters of penetration rate and drilling parameters.

3. The data-driven drilling rate deep-layer while drilling refinement optimization method as claimed in claim 2, wherein the drilling parameters comprise weight on bit, rotation speed, torque, displacement, type of drill bit, axial vibration acceleration, transverse vibration acceleration, circumferential vibration acceleration, drilling fluid density and bottom hole annulus pressure.

4. The data-driven deep-while-drilling refinement optimization method for drilling rate based on data driving as claimed in claim 1, wherein the peak interval average method in step S3 is implemented by the following steps:

step S31: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S32: searching the whole unit drilling speed data set；

Step S33: presetting a drilling rate peak value stage value CT, wherein the value is 70% -95%;

step S34: locking step S32 Rate of penetration datasetDrilling speed of anterior CT, formation of excellenceSelected interval data set of drilling rate peak value；

Step S35: locking the data set in step S34Corresponding drilling parameters, forming an optimized drilling parameter dataset；

Step S36: locking out the drilling parameter dataset in step S35Taking the average value to form the average value data set of the drilling parametersTo collect dataAs an optimal drilling parameter data set, the specific expression is as follows:

wherein the content of the first and second substances,the ith drilling parameter mean data representing a certain set of optimized drilling parameter data sets,(ii) a i is a data point positioning control parameter in the data set; n is the number of the optimal drilling parameter data sets and is dimensionless;

step S37: will be described in detailOptimal drilling parameter dataset in S36Feeding back to a drilling engineer control system;

step S38: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingAnd the optimization process is finished.

5. The data-driven deep-layer refinement optimization while drilling method for drilling rate based on data driving of claim 1, wherein when the drilling parameter optimized in step S3 fails to reach the expected acceleration amplitude, a preset target drilling rate optimization method is used to optimize the data established in step S2 and the drilling rate to obtain the optimized drilling parameter, the drilling parameter is fed back to a drilling engineer control system, and if the optimized drilling parameter can reach the expected acceleration amplitude, the optimization process is terminated and the next drilling rate optimization is continued.

6. The data-driven deep-while-drilling refinement optimization method for the drilling rate is characterized by comprising the following specific implementation steps of:

step S41: presetting drilling speed optimization intervalOptimizing the drilling rate as a target;

step S42: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S43: searching the whole unit drilling speed data set；

Step S44: if the result of drilling speed is foundThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs the optimal drilling parameter, and feeding back to the drilling engineer control system;

step S45: if it is notThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs the optimal drilling parameter, and feeding back to the drilling engineer control system;

step S46: if it is notThen find the drilling speed resultCan not be used as the optimal drilling speed, and the drilling speed data set is continuously searched；

Step S47: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeContinuing to optimize the drilling speed of the next section;

step S48: resetting the drilling rate optimization interval of step S41；

Step S49: repeating the steps S42-S47;

step S410: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeIf so, ending the optimization process and continuing the next section of drilling speed optimization;

step S411: if the optimized running time exceeds the limit time of the preset optimization processing process while drillingAnd the optimization process is finished.

7. The data-driven deep-layer refinement optimization method for drilling rate while drilling based on data driving of claim 1, wherein when the drilling parameter optimized in step S3 fails to reach the expected acceleration amplitude, the data established in step S2 and the drilling rate are optimized by a scattered point refinement drilling rate optimization method to obtain the optimized drilling parameter, the drilling parameter is fed back to a drilling engineer control system, and if the optimized drilling parameter can reach the expected acceleration amplitude, the optimization process is terminated and the next drilling rate optimization is continued.

8. The data-driven deep-while-drilling refinement optimization method for the drilling rate is characterized by comprising the following specific implementation steps of:

step S51: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,i-th well representing a set of drilling parameters while drillingParameter data;

step S52: initializing and setting 3 target drilling speed data；

Step S53: 3 pieces of target drilling speed dataDividing into optimal, medium and worst grade, 3 pieces of target drilling speed data；

Step S54:andas a mean value of；

Step S55: centering valueAnd worst drilling rateThe connecting line between the two is taken as a central line and optimized along the central line;

step S56: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerReflection contrast;

step S57: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerContrast is extended in the opposite direction until greater than；

Step S58: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerAndthe median value is compared until the median value is greater than；

Step S59: if it is not>Step S54, step S55 and step S56, searching for the optimal value of the drilling rate values in step S54, step S55 and step S56;

step S510: taking the drilling parameter corresponding to the optimal drilling rate value in the step S57 as an optimal drilling parameter, and feeding back the optimal drilling parameter to a drilling engineer control system;

step S511: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingOr converging the drilling speed values of the step S54, the step S55 and the step S56 into an average valueThe optimization process is finished;

wherein the content of the first and second substances,，，setting 3 target drilling speed data for initialization, r/min;the optimal rotating speed in the target drilling speed is r/min;the target drilling speed is medium and medium rotating speed, r/min;the worst rotation speed in the target drilling speed is r/min;is composed ofAndthe average value of (1) is recorded as a midpoint value, r/min;and the ith drilling speed data, r/min, represents a certain group of drilling speed data sets while drilling.

Background

During the drilling process, due to the uncertainty of the stratum, the designed drilling parameters can not reach the expected drilling rate at all times, and the drilling parameters need to be optimized in real time according to the change of the stratum properties. At present, a specific energy method is usually used for carrying out parameter real-time optimization on site, and the method is mainly based on a mechanical specific energy theory, and well parameters are adjusted in real time according to the change condition of a mechanical specific energy curve to realize drilling rate optimization. However, in practice the specific energy method has the following two problems: (1) the real-time optimization of drilling parameters by using a specific energy method mainly comprises the steps of qualitatively adjusting parameters according to the change of a specific energy curve of a machine, failing to quantitatively and accurately provide an optimal parameter combination and failing to optimize the drilling speed to the maximum extent; (2) the method for realizing the real-time optimization of the drilling parameters based on the mechanical specific energy theory does not consider the drilling cost and cannot realize the real-time optimization of the comprehensive drilling cost. Although the conventional method for optimizing well parameters based on the drilled well completion data can solve the problems existing in the real-time parameter optimization compared with the energy method, the following problems can occur when the real-time parameter optimization is carried out by using the drilling data:

(1) because the drilling rate model in the traditional drilling parameter optimization method is built according to data regression of a field test after the drilling is stopped, the real-time building of the drilling rate model is very difficult when the drilling data is used for carrying out the real-time optimization of the parameters;

(2) the traditional drilling rate model building is based on the data evaluation after drilling and builds a model according to the measured data after drilling, and the method results in prolonged construction period, can not realize real-time evaluation of a drill bit and increases drilling cost, so that the problem of drilling rate dynamic optimization under the condition of drilling is required to be solved.

Therefore, a low-cost and high-benefit drilling while-drilling rotation speed optimization method needs to be established, the invention discloses a data-driven drilling speed while-drilling optimization method, which comprises the steps of establishing a corresponding unit data set while-drilling according to a unit operation time period or unit operation footage, optimizing the drilling speed while-drilling according to a peak interval average value method or a preset target drilling speed optimization method or a scattered point fine drilling speed optimization method, and stopping the optimization process by controlling the limit time of the drilling speed while-drilling optimization processing process and the drilling speed acceleration amplitude value. Scientific optimization of the rotation speed while drilling is carried out through a large amount of actual data, so that the optimal value of the rotation speed is infinitely close to an ideal value, and the method has a guiding effect on optimizing drilling construction in real time and improving the drilling efficiency.

Disclosure of Invention

In order to realize the technical effects, the following technical scheme is adopted:

the invention aims to overcome the defects of the prior art and provides a deep drilling speed fine optimization method based on data driving, which comprises the steps of establishing a corresponding unit data set while drilling according to a unit operation time period or a unit operation scale, optimizing the drilling speed while drilling according to a peak interval average value method or a preset target drilling speed optimization method or a scattered point fine drilling speed optimization method, and stopping the optimization process by controlling the limiting time of the drilling speed optimization processing process while drilling and a drilling speed acceleration amplitude value. The optimal value of the rotating speed is infinitely close to the ideal value, and the method has a guiding effect on optimizing drilling construction in real time and improving the drilling efficiency.

In order to realize the technical effects, the following technical scheme is adopted:

a drilling speed while drilling deep-layer fine optimization method based on data driving comprises the following steps:

step S1: determining the limit time of the drilling speed while drilling optimization processing processDrilling speed acceleration amplitude；

Step S2: determining a unit operation time period or a unit operation footage of the while-drilling data, and establishing a corresponding unit data set while drilling according to the unit operation time period or the unit operation footage;

step S3: and optimizing the drilling rate of the data set established in the step S2 according to a peak interval average value method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling rate optimization.

The while-drilling unit data set of step S2 includes two types of parameters, namely drilling speed and drilling parameters.

The drilling parameters include weight-on-bit, rotational speed, torque, displacement, bit type, axial (longitudinal) vibration acceleration, lateral vibration acceleration, circumferential (torsional) vibration acceleration, drilling fluid density, and bottom hole annulus pressure.

The step S3 peak interval average method is implemented as follows:

step S31: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S32: searching the whole unit drilling speed data set；

Step S33: presetting a drilling rate peak value stage value CT, wherein the value is 70% -95%;

step S34: locking step S32 Rate of penetration datasetDrilling speed of front CT to form optimized drilling speed peak interval data set；

Step S35: locking the data set in step S34Corresponding drilling parameters, forming an optimized drilling parameter dataset；

Step S36: locking out the drilling parameter dataset in step S35Taking the average value to form the average value data set of the drilling parametersTo collect dataAs an optimal drilling parameter data set, the specific expression is as follows:

wherein the content of the first and second substances,the ith drilling parameter mean data representing a certain set of optimized drilling parameter data sets,(ii) a i is a data point positioning control parameter in the data set; n is the number of the optimal drilling parameter data sets and is dimensionless;

step S37: setting the optimal drilling parameter data set in step S36Feeding back to a drilling engineer control system;

step S38: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingAnd the optimization process is finished.

And if the drilling parameters optimized in the step S3 can not reach the expected acceleration amplitude, optimizing the drilling speed and the data established in the step S2 by adopting a preset target drilling speed optimization method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling speed optimization.

The preset target drilling speed optimization method comprises the following specific implementation steps:

step S41: presetting drilling speed optimization intervalOptimizing the drilling rate as a target;

step S42: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S43: searching the whole unit drilling speed data set；

Step S44: if the result of drilling speed is foundThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs the optimal drilling parameter, and feeding back to the drilling engineer control system;

step S45: if it is notThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs the optimal drilling parameter, and feeding back to the drilling engineer control system;

step S46: if it is notThen find the drilling speed resultCan not be used as the optimal drilling speed, and the drilling speed data set is continuously searched；

Step S47: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeContinuing to optimize the drilling speed of the next section;

step S48: resetting the drilling rate optimization interval of step S41；

Step S49: repeating the steps S42-S47;

step S410: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeThe optimization process ends and continuesOptimizing the drilling speed of the next section;

step S411: if the optimized running time exceeds the limit time of the preset optimization processing process while drillingAnd the optimization process is finished.

And if the drilling parameters optimized in the step S3 can not reach the expected acceleration amplitude, optimizing the drilling speed and the data established in the step S2 by adopting a scattered point refined drilling speed optimization method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling speed optimization.

The scattered point refined drilling speed optimization method comprises the following concrete implementation steps:

step S51: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S52: initializing and setting 3 target drilling speed data；

Step S53: 3 pieces of target drilling speed dataDividing into optimal, medium and worst grade, 3 pieces of target drilling speed data；

Step S54:andas a mean value of；

Step S55: centering valueAnd worst drilling rateThe connecting line between the two is taken as a central line and optimized along the central line;

step S56: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerReflection contrast;

step S57: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerContrast is extended in the opposite direction until greater than；

Step S58: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerAndthe median value is compared until the median value is greater than；

Step S59: if it is not>Step S54, step S55 and step S56, searching for the optimal value of the drilling rate values in step S54, step S55 and step S56;

step S510: taking the drilling parameter corresponding to the optimal drilling rate value in the step S57 as an optimal drilling parameter, and feeding back the optimal drilling parameter to a drilling engineer control system;

step S511: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingOr converging the drilling speed values of the step S54, the step S55 and the step S56 into an average valueThe optimization process is finished;

wherein the content of the first and second substances,，，for the 3 target rates of penetration data set for initialization,for the optimal rotation speed in the target drilling speed,is the medium rotating speed in the target drilling speed,is the worst rotation speed in the target drilling speed,is composed ofAndthe average value of (a), noted as the midpoint value,the ith rate of penetration data representing a set of rate of penetration while drilling data sets.

The invention has the beneficial effects that:

the invention discloses a deep-layer drilling-while-drilling optimization method based on data driving, which comprises the steps of establishing a corresponding single-bit data set while drilling according to a unit operation time period or a unit operation scale, optimizing the drilling speed while drilling according to a peak interval average value method or a preset target drilling speed optimization method or a scattered point refined drilling speed optimization method, and terminating the optimization process by controlling the limit time of the drilling speed optimization processing process while drilling and the drilling speed acceleration amplitude. The optimal value of the rotating speed is infinitely close to the ideal value, and the method has a guiding effect on optimizing drilling construction in real time and improving the drilling efficiency.

Detailed Description

The present invention is further described below, and the scope of protection of the present invention is not limited to the following:

example 1:

a deep-layer fine optimization method while drilling of drilling speed based on data driving is characterized by comprising the following steps:

step S1: determining the limit time of the drilling speed while drilling optimization processing processDrilling speed acceleration amplitude；

Step S2: determining a unit operation time period or a unit operation footage of the while-drilling data, and establishing a corresponding unit data set while drilling according to the unit operation time period or the unit operation footage;

step S3: and optimizing the drilling rate of the data set established in the step S2 according to a peak interval average value method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling rate optimization.

The unit while drilling data set of step S2 includes two types of parameters, namely drilling rate and drilling parameters, and the drilling parameters include weight on bit, rotational speed, torque, displacement, bit type, axial (longitudinal) vibration acceleration, lateral vibration acceleration, circumferential (torsional) vibration acceleration, drilling fluid density, and bottom hole annulus pressure.

Peak interval average method

The step S3 peak interval average method is implemented as follows:

step S31: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S32: searching the whole unit drilling speed data set；

Step S33: presetting a drilling rate peak value stage value CT, wherein the value is 70% -95%;

step S34: locking step S32 Rate of penetration datasetDrilling speed of front CT to form optimized drilling speed peak interval data set；

Step S35: locking the data set in step S34Corresponding drilling parameters, forming an optimized drilling parameter dataset；

Step S36: locking out the drilling parameter dataset in step S35Taking the average value to form the average value data set of the drilling parametersTo collect dataAs an optimal drilling parameter data set, the specific expression is as follows:

wherein the content of the first and second substances,the ith drilling parameter mean data representing a certain set of optimized drilling parameter data sets,(ii) a i is a data point positioning control parameter in the data set; n is the number of the optimal drilling parameter data sets and is dimensionless;

step S37: setting the optimal drilling parameter data set in step S36Feeding back to a drilling engineer control system;

step S38: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingAnd the optimization process is finished.

Method for optimizing preset target drilling speed

And if the drilling parameters optimized in the step S3 can not reach the expected acceleration amplitude, optimizing the drilling speed and the data established in the step S2 by adopting a preset target drilling speed optimization method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling speed optimization.

The preset target drilling speed optimization method comprises the following specific implementation steps:

step S41: presetting drilling speed optimization intervalOptimizing the drilling rate as a target;

step S42: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S43: searching the whole unit drilling speed data set；

Step S44: if the result of drilling speed is foundThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs the optimal drilling parameter, and feeding back to the drilling engineer control system;

step S45: if it is notThen find the result of drilling speedAs the optimal drilling speed, corresponding drilling parameters are setAs an optimized drillWell parameters are fed back to a drilling engineer control system;

step S46: if it is notThen find the drilling speed resultCan not be used as the optimal drilling speed, and the drilling speed data set is continuously searched；

Step S47: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeContinuing to optimize the drilling speed of the next section;

step S48: resetting the drilling rate optimization interval of step S41；

Step S49: repeating the steps S42-S47;

step S410: if the drilling parameters are optimizedCan achieve the expected acceleration amplitudeIf so, ending the optimization process and continuing the next section of drilling speed optimization;

step S411: if the optimized running time exceeds the limit time of the preset optimization processing process while drillingAnd the optimization process is finished.

Scattered point refined drilling speed optimization method

And if the drilling parameters optimized in the step S3 can not reach the expected acceleration amplitude, optimizing the drilling speed and the data established in the step S2 by adopting a scattered point refined drilling speed optimization method to obtain optimized drilling parameters, feeding the drilling parameters back to a drilling engineer control system, and if the optimized drilling parameters can reach the expected acceleration amplitude, terminating the optimization process and continuing the next section of drilling speed optimization.

The scattered point refined drilling speed optimization method comprises the following concrete implementation steps:

step S51: determining a drilling rate data set in a data set of a while-drilling unit according to an operation time period of the while-drilling data unit or a unit operation footageAnd drilling parameter data setThe expression is of the form:

wherein the content of the first and second substances,；；(ii) a i, k and t are positioning control parameters of data points in the data set; n is the number of the data sets of the unit while drilling and is dimensionless; m is the number of drilling parameters and is dimensionless; l is the number of data in the data set of the unit while drilling, and is dimensionless;the ith rate of penetration data representing a set of rate of penetration while drilling data sets,an ith drilling parameter data representing a set of drilling parameters while drilling;

step S52: initializing and setting 3 target drilling speed data；

Step S53: 3 pieces of target drilling speed dataDividing into optimal, medium and worst grade, 3 pieces of target drilling speed data；

Step S54:andas a mean value of；

Step S55: centering valueAnd worst drilling rateThe connecting line between the two is taken as a central line and optimized along the central line;

step S56: other drilling rate valuesRunning along the midpoint line, along the center toWorst drilling rateReflection contrast;

step S57: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerContrast is extended in the opposite direction until greater than；

Step S58: other drilling rate valuesRunning along the midpoint line, worst drilling rate along the centerAndthe median value is compared until the median value is greater than；

Step S59: if it is not>Step S54, step S55 and step S56, searching for the optimal value of the drilling rate values in step S54, step S55 and step S56;

step S510: taking the drilling parameter corresponding to the optimal drilling rate value in the step S57 as an optimal drilling parameter, and feeding back the optimal drilling parameter to a drilling engineer control system;

step S511: if the optimized drilling parameters can reach the expected acceleration amplitudeIf the optimization process is finished, the next drilling speed optimization is continued, and if the optimization operation time exceeds the preset limit time of the optimization processing process while drillingOr converging the drilling speed values of the step S54, the step S55 and the step S56 into an average valueThe optimization process is finished;

wherein the content of the first and second substances,，，for the 3 target rates of penetration data set for initialization,for the optimal rotation speed in the target drilling speed,is the medium rotating speed in the target drilling speed,is the worst rotation speed in the target drilling speed,is composed ofAndthe average value of (a), noted as the midpoint value,the ith rate of penetration data representing a set of rate of penetration while drilling data sets.

The invention discloses a data-driven drilling rate optimization while drilling method, which comprises the steps of establishing a corresponding unit data set while drilling according to a unit operation time period or a unit operation scale, optimizing the drilling rate while drilling according to a peak interval average value method or a preset target drilling rate optimization method or a scattered point refined drilling rate optimization method, and terminating the optimization process by controlling the limit time of the drilling rate optimization while drilling process and the drilling rate acceleration amplitude. The optimal value of the rotating speed is infinitely close to the ideal value, and the method has a guiding effect on optimizing drilling construction in real time and improving the drilling efficiency.

Thus, it will be appreciated by those skilled in the art that while embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications can be made which conform to the principles of the invention, as may be directly determined or derived from the disclosure herein, without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.