CN113128014A - Grey prediction theory-based method for predicting pressure of stratum pore to be drilled in front of drill bit - Google Patents
Grey prediction theory-based method for predicting pressure of stratum pore to be drilled in front of drill bit Download PDFInfo
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Abstract
The invention discloses a method for predicting the pressure of a hole in a stratum to be drilled in front of a drill bit based on a grey prediction theory. According to the scheme, more accurate pore pressure information of a stratum to be drilled in front of a drill bit can be provided for field drilling technicians, dynamic risk evaluation in the drilling operation process can be performed based on the pore pressure prediction result of the stratum to be drilled, and then the drilling construction measures are optimized and adjusted according to the risk evaluation result, so that the drilling technicians are assisted to make a decision quickly and accurately, the drilling risk degree is prevented from further worsening, the operation risk caused by inaccurate knowledge of the pore pressure information is finally reduced, and the aim of reducing the drilling risk or drilling without risk is achieved.
Description
Technical Field
The invention relates to the technical field of deep well drilling, in particular to a method for predicting the pressure of a stratum to be drilled in front of a drill bit based on a grey prediction theory.
Background
The formation pore pressure is basic data reflecting the fluid condition, the rock type and the engineering mechanical property thereof, the geological structure and the like in the formation, and the accurate prediction of the formation pore pressure is an important precondition for ensuring the smooth and safe operation of the drilling from the design to the construction. Therefore, formation pore pressure monitoring and prediction has been an important task in oil and gas drilling. At present, the method for solving the pore pressure of the abnormal stratum is mainly divided into the following categories: pre-drilling pressure prediction, pressure monitoring while drilling, geophysical logging pressure detection and pressure actual measurement. Among them, geophysical logging is a generally accepted important means for accurately predicting the pore pressure of the formation, but this method is a post prediction method that cannot predict the pore pressure of the formation not drilled below the bottom of the well. While the pressure value of the stratum to be drilled in front of the drill bit cannot be predicted by the monitoring while drilling method and the pressure detection method for logging after drilling. The method mainly comprises the steps of calculating the formation pore pressure by using seismic interval velocity data and a relation model of the seismic interval velocity data and the formation pore pressure, wherein the common methods comprise an equivalent depth method, a single-point prediction model, a comprehensive prediction model and the like, pressure monitoring is carried out by using various drilling and logging parameters in the drilling process, the method is widely applied to the actual drilling process of an oil and gas field, and the function of real-time guiding drilling engineering is achieved.
However, the adopted stratum pore pressure pre-drilling prediction method is to predict the stratum pore pressure through seismic data, the underground geological condition is complex, and the information below the well bottom is too little or no useful information is obtained, so that the stratum pore pressure pre-drilling prediction is difficult, and the result predicted by the stratum pore pressure pre-drilling prediction method is inaccurate.
Disclosure of Invention
In view of the above, the embodiment of the present invention provides a method for predicting formation pore pressure in a to-be-drilled stratum in front of a drill bit based on a gray prediction theory, which predicts formation pore pressure in the to-be-drilled area through a formation pore pressure prediction model established based on the gray prediction theory, provides relatively accurate formation pore pressure information of the to-be-drilled stratum at the lower part of the drill bit for field drilling operators, and solves the risk caused by inaccurate knowledge of the formation pore pressure information, so as to achieve the purpose of risk-free drilling.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a method for predicting the pressure of the pore of the stratum to be drilled in front of a drill bit based on the grey prediction theory comprises the following steps:
step 1: acquiring n formation pressures of a drill bit in a preset well depth interval of a target well based on pre-drilling data, and determining an original sequence p corresponding to the n formation pressures(0)；
Step 2: for the original sequence p(0)Is pretreated to obtain p'(0)；
And step 3: to p'(0)Establishing a stratum pore pressure prediction model of the target well based on a grey theory;
and 4, step 4: and predicting the formation pore pressure of the region to be drilled of the target well based on the formation pore pressure prediction model.
Preferably, n formation pressures while drilling of the drill bit in a preset well depth interval of the target well are obtained based on pre-drilling data, and an original sequence p corresponding to the n formation pressures while drilling is determined(0)The method comprises the following steps:
acquiring n formation pressures while drilling of a drill bit in a preset well depth interval of a target well based on pre-drilling data, and sequencing the n formation pressures while drilling in an increasing mode according to the well depth to obtain an original number sequence p(0)＝{p(0)(k)}＝{p(0)(1),p(0)(2),...,p(0)(n)},k＝1,2,...,n.。
Preferably, in the step 2, the original sequence p is processed(0)Pre-treatment to obtain p'(0)The method comprises the following steps:
applying the original sequence p by moving average(0)Pre-treating to obtain a treated original number line p'(0)＝{p'(0)(k)}＝{p'(0)(1),p'(0)(2),...,p'(0)(n)},k＝1,2,...,n.。
Preferably, in step 3, p 'is listed based on the processed original number'(0)And a pre-established grey model to obtain a stratum pore pressure prediction model of the target well, wherein the stratum pore pressure prediction model comprises the following steps: and (3) constructing a gray model GM (1,1), solving a reduction model and carrying out residual error test.
Preferably, said constructing a gray model GM (1,1) comprises:
p 'to the processed original number'(0)Performing first-order accumulation to obtain a generated sequence:
p(1)＝{p(1)(k)},k＝1,2,...,n；
for the number sequence p(1)Carrying out mean value processing to obtain:
z(1)＝{z(1)(k)}＝{z(1)(1),z(1)(2),...,z(1)(n)},k＝1,2,...,n；
wherein z is(1)(k)＝0.5[p(1)(k)+p(1)(k-1)].k＝2,...,n；
Based on pre-established grey differential equations
Calculating a coefficient a and a coefficient b;
substituting the coefficient a and the coefficient b into the gray differential equation, and calculating the original sequence p by using the whitening response function of the gray differential equation(0)An analog value of (d);
determination based on least squares
Preferably, the solving the reduction model includes: to pair
Performing first-order accumulation to generate the original sequence p(0)Analog value of
And obtaining a stratum pore pressure prediction model of the target well.
Preferably, the performing the residual error test includes:
based on a preset residual value delta (k) and a residual relative value epsilon (k), by
Calculating the average precision q;
judging whether the average precision q is smaller than a preset average precision or not;
if the average precision q is not smaller than the preset average precision, entering step 4;
and if the average precision q is smaller than the preset average precision, repeatedly executing the step 2 to the step 3.
Preferably, in the step 4, predicting the formation pore pressure of the region to be drilled of the target well based on the formation pore pressure prediction model includes:
predicting the formation pore pressure of the formation to be drilled in front of the drill bit based on the formation pore pressure prediction model
Preferably, after the step 4 is executed, the method further includes:
removing the formation pore pressure at the first point of the upper part of the drill bit, and calculating the predicted pressure value
Adding the data into an original sequence, and updating the original data of the formation pressure while drilling into
According to the content, the invention discloses a method for predicting the pore pressure of the stratum to be drilled in front of a drill bit based on the grey prediction theory, which comprises the steps of acquiring n formation pressures while drilling of the drill bit in a preset well depth interval of a target well based on pre-drilling data, and determining an original sequence p corresponding to the n formation pressures while drilling(0)(ii) a For the original sequence p(0)Is pretreated to obtain p'(0)(ii) a To p'(0)Establishing a stratum pore pressure prediction model of the target well based on a grey theory; predicting formation pore pressure of an undrilled region of the target well based on the formation pore pressure prediction model. By the method for predicting the pore pressure of the stratum to be drilled in front of the drill bit based on the grey prediction theory, the monitoring result of the pressure while drilling of the stratum drilled in a certain depth range at the upper part of the drill bit position is obtained in a target well and used as initial original data, the original sequence is preprocessed by applying a moving sliding average method, the randomness and the uncertainty of the original sequence are weakened, so that a new sequence which is easier to model is obtained, a differential dynamic equation of a system is built by fitting, the model built according to the new sequence is subjected to reduction generation processing, a stratum pore pressure prediction model is built, the stratum pore pressure model of the area to be drilled is predicted by the built stratum pore pressure prediction model, more accurate stratum pore pressure information of the stratum to be drilled at the lower part of the drill bit is provided for field drilling operators, and dynamic engineering risk assessment can be carried out based on the stratum pore pressure prediction result of the stratum to be drilled, and then, carrying out optimization adjustment on drilling construction measures according to the risk evaluation result, so as to assist drilling operators to quickly and accurately make decisions and prevent the drilling risk degree from being further expanded, and finally reducing the risk caused by inaccurate knowledge of formation pore pressure information so as to achieve the aim of risk-free drilling.
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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 for predicting the pore pressure of a formation to be drilled ahead of a drill bit based on a grey prediction theory according to an embodiment of the present invention;
FIG. 2 is a flow chart for predicting formation pore pressure of a formation to be drilled ahead of a drill bit based on a grey theory according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of predicting formation pore pressure of a formation to be drilled ahead of a drill bit based on a grey theory according to an embodiment of the invention;
FIG. 4 is a schematic diagram of the variation of the XX well acoustic wave time difference while drilling with depth according to the embodiment of the invention;
FIG. 5 is a schematic diagram of the variation of the resistivity while drilling of the XX well with depth according to the embodiment of the invention;
FIG. 6 is a schematic diagram of the variation of formation pressure while drilling of the XX well with depth according to the embodiment of the invention;
FIG. 7 is a flow chart of predicting the pore pressure of the formation to be drilled 10m ahead of the drill bit at a XX well 1750m well depth position according to an embodiment of the invention.
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.
In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The embodiment of the invention provides a method for predicting the pore pressure of a stratum to be drilled in front of a drill bit based on a grey prediction theory, which is shown in figure 1 and is a schematic flow chart for predicting the pore pressure of the stratum to be drilled in front of the embodiment of the application, and the method for predicting the pore pressure of the stratum to be drilled in front of the drill bit based on the grey prediction theory at least comprises the following steps:
step 1: acquiring n formation pressures of a drill bit in a preset well depth interval of a target well based on pre-drilling data, and determining an original sequence p corresponding to the n formation pressures(0)。
In step 1, the pre-drilling data includes logging data such as acoustic wave, density, natural gamma, and the like of the drilled well, test analysis data, and the like.
It should be noted that the preset well depth interval is a drilled section at the upper part of the drill bit during the drilling process of the drill bit, and in the well section, n formation pressures while drilling in the well section are monitored through pre-drilling data.
In order to achieve the purpose, the well depth position of the drill bit is used as an origin, then the formation pressure while drilling of n points is taken upwards at equal intervals, and finally the obtained formation pressure while drilling is arranged into a number series from shallow to deep as an original number series p(0)。
Step 2: for the original sequence p(0)Is pretreated to obtain p'(0)。
In step 2, the preprocessing is to process the original sequence of numbers by a moving average method.
It should be noted that the moving average method is a simple smooth prediction technique, and its basic idea is to sequentially calculate a time-series average value containing a certain number of terms according to time-series data item by item, so as to reflect the long-term trend. Therefore, when the time series numerical value is affected by the periodic variation and the random fluctuation, the fluctuation is large, and the development trend of the event is not easy to display, the influence of the factors can be eliminated by using the moving average method, the development direction and the development trend (namely the trend line) of the event can be displayed, and then the long-term trend of the time series can be analyzed and predicted according to the trend line.
It should be noted that the original sequence p is obtained by moving the moving average(0)Pre-processing to obtain processed original number row p'(0)＝{p'(0)(k)}＝{p'(0)(1),p'(0)(2),...,p'(0)(n)},k＝1,2,...,n.。
Wherein the content of the first and second substances,
and step 3: to p'(0)And establishing a stratum pore pressure prediction model of the target well based on a grey theory.
In step 3, the grey theory is an applied mathematical discipline that studies information to be partially clear, partially unclear and with uncertainty phenomena. The grey system theory was first proposed by professor Duncao of Huazhong university of science and technology in Chinese in 1982, and then has received attention and attention at home and abroad. The 'poor information and small sample system' is the main research content of the grey system theory, and realizes the realization of the real world and the prediction of the future state by processing, mining and utilizing the existing 'poor information' and correctly grasping and describing the evolution rule of the system operation behavior. The gray system theory has been expanded to a plurality of scientific fields such as industry, agriculture, society, economy, energy, geology, petroleum and the like, successfully solves a large number of practical problems in production, life and scientific research, and achieves remarkable results.
P 'is'(0)The stratum pore pressure prediction model of the target well is established based on the grey theory and is a model capable of predicting the stratum pore pressure of the stratum to be drilled of the target well.
In the specific implementation process of step 3, a formation pore pressure prediction model of the target well can be obtained by constructing a gray model GM (1,1), solving a reduction model and performing residual error inspection.
And 4, step 4: and predicting the formation pore pressure of the region to be drilled of the target well based on the formation pore pressure prediction model.
In step 4, the formation pore pressure of the region to be drilled of the target well can be predicted through the formation pore pressure prediction model.
According to the method and the device, n formation pressures while drilling of a drill bit in a preset well depth interval of a target well are obtained based on pre-drilling data, and an original sequence p corresponding to the n formation pressures while drilling is determined(0)(ii) a For the original sequence p(0)Is pretreated to obtain p'(0)(ii) a To p'(0)Establishing a stratum pore pressure prediction model of the target well based on a grey theory; predicting formation pore pressure of an undrilled region of the target well based on the formation pore pressure prediction model. By the method for predicting the pore pressure of the stratum to be drilled in front of the drill bit based on the grey prediction theory, the monitoring result of the pressure while drilling of the stratum drilled in a certain depth range at the upper part of the drill bit position is obtained in a target well and used as initial original data, the original sequence is preprocessed by applying a moving sliding average method, the randomness and the uncertainty of the original sequence are weakened, so that a new sequence which is easier to model is obtained, a differential dynamic equation of a system is built by fitting, the model built according to the new sequence is subjected to reduction generation processing, a stratum pore pressure prediction model is built, the stratum pore pressure model of the area to be drilled is predicted by the built stratum pore pressure prediction model, more accurate stratum pore pressure information of the stratum to be drilled at the lower part of the drill bit is provided for field drilling operators, and dynamic engineering risk assessment can be carried out based on the stratum pore pressure prediction result of the stratum to be drilled, and then, carrying out optimization adjustment on drilling construction measures according to the risk evaluation result, so as to assist drilling operators to quickly and accurately make decisions and prevent the drilling risk degree from being further expanded, and finally reducing the risk caused by inaccurate knowledge of formation pore pressure information so as to achieve the aim of risk-free drilling.
Preferably, in step 3, p 'is listed based on the processed original number'(0)And a pre-established grey model to obtain a stratum pore pressure prediction model of the target well, and the method comprises the following steps:
firstly, a gray model GM (1,1) is constructed, then a reduction model is solved, and finally a residual error test is carried out.
It should be noted that G of the gray model GM (1,1) represents grey (gray), M represents model, GM (1,1) represents a 1-variable model of order 1, and the residual error refers to the difference between the actual observed value and the estimated value (fitted value) in mathematical statistics. "residual" implies important information about the basic assumptions of the model. If the regression model is correct, we can consider the residual as an observed value of the error.
Preferably, said constructing a gray model GM (1,1) comprises:
p 'to the processed original number'(0)Performing first-order accumulation to obtain a generated sequence:
p(1)＝{p(1)(k)},k＝1,2,...,n；
for the number sequence p(1)Carrying out mean value processing to obtain:
z(1)＝{z(1)(k)}＝{z(1)(1),z(1)(2),...,z(1)(n)},k＝1,2,...,n；
wherein z is(1)(k)＝0.5[p(1)(k)+p(1)(k-1)].k＝2,...,n；
Based on pre-established grey differential equations
Calculating a coefficient a and a coefficient b;
substituting the coefficient a and the coefficient b into the gray differential equation, and calculating the original sequence p by using the whitening response function of the gray differential equation(0)An analog value of (d);
determination based on least squares
Preferably, the solving the reduction model includes: to pair
Performing first-order accumulation to generate the original sequence p(0)Analog value of
And obtaining a stratum pore pressure prediction model of the target well.
In the specific implementation process, the first step can be to
Performing first-order accumulation to obtain a reduction model:
let k be 1, 2.. multidot.n-1, the original sequence p 'can be obtained'(0)Analog value of
Preferably, the performing the residual error test includes:
based on a preset residual value delta (k) and a residual relative value epsilon (k), by
Calculating the average precision q;
judging whether the average precision q is smaller than a preset average precision or not;
if the average precision q is not smaller than the preset average precision, entering step 4;
and if the average precision q is smaller than the preset average precision, repeatedly executing the step 2 to the step 3.
In a specific implementation, Δ (k) may be a residual value, ∈ (k) may be a residual relative value, and q may be an average precision:
then
Derived to obtain
If the average precision q is more than or equal to 90%, the number series meets the modeling requirement, and prediction can be carried out; otherwise, repeating the modeling process, and not performing the next step until the average precision q meets the condition.
It should be noted that, through residual error detection of the formation pore pressure prediction model, the accuracy of the prediction model for predicting the formation pore pressure is effectively improved, more accurate pore pressure information of the formation to be drilled in front of a drill bit is provided for field drilling technicians, dynamic risk evaluation of a drilling operation process can be performed based on the prediction result of the formation pore pressure to be drilled, and then optimization and adjustment of drilling construction measures are performed according to the risk evaluation result, so that the drilling technicians are assisted to make a decision quickly and accurately, the drilling risk degree is prevented from further deteriorating, and finally, the operation risk caused by inaccurate knowledge of the pore pressure information is reduced, and the drilling risk or risk-free drilling goal is achieved.
Preferably, in the step 4, predicting the formation pore pressure of the undrilled area of the target well based on the formation pore pressure prediction model includes:
predicting the formation pore pressure of the formation to be drilled in front of the drill bit based on the formation pore pressure prediction model
Preferably, after the step 4 is executed, the method further includes:
removing formation pressure monitoring while drilling data of the first point at the upper part of the drill bit, and predicting the pressure value
Adding the data into the original sequence, and updating the original data of the formation pressure as follows:
it should be noted that the new original sequence p of formation pore pressures may be utilized during drilling of the drill bit in the area to be drilled in the target well*(0)And restarting the stratum pore pressure prediction of the next adjacent point, and re-executing the steps 1 to 4, so that more accurate pore pressure information of the stratum to be drilled in front of the drill bit can be provided for field drilling technicians, dynamic risk evaluation can be performed in the drilling operation process based on the pore pressure prediction result of the stratum to be drilled, and then the optimization and adjustment of drilling construction measures are performed according to the risk evaluation result, so that the drilling technicians are assisted to quickly and accurately make decisions and the drilling risk degree is prevented from further deteriorating, and finally, the operation risk caused by inaccurate knowledge of the pore pressure information is reduced, and the drilling risk or risk-free drilling target is achieved.
According to the method disclosed by the above embodiment, the scheme is further described by combining the specific embodiment as follows:
the invention content is as follows:
the invention provides a method for predicting the pore pressure of a stratum to be drilled in front of a drill bit based on a grey prediction theory, which can provide relatively accurate pore pressure information of the stratum to be drilled at the lower part of the drill bit for field drilling operators, can carry out dynamic engineering risk assessment based on the pressure prediction result of the stratum to be drilled, and then carry out optimization and adjustment of drilling construction measures according to the risk assessment result, thereby assisting the drilling operators to make a decision quickly and accurately and preventing the drilling risk degree from being further expanded, and finally reducing the risk caused by inaccurate knowledge of the pressure information of the stratum to be drilled so as to achieve the aim of risk-free drilling.
The technical scheme is as follows:
firstly, collecting seismic interval velocity processing data, well logging data such as well-drilled sound waves, density and natural gamma rays, test analysis data and the like, and obtaining longitudinal stratum rock mechanical parameters of the area by matching with core testing; comprehensively considering the problems of complexity of geological environment, fuzziness of logging seismic interpretation data, accuracy of a pressure prediction model and the like, and predicting to obtain a formation pore pressure profile;
and then, establishing a stratum pore pressure while-drilling prediction model based on a grey theory, and predicting the stratum pore pressure to be drilled in front of the drill bit according to the while-drilling pressure monitoring result of the drilled section at the upper part of the drill bit. Selecting a drilling pressure monitoring result of a drilled stratum within a certain depth range at the upper part of a drill bit position as initial original data, preprocessing an original sequence by applying a moving sliding average method, weakening the randomness and uncertainty of the original sequence, thus obtaining a new sequence which is easier to model, then constructing a differential dynamic equation of a system by fitting, and carrying out reduction generation processing on a model constructed according to the new sequence, and finally establishing a pressure prediction model.
The method mainly comprises the following steps: (1) constructing an original number sequence; (2) preprocessing an original sequence; (3) constructing a gray model GM (1, 1); (4) solving the reduction model; (5) carrying out residual error inspection; (6) and predicting the formation pore pressure while drilling.
Detailed steps are as follows:
the grey system theory was first proposed by professor Duncao of Huazhong university of science and technology in Chinese in 1982, and then has received attention and attention at home and abroad. The 'poor information and small sample system' is the main research content of the grey system theory, and realizes the realization of the real world and the prediction of the future state by processing, mining and utilizing the existing 'poor information' and correctly grasping and describing the evolution rule of the system operation behavior. The gray system theory has been expanded to a plurality of scientific fields such as industry, agriculture, society, economy, energy, geology, petroleum and the like, successfully solves a large number of practical problems in production, life and scientific research, and achieves remarkable results.
The method establishes a stratum pore pressure while-drilling prediction model based on a grey theory, and predicts the stratum pore pressure to be drilled in front of a drill bit according to the monitoring result of the pressure while-drilling of the drilled section at the upper part of the drill bit. Selecting a drilling pressure monitoring result of a drilled stratum within a certain depth range at the upper part of a drill bit position as initial original data, preprocessing an original sequence by applying a moving sliding average method, weakening the randomness and uncertainty of the original sequence, thus obtaining a new sequence which is easier to model, then constructing a differential dynamic equation of a system by fitting, and carrying out reduction generation processing on a model constructed according to the new sequence, and finally establishing a pressure prediction model. The method comprises the following steps:
(1) constructing an original sequence of numbers
Taking the well depth position of a drill bit as an origin, taking the formation pressure monitoring while drilling values of n points at equal intervals upwards, and arranging the formation pressure monitoring while drilling values into a sequence from shallow to deep as original data:
p(0)＝{p(0)(k)}＝{p(0)(1),p(0)(2),...,p(0)(n)},k＝1,2,...,n. (1)
(2) preprocessing raw sequence
Preprocessing the raw sequence by applying a moving average method:
p'(0)＝{p'(0)(k)}＝{p'(0)(1),p'(0)(2),...,p'(0)(n)},k＝1,2,...,n. (2)
(3) construction of Gray model GM (1,1)
For a given p'(0)1-AGO (first order accumulation) to obtain a generation sequence p(1)＝{p(1)(k) 1,2, n. wherein:
for new generation of sequence p(1)Performing an averaging process to obtain z(1)＝{z(1)(k)}＝{z(1)(1),z(1)(2),...,z(1)(n)},k＝1,2,...,n.。
Wherein z is(1)(k)＝0.5[p(1)(k)+p(1)(k-1)].k＝2,...,n.
Establishing a gray differential equation:
using the gray differential equation, the coefficients a, b are calculated:
p(1)(k)＝az(1)(k)＝b (5)
substituting the coefficients into a gray differential equation, and calculating the analog value of the original sequence by using the whitening response function of the equation; solving the equation according to the least squares method, the solution being:
(4) solving reduction model
To pair
Obtaining a reduction model by taking 1-IAGO:
when k ═ 1, 2., n-1, the original sequence p 'can be obtained'(0)Analog value of
(5) Performing residual error test
Let Δ (k) be the residual value, ε (k) be the residual relative value, q be the average precision:
if the average precision q is more than or equal to 90 percent, the number series can meet the modeling requirement, and prediction can be carried out; otherwise, repeating the steps (1) to (5) until the conditions are met, and then carrying out the next step.
(6) Formation pore pressure while drilling prediction
And after the precision meets the requirement, predicting the pressure of the stratum pore to be drilled in front of the drill bit:
removing the pore pressure monitoring while drilling data of the first point at the uppermost part, and predicting the pressure value
Adding the data into the original sequence, and updating the original data of the formation pore pressure as follows:
using the new original sequence of formation pore pressures p*(0)And restarting the formation pore pressure prediction of the next adjacent point, and the steps are the same. The flow chart of the pore pressure prediction of the formation in front of the bit based on the grey theory is shown in the figures 2 and 3.
Example (c):
the XX well is taken as an example to carry out example calculation and result analysis. XX well pre-drilling pressure prediction results show: the pressure coefficient before 1500m fluctuates between 1.0 and 1.2, and belongs to a normal hydrostatic pressure system; from below 1500m, the pressure rises gradually, and the on-site safety of the drilled well is seriously influenced by the existence of abnormal high pressure, so that the pressure monitoring while drilling is carried out in a well section with the drilling depth of 1500m, as shown in figures 4, 5 and 6. Assuming that the position of the drill bit is 1750m, firstly, the formation pore pressure of a well section of 1700 m-1749 m at the upper part of the drill bit is calculated according to logging-while-drilling data and is used as an original sequence, and the gray prediction method established by the invention is used for predicting the formation pore pressure of a well section of 1750m-1759m of the formation to be drilled in front of the drill bit. The specific steps are shown in fig. 7.
First, 1700m to 1749m formation pore pressure monitor while drilling data are selected as an original sequence, as shown in table 1. Let the raw data sequence of formation pore pressure be:
P(0)＝{p(0)(k)}＝{p(0)(1),p(0)(2),...,p(0)(50)},k＝1,2,...,50.
let sequence z(1)＝{z(1)(k)}＝{z(1)(1),z(1)(2),...,z(1)(50) 1,2, 50, is the immediately adjacent generation sequence of P, where z is(1)(k)＝0.5[p(1)(k)+p(1)(k-1)].k＝2,...,50.。
Table 1: XX well 1700m to 1749m formation pore pressure while drilling monitoring data
A formation pore pressure while-drilling prediction model is established by 50 groups of formation pressure while-drilling monitoring data sequences under the matching use of gray system theoretical modeling software (GTMS3.0) and MATLAB software. The first order close proximity mean generation sequence was performed using grey system theoretical modeling software and the results are shown in table 2.
Table 2: first order close-proximity mean generation sequence for formation pore pressure
And substituting the first-order adjacent generated sequence into a smooth sequence judgment condition to meet the smooth sequence condition. The original data sequence was first order accumulated to yield (1-AGO), the results of which are shown in Table 3.
Table 3: first order additive generation sequence of formation pore pressure
As can be seen from table 3: the first order cumulative generation sequence of formation pore pressure is a non-negative increasing sequence and has better smoothness. According to the two steps, the original data sequence of the formation pore pressure can be judged to have a better smoothness ratio, so that the modeling prediction can be carried out by replacing gray system theoretical modeling software and combining MATLAB software.
Step 1: and initializing original formation pore pressure data, and listing a formation pore pressure original data sequence.
Step 2: the 1-AGO sequence of the original data sequence was generated as shown in Table 3.
And 3, step 3: 1-AGO immediately adjacent to the mean generating sequence, as shown in Table 4.
And 4, step 4: calculating the model coefficient: the developing coefficient a is 0.0003 and the gray effect amount b is 1.4672.
And 5, step 5: the system characteristic data sequence simulation value calculation results are shown in table 5.
And 6, step 6: calculating residual error, wherein the residual error is 0.0028; and the relative average error of the formation pore pressure prediction model is as follows:
therefore, the model accuracy is ideal.
And 7, step 7: and (3) predicting the formation pore pressure of the future ten steps (the front part of the drill bit is not drilled for 1750m-1759m) according to the established model and comparing the predicted formation pore pressure with the formation pressure monitoring results while drilling, wherein the results are shown in the table 6.
Table 4: sequence of close-proximity mean generation of formation pore pressure
Table 5: simulated value of formation pore pressure
| Serial number | Analog value | Serial number | Analog value | Serial number | Analog value | Serial number | Analog value | Serial | Analog value | |
| 1 | 1.443232 | 11 | 1.463266 | 21 | 1.45956 | 31 | 1.455864 | 41 | 1.452178 | |
| 2 | 1.466609 | 12 | 1.462895 | 22 | 1.45919 | 32 | 1.455495 | 42 | 1.451809 | |
| 3 | 1.466237 | 13 | 1.462524 | 23 | 1.458821 | 33 | 1.455126 | 43 | 1.451441 | |
| 4 | 1.465865 | 14 | 1.462153 | 24 | 1.45845 | 34 | 1.454758 | 44 | 1.451074 | |
| 5 | 1.465493 | 15 | 1.461782 | 25 | 1.458081 | 35 | 1.454388 | 45 | 1.450705 | |
| 6 | 1.465123 | 16 | 1.461412 | 26 | 1.457711 | 36 | 1.45402 | 46 | 1.450338 | |
| 7 | 1.46475 | 17 | 1.461042 | 27 | 1.457342 | 37 | 1.453651 | 47 | 1.44997 | |
| 8 | 1.464379 | 18 | 1.460671 | 28 | 1.456972 | 38 | 1.453282 | 48 | 1.449602 | |
| 9 | 1.464008 | 19 | 1.4603 | 29 | 1.456602 | 39 | 1.452914 | 49 | 1.449235 | |
| 10 | 1.463637 | 20 | 1.459931 | 30 | 1.456234 | 40 | 1.452546 | 50 | 1.448867 |
Table 6: error between predicted value and monitored value of formation pore pressure
And (3) comparing a stratum pore pressure prediction result obtained by calculation of a 1750-1759 m well section based on a grey theory with a stratum pore pressure while-drilling monitoring result to find that: the maximum relative error is 3.408%, and the average relative error is 3.038%; the model is high in precision, the stratum pore pressure in 10m below the drill bit can be accurately predicted, and the requirements of site drilling construction can be met.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A method for predicting the pressure of a pore in an earth formation to be drilled in front of a drill bit based on a grey prediction theory is characterized by comprising the following steps:
step 1: acquiring n formation pressures of a drill bit in a preset well depth interval of a target well based on pre-drilling data, and determining an original sequence p corresponding to the n formation pressures(0)；
Step 2: for the original sequence p(0)Is pretreated to obtain p'(0)；
And step 3: to p'(0)Establishing a stratum pore pressure prediction model of the target well based on a grey theory;
and 4, step 4: and predicting the formation pore pressure of the region to be drilled of the target well based on the formation pore pressure prediction model.
2. The method as claimed in claim 1, wherein in step 1, n formation-while-drilling pressures of the drill bit in a preset well depth interval of the target well are obtained based on pre-drilling data, and an original sequence p corresponding to the n formation-while-drilling pressures is determined(0)The method comprises the following steps:
acquiring n formation pressures while drilling of a drill bit in a preset well depth interval of a target well based on pre-drilling data, and sequencing the n formation pressures while drilling in an increasing mode according to the well depth to obtain an original number sequence p(0)＝{p(0)(k)}＝{p(0)(1),p(0)(2),...,p(0)(n)},k＝1,2,...,n.。
3. Method according to claim 1, characterized in that in step 2, the original sequence of numbers p is compared(0)Pre-treatment to obtain p'(0)The method comprises the following steps:
applying the original sequence p by moving average(0)Pre-treating to obtain a treated original number line p'(0)＝{p'(0)(k)}＝{p'(0)(1),p'(0)(2),...,p'(0)(n)},k＝1,2,...,n.。
4. Method according to claim 1, characterized in that in step 3, based on said processed raw sequence p'(0)And a pre-established grey model to obtain a stratum pore pressure prediction model of the target well, wherein the stratum pore pressure prediction model comprises the following steps: and (3) constructing a gray model GM (1,1), solving a reduction model and carrying out residual error test.
5. The method according to claim 4, wherein the constructing a gray model GM (1,1) comprises:
p 'to the processed original number'(0)Performing first-order accumulation to obtain a generated sequence:
p(1)＝{p(1)(k)},k＝1,2,...,n；
for the number sequence p(1)Carrying out mean value processing to obtain:
z(1)＝{z(1)(k)}＝{z(1)(1),z(1)(2),...,z(1)(n)},k＝1,2,...,n；
wherein z is(1)(k)＝0.5[p(1)(k)+p(1)(k-1)].k＝2,...,n；
Based on pre-established grey differential equations
Calculating a coefficient a and a coefficient b;
substituting the coefficient a and the coefficient b into the gray differential equation, and calculating the original sequence p by using the whitening response function of the gray differential equation(0)An analog value of (d);
determination based on least squares
6. The method of claim 5, wherein solving the reduction model comprises: to pair
Performing first-order accumulation to generate the original sequence p(0)Analog value of
And obtaining a stratum pore pressure prediction model of the target well.
7. The method of claim 6, wherein performing a residual check comprises:
based on a preset residual value delta (k) and a residual relative value epsilon (k), by
Calculating the average precision q;
judging whether the average precision q is smaller than a preset average precision or not;
if the average precision q is not smaller than the preset average precision, entering step 4;
and if the average precision q is smaller than the preset average precision, repeatedly executing the step 2 to the step 3.
8. The method of claim 1, wherein in step 4, predicting the formation pore pressure of the region to be drilled of the target well based on the formation pore pressure prediction model comprises:
predicting the formation pore pressure of the formation to be drilled in front of the drill bit based on the formation pore pressure prediction model
9. The method of claim 8, further comprising, after step 4:
removing the formation pore pressure at the first point of the upper part of the drill bit, and calculating the predicted pressure value
Adding the data into an original sequence, and updating the original data of the formation pressure while drilling into
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