CN111625916B - Wellbore stability value calculation method and system - Google Patents
Wellbore stability value calculation method and system Download PDFInfo
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Abstract
The invention provides a well wall stability value calculation method which comprises the steps of determining relevant influence parameters affecting a well wall stability value according to historical statistical data, obtaining adjacent well data according to the relevant influence parameters, carrying the adjacent well data into a multiple regression analysis equation to calculate to obtain regression coefficients, collecting actual measurement data of a well to be analyzed according to the relevant influence parameters, and calculating the well wall stability value of the well to be analyzed according to the actual measurement data, the regression coefficients and the multiple regression analysis equation. According to the method, a plurality of associated influence parameters are combined, the well wall stability value is obtained based on a multiple regression algorithm, the associated influence parameters can be correspondingly adjusted according to the on-site situation, and the mobility is good. In addition, the stability state of the well wall can be automatically monitored without manual intervention, and the effect of intelligently monitoring the stability of the well wall is achieved. In addition, factors such as formation lithology and the like are considered, the method is suitable for various formations, the considered factors are comprehensive, and the prediction of the stability of the well wall is more diversified and accurate.
Description
Technical Field
The invention relates to the field of drilling engineering, in particular to a well wall stability value calculation method and system.
Background
In the drilling process, the optimized drilling technology can reduce the drilling cost and construction accidents, and predicting the stability of the well wall is the basis of safe drilling. The problem of well wall stabilization is a very complex problem often encountered in drilling engineering. Prior to drilling, the formation buried in the subsurface receives the combined actions of overburden pressure, maximum horizontal ground stress, minimum horizontal ground stress, and pore pressure, in equilibrium. After the well is opened, the rock in the well is removed, the rock on the well wall loses the original support, and the slurry hydrostatic pressure is used instead, under the new condition, the stress of the well is redistributed, high stress concentration is generated near the well wall, and if the rock strength is not large enough, the phenomenon of unstable well wall occurs.
The existing well wall stability prediction method is various, the considered influence factors are emphasized, most equations are simplified, the prediction accuracy cannot meet the field requirement, few equations are complex in structure and poor in operability even if considered comprehensively, and the practicability is limited to a certain extent.
Therefore, the invention provides a well wall stability value calculation method and a well wall stability value calculation system.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for calculating a stability value of a well wall, the method comprising the following steps:
Determining associated influence parameters influencing the stability value of the well wall according to the historical statistical data, acquiring adjacent well data according to the associated influence parameters, and carrying the adjacent well data into a multiple regression analysis equation to calculate and obtain regression coefficients;
acquiring measured data of the well to be analyzed according to the associated influence parameters;
and calculating the well wall stability value of the well to be analyzed according to the measured data, the regression coefficient and the multiple regression analysis equation.
According to one embodiment of the invention, the associated influencing parameters include a rock drillability factor x 1, a geological strength index x 2, a ground stress factor x 3, a collapse pressure x 4, a fracture pressure x 5, a wellbore size x 6, a differential bottom hole pressure x 7, and a logging data factor x 8.
According to one embodiment of the invention, the multiple regression analysis equation is expressed by the following formula:
y＝β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7+β8x8+ε
Where y represents the borehole wall stability value, β 0、β1、β2、β3、β4、β5、β6、β7 and β 8 represent the regression coefficients, ε represents the random error.
According to an embodiment of the present invention, the step of acquiring the measured data of the well to be analyzed according to the associated influence parameter further comprises the steps of:
And collecting n groups of measured data of the wells to be analyzed according to a preset time interval, wherein n represents a natural number greater than zero.
According to an embodiment of the present invention, the step of calculating the well wall stability value of the well to be analyzed according to the measured data, the regression coefficients and the multiple regression analysis equation further includes the steps of:
calculating a well wall stability value corresponding to each set of measured data in the n sets of measured data according to the multiple regression analysis equation to obtain n sets of well wall stability values;
and calculating the well wall stability value of the well to be analyzed according to the obtained n groups of well wall stability values.
According to one embodiment of the invention, the wall stability value of the well to be analyzed is calculated according to the following formula:
Wherein epsilon 0 represents the wall stability value of the well to be analyzed, y i represents a wall stability value corresponding to the i-th set of measured data (i=1, 2, once again, n).
According to one embodiment of the invention, the method further comprises:
And after the actual measurement data are acquired, carrying out average value and false data processing on the actual measurement data.
According to one embodiment of the invention, the method further comprises:
and comparing the obtained well wall stability value of the well to be analyzed with a preset threshold value, and performing well wall stability early warning after exceeding the preset threshold value.
According to another aspect of the present invention, there is also provided a well wall stability value calculation system, the system comprising:
The regression coefficient module is used for determining associated influence parameters influencing the stability value of the well wall according to the historical statistical data, acquiring adjacent well data according to the associated influence parameters, and carrying the adjacent well data into a multiple regression analysis equation to calculate and obtain a regression coefficient;
the acquisition module is used for acquiring actual measurement data of the well to be analyzed according to the associated influence parameters;
And the calculation module is used for calculating the well wall stability value of the well to be analyzed according to the measured data, the regression coefficient and the multiple regression analysis equation.
According to one embodiment of the invention, the acquisition module comprises:
and the interval acquisition unit is used for acquiring n groups of measured data of the wells to be analyzed according to a preset time interval, wherein n represents a natural number greater than zero.
According to the well wall stability value calculation method, a plurality of associated influence parameters are combined, the well wall stability value is obtained based on a multiple regression algorithm, the associated influence parameters can be correspondingly adjusted according to the on-site situation, and the mobility is good. In addition, the invention can automatically monitor the stability state of the well wall without manual intervention, thereby achieving the effect of intelligently monitoring the stability of the well wall. In addition, the method also considers factors such as formation lithology and the like, is suitable for various formations, has comprehensive consideration factors, and has more diversity and accuracy in predicting the stability of the well wall.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention, without limitation to the invention. In the drawings:
FIG. 1 shows a flow chart of a method of calculating a borehole wall stability value in accordance with one embodiment of the present invention;
FIG. 2 shows a flow chart of a method for calculating a borehole wall stability value in accordance with another embodiment of the invention, and
FIG. 3 shows a block diagram of a borehole wall stability value calculation system in accordance with one embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
FIG. 1 shows a flow chart of a method for calculating a borehole wall stability value in accordance with one embodiment of the present invention.
At present, the stability of the well wall is determined through a traditional mechanism or a three-pressure profile, the considered influencing factors are not comprehensive enough, the stability of the well wall is required to be judged manually according to the three pressures, different stratum have different calculation modes, and a plurality of parameters are difficult to acquire.
As shown in fig. 1, in step S101, associated influence parameters that influence the stability value of the well wall are determined according to the historical statistical data, and adjacent well data are obtained according to the associated influence parameters, and are brought into a multiple regression analysis equation to calculate a regression coefficient.
According to one embodiment of the invention, the associated impact parameters include rock drillability factor x 1, geological strength index x 2, earth stress factor x 3, collapse pressure x 4, fracture pressure x 5, wellbore size x 6, differential well pressure x 7, and logging data factor x 8.
In one embodiment, the multiple regression analysis equation is as follows:
y＝β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7+β8x8+ε
Where y represents the borehole wall stability value, β 0、β1、β2、β3、β4、β5、β6、β7 and β 8 represent regression coefficients, ε represents the random error. And (5) calculating a regression coefficient according to the adjacent well data and the multiple regression analysis equation. Wherein, β 1、β2、β3、β4、β5、β6、β7 and β 8 represent the correlation coefficients of the rock drillability coefficient x 1, the geological strength index x 2, the ground stress coefficient x 3, the collapse pressure x 4, the fracture pressure x 5, the wellbore size x 6, the bottom hole differential pressure x 7, and the logging data coefficient x 8, respectively.
After obtaining the regression coefficient, in step S102, the measured data of the well to be analyzed is acquired according to the associated influence parameters.
According to one embodiment of the invention, the step of collecting measured data may be collecting measured data of n groups of wells to be analyzed according to a preset time interval, where n represents a natural number greater than zero.
Finally, in step S103, a wall stability value of the well to be analyzed is calculated according to the measured data, the regression coefficients and the multiple regression analysis equation.
According to one embodiment of the invention, the stability values of the well wall corresponding to each set of measured data in the n sets of measured data are calculated according to a multiple regression analysis equation, so as to obtain n sets of stability values of the well wall. And then, calculating according to the obtained n groups of well wall stability values to obtain the well wall stability value of the well to be analyzed.
In one embodiment, the formula for calculating the wall stability value of the well to be analyzed is as follows:
Wherein epsilon 0 represents the wall stability value of the well to be analyzed, y i represents a wall stability value corresponding to the i-th set of measured data (i=1, 2, once again, n).
Preferably, after the measured data is collected, the measured data is subjected to average value and false data processing.
In addition, the obtained well wall stability value of the well to be analyzed can be compared with a preset threshold value, and after the well wall stability value exceeds the preset threshold value, well wall stability early warning is carried out.
The well wall stability value calculation method shown in fig. 1 is based on multiple regression, well wall stability prediction is carried out on all well sections in the drilling process, a correlation value representing the well wall stability is obtained, the well wall stability is timely identified in the drilling construction process, countermeasures are taken, and therefore the occurrence of drilling risks is avoided to the greatest extent.
According to the calculation method of the well wall stability value, provided by the invention, the well wall stability value is obtained based on a multiple regression algorithm by combining various influence parameters, the coefficient can be obtained by multiple regression in the field of the eight influence parameters, the on-site application is convenient for the data coefficient which cannot be obtained to be 0, the well wall stability state is automatically monitored without manual intervention, the intelligent monitoring of the well wall stability is achieved, and factors such as formation lithology and the like are taken as influence parameters to be considered, so that the calculation method is suitable for various strata, the consideration factors are comprehensive, and the prediction of the well wall stability is more diversified and accurate.
FIG. 2 shows a flow chart of a method for calculating a borehole wall stability value in accordance with another embodiment of the present invention.
As shown in fig. 2, in step S201, it is determined that the borehole wall stability influencing parameters include logging data, rock drillability coefficient, geological strength index GSI, ground stress coefficient, collapse pressure, fracture pressure, and bottom hole pressure difference. In addition to the seven influencing parameters mentioned above, wellbore size also has an effect on the stability of the wellbore wall.
The process of determining the well wall stability influence parameters can be to carry out arrangement analysis on the data and the data of the well wall instability well, and to carry out statistics on the changes of all the parameters to obtain the well wall stability influence parameters through statistical analysis.
The rock drillability coefficient comprises the influence of rock strength, drill bit type related to drillability, drilling fluid performance and the like on the stability of a well wall, and is acquired for considering the well wall conditions of different stratum lithology.
The geological strength index GSI reflects the comprehensive relation of mechanical parameters such as elastic modulus, poisson ratio, tensile strength, compression strength and the like.
The ground stress coefficient is the ratio of the maximum horizontal ground stress to the minimum horizontal ground stress. The collapse pressure is the value of the collapse pressure.
The burst pressure is the burst pressure value. The wellbore size may be calculated from the wellbore diameter. Differential bottom hole pressure TVD x g p -EMW (PWD)/TVD.
The equivalent mud weight EMW or the while-drilling pressure PWD can be calculated in real time based on well bore configuration, borehole trajectory, drill tool configuration, mud properties, real-time acquisition of drilling process parameters, and the like. Where TVD represents the depth of burial of the rock, g p represents the formation pore pressure gradient, and g p is in g/cm 3.
The real-time logging data coefficients include total pool volume, inlet flow, etc. The coefficient value is only 1 or 2, and is obtained according to the real-time data change of the total pool volume and the inlet flow, the change rule of the data in the well deep section is large in amplitude and small in amplitude and is 1 and 2.
After the influence parameters are determined, in step S202, data samples of logging data, drilling data rock drillability coefficients, geological strength index GSI, earth stress coefficients, collapse pressure, fracture pressure, bottom hole pressure difference, and the like of adjacent wells of the oilfield block are collected. In this step, data information about the influence parameters of adjacent wells in the oilfield block to which the well to be analyzed belongs is acquired.
Then, in step S203, the correlation coefficient is determined from the collected data, i.e., the correlation coefficient beta 1-β8 is determined from the multiple regression algorithm in combination with the region big data.
In this step, the associated parameters are confirmed based on the influence parameters. In general, multiple regression analysis is to substitute known values (influence parameters x 1、x2、…、xm) of variables into a regression equation to obtain an estimated value (predicted value y m) of a dependent variable, so that occurrence and development of a certain phenomenon can be effectively predicted. Assuming a linear relationship between the dependent variable y m and the independent variable x 1、x2、…、xm, the mathematical model is:
yj＝β0+β1x1j+β2x2j+…+βmxmj+εj(j＝1,2,…n)
In one embodiment of the invention, x 1、x2、…、x8 is calculated according to a large amount of data such as drilling parameters, geological stratification, pressure gradient, drill bit characteristics and the like in the logging data according to the adjacent well data, a multiple regression equation is established, and finally a regression coefficient beta 0～β8 and a relevance coefficient beta 1-β8 are obtained.
The multiple regression analysis equation adopted by the invention is as follows:
y＝β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7+β8x8+ε
Where y represents the borehole wall stability value, β 0、β1、β2、β3、β4、β5、β6、β7 and β 8 represent regression coefficients, ε represents the random error. And (5) calculating a regression coefficient according to the adjacent well data and the multiple regression analysis equation. Wherein, β 1、β2、β3、β4、β5、β6、β7 and β 8 represent the correlation coefficients of the rock drillability coefficient x 1, the geological strength index x 2, the ground stress coefficient x 3, the collapse pressure x 4, the fracture pressure x 5, the wellbore size x 6, the bottom hole differential pressure x 7, and the logging data coefficient x 8, respectively.
After the regression coefficient is obtained, in step S204, real-time influence parameters of the key well are collected, and the well wall stability value of the whole well section is analyzed according to the association coefficient and the regional big data. In practical application, the key well is the well to be analyzed, and the measured data of the well to be analyzed can be obtained, wherein the measured data comprises the original data of a plurality of influencing parameters, including logging data, drilling fluid, drilling tool and drill bit data and the like.
In one embodiment, the measured data is obtained by calculating from the 1 st point of starting monitoring, collecting relevant parameters (well depth, torque, inlet flow, outlet flow, total pool volume, weight on bit, hook load, riser pressure, drilling time, rotating speed and the like) from real-time logging data, and obtaining the most original data by utilizing the on-site drilling fluid performance, drilling tool combination, drill bit and the like. And (3) setting a time sequence { x (T i)) in a certain time interval DeltaT, and carrying out average value and false data processing on the input parameters (parameters related to real-time logging data acquisition). According to the time interval delta T, 6 groups of data are collected in total to obtain actual measurement data.
Finally, in step S205, a final well wall stability value is calculated by fusing the calculation results of the above steps.
In one embodiment, for a first set of data, each influencing parameter is calculated to obtain each influencing parameter value x 1、x2、…、x8. And substituting the regression coefficient beta 0～β8. Y 1 is obtained. Y 2 was calculated from the data of group 2, and the average of the first 5 points was calculated after the 5 th point in turn, with the extra large or extra small values removed for these 5 points. Finally, calculating y 6 to obtain y by the following formula 0
In addition, the well wall stability value epsilon 0 to be analyzed can be compared with a well wall stability threshold value (preset threshold value) set manually according to the last obtained well wall stability value epsilon 0, and early warning is performed when the threshold value exceeds the threshold value.
According to the well wall stability value calculation method, experiments and applications are carried out in the drilling construction monitoring project of the key well of a certain oilfield block, the logging data, drilling fluid, drilling tool, drill bit data, rock drillability coefficient, geological strength index GSI, ground stress coefficient, collapse pressure, cracking pressure, EMW and other data samples of the adjacent well of the oilfield block are collected, and the well wall stability coefficient is calculated according to the data of the key well by regression relevance coefficient beta 0～β8 of a multiple regression algorithm. When the monitoring well X drills to 5138 meters, the stability coefficient of the well wall is out of limit, a prompt for the stability of the well wall is given, and a field engineer carries out deep analysis on the condition, so that the occurrence of primary well wall collapse is avoided. The well drilling data of the same block well are adopted for verification, the well wall stability prediction probability is high, the prediction precision reaches 90%, and the established equation can meet the well drilling construction requirement. The method improves the prediction precision of the well wall, has relatively simple calculation process, is easy to obtain the used data, and has important significance for popularization of the safe drilling technology.
FIG. 3 shows a block diagram of a borehole wall stability value calculation system in accordance with one embodiment of the present invention.
As shown in fig. 3, the computing system 300 includes a regression coefficient module 301, an acquisition module 302, and a computing module 303. Wherein the acquisition module 302 comprises an interval acquisition unit 3021.
The regression coefficient module 301 is configured to determine an associated influence parameter that affects a stability value of a well wall according to historical statistical data, obtain adjacent well data according to the associated influence parameter, and take the adjacent well data into a multiple regression analysis equation to calculate a regression coefficient.
The acquisition module 302 is configured to acquire measured data of the well to be analyzed according to the associated influence parameters. The interval acquisition unit 3021 is configured to acquire measured data of n groups of wells to be analyzed according to a preset time interval, where n represents a natural number greater than zero.
The calculation module 303 is configured to calculate a wall stability value of the well to be analyzed according to the measured data, the regression coefficient and the multiple regression analysis equation.
In summary, the well wall stability value calculation method combines a plurality of associated influence parameters, obtains the well wall stability value based on a multiple regression algorithm, and the associated influence parameters can be correspondingly adjusted according to the on-site situation, so that the mobility is good. In addition, the invention can automatically monitor the stability state of the well wall without manual intervention, thereby achieving the effect of intelligently monitoring the stability of the well wall. In addition, the method also considers factors such as formation lithology and the like, is suitable for various formations, has comprehensive consideration factors, and has more diversity and accuracy in predicting the stability of the well wall.
It is to be understood that the disclosed embodiments are not limited to the specific structures, process steps, or materials disclosed herein, but are intended to extend to equivalents of these features as would be understood by one of ordinary skill in the relevant arts. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.
Although the embodiments of the present invention are disclosed above, the embodiments are only used for the convenience of understanding the present invention, and are not intended to limit the present invention. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the appended claims.
Claims (7)
1. The well wall stability value calculating method is characterized by comprising the following steps of:
Determining associated influence parameters affecting a well wall stability value according to historical statistical data, acquiring adjacent well data according to the associated influence parameters, and carrying the adjacent well data into a multiple regression analysis equation to calculate a regression coefficient, wherein the associated influence parameters comprise a rock drillability coefficient x 1, a geological strength index x 2, a ground stress coefficient x 3, a collapse pressure x 4, a fracture pressure x 5, a well bore size x 6, a well bottom pressure difference x 7 and a logging data coefficient x 8, wherein the rock drillability coefficient x 1 comprises rock strength and the influence of a drill bit type and drilling fluid performance related to drillability on well wall stability;
acquiring measured data of the well to be analyzed according to the associated influence parameters;
According to the measured data, the regression coefficients and the multiple regression analysis equation, calculating to obtain a well wall stability value of the well to be analyzed;
Collecting the actual measurement data of n groups of wells to be analyzed according to a preset time interval, wherein n represents a natural number greater than zero;
The step of calculating the well wall stability value of the well to be analyzed according to the measured data, the regression coefficient and the multiple regression analysis equation further comprises the steps of calculating the well wall stability value corresponding to each set of measured data in n sets of measured data according to the multiple regression analysis equation to obtain n sets of well wall stability values, and calculating the well wall stability value of the well to be analyzed according to the n sets of well wall stability values.
2. The method of claim 1, wherein the multiple regression analysis equation is expressed by the following equation:
y＝β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7+β8x8+ε
Where y represents the borehole wall stability value, β 0、β1、β2、β3、β4、β5、β6、β7 and β 8 represent the regression coefficients, ε represents the random error.
3. The method of claim 1, wherein the wall stability value of the well to be analyzed is calculated according to the following formula:
Wherein epsilon 0 represents the well wall stability value of the well to be analyzed, y i represents the well wall stability value corresponding to the i-th set of measured data, i=1, 2.
4. The method of claim 1, further comprising, after collecting the measured data, performing an average and dummy data processing on the measured data.
5. The method of any one of claims 1-4, wherein the method further comprises:
and comparing the obtained well wall stability value of the well to be analyzed with a preset threshold value, and performing well wall stability early warning after exceeding the preset threshold value.
6. A borehole wall stability value calculation system, wherein the method of any one of claims 1-5 is performed, the system comprising:
The regression coefficient module is used for determining associated influence parameters influencing the stability value of the well wall according to the historical statistical data, acquiring adjacent well data according to the associated influence parameters, and carrying the adjacent well data into a multiple regression analysis equation to calculate and obtain a regression coefficient;
the acquisition module is used for acquiring actual measurement data of the well to be analyzed according to the associated influence parameters;
And the calculation module is used for calculating the well wall stability value of the well to be analyzed according to the measured data, the regression coefficient and the multiple regression analysis equation.
7. The system of claim 6, wherein the acquisition module comprises:
and the interval acquisition unit is used for acquiring n groups of measured data of the wells to be analyzed according to a preset time interval, wherein n represents a natural number greater than zero.
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