CN115263269A - Method, device, equipment and storage medium for automatically identifying downhole working condition of drilling well - Google Patents
Method, device, equipment and storage medium for automatically identifying downhole working condition of drilling well Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for automatically identifying the underground working condition of a drilling well, wherein the method comprises the following steps: inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model; in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters; and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree. According to the technical scheme, automatic identification of the underground working condition is achieved, the underground working condition judgment types are enriched, the real underground working condition judgment accuracy is improved, the underground complex condition is prevented, and powerful support is provided for realizing intelligent drilling technology and remote technical support.
Description
Technical Field
The embodiment of the invention relates to the petroleum exploration technology, in particular to a method, a device, equipment and a storage medium for automatically identifying the underground working condition of a drilling well.
Background
In the drilling process, near bit engineering parameters such as well deviation, azimuth, temperature, pressure, torque and the like need to be monitored in real time, and near bit stratum parameters (gamma, resistivity, sound waves and the like) need to be measured in real time, and the acquisition of the parameters has very important significance for efficient drilling and safe drilling. In the process of geosteering well drilling, the lithology of the stratum is generally identified through gamma counting, and the position of the current position of the drill bit is positioned, so that the drilling direction of the drill bit is guided, the drill bit penetrates through a producing layer, and the drilling success rate of a highly-deviated well, particularly a horizontal well, is improved. However, the depth of formation lithology identification by gamma counting is limited, and only lithology of the surface formations of the borehole can be distinguished, and formation lithology divisions several meters away and more than ten meters away in front of the drill bit and around the borehole are limited. If the drilling speed is too high, the drill bit breaks through high-pressure strata, karst caves or faults, so that serious drilling accidents such as blowout, well leakage and drilling tool abrasion are caused inevitably, and great loss is brought to oil and gas development.
The development of the acoustic logging while drilling technology enables the acquisition of formation characteristics by using audio information to become a conventional logging means, and the acoustic logging while drilling technology is technically characterized in that the formation lithology is divided by measuring information such as sound velocity, amplitude and the like of a surface formation of a borehole, and the Young modulus and Poisson ratio of the formation are calculated, so that the formation pressure condition is indirectly acquired. However, in practical application, the fact that the speed and amplitude information of the sound waves are only utilized in the drilling engineering is that the natural frequency parameters of the sound waves are rarely mentioned, and it is meaningless to say the propagation speed and amplitude attenuation of the sound waves by any medium or stratum. Therefore, it is not accurate to use parameters of acoustic propagation velocity and amplitude attenuation that are not based on frequency signals to predict and evaluate the type of rock ahead of the drill bit during while drilling.
The existing drilling working condition identification method system can only simply judge a plurality of simple drilling working conditions, but the drilling underground working conditions have instantaneity and variability, when the underground working conditions change or are complex, the ground monitoring system has limited judgment means, the existing technology and the ground sensor system can not effectively identify the complex drilling working conditions such as reaming, overflowing, sticking and the like, so that field personnel are required to judge the on-site underground working conditions through manual experience, the judgment method has hysteresis and uncertainty, the drilling construction risk is increased, the production efficiency is reduced, and the application of remote technical support is not facilitated.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for automatically identifying underground working conditions of drilling, which are used for automatically identifying the underground working conditions so as to enrich the judgment types of the underground working conditions, improve the judgment accuracy of the real underground working conditions, prevent the underground complex conditions and provide powerful support for realizing intelligent drilling technology and remote technical support.
In a first aspect, an embodiment of the present invention provides a method for automatically identifying a downhole condition of a drilling well, including:
inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model;
in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is target characteristic vectors corresponding to the working condition characteristic parameters and the ground parameters;
and calculating the association degree of the target characteristic vector and each standard characteristic vector, and determining the underground working condition according to the standard characteristic vector corresponding to the association degree if any association degree is greater than or equal to the critical association degree.
The embodiment of the invention provides a method for automatically identifying the underground working condition of a drilling well, which comprises the following steps: inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model; in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters; and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree. According to the technical scheme, the working condition characteristic parameters and the characteristic vectors corresponding to the ground parameters are determined by combining the working condition characteristic parameters and the ground parameters, after the correlation degree of the characteristic vectors and the standard characteristic vectors is calculated, if any correlation degree is larger than or equal to the critical correlation degree, the underground working condition corresponding to the standard characteristic vectors corresponding to the correlation degree is determined as the underground working condition corresponding to the working condition characteristic parameters and the ground parameters, the automatic identification of the underground working condition is achieved, the judgment types of the underground working condition are enriched, the judgment accuracy of the real underground working condition is improved, the underground complex condition is prevented, and powerful support is provided for the realization of intelligent drilling technology and remote technical support.
Further, the working condition judgment model is obtained by the following method:
inputting the acquired historical working condition characteristic parameters and the acquired historical ground parameters into a preset model to obtain training characteristic vectors corresponding to the historical working condition characteristic parameters and the historical ground parameters, and determining training underground working conditions according to the training characteristic vectors;
determining historical underground working conditions according to the historical working condition characteristic parameters and historical characteristic vectors corresponding to the historical ground parameters;
if the training underground working condition is not consistent with the historical underground working condition, updating the preset model until the training underground working condition is consistent with the historical underground working condition;
and determining the preset model as the working condition judgment model when the training underground working condition is consistent with the historical underground working condition.
Further, updating the preset model includes:
and modifying the weight of each element in the standard characteristic vector contained in the preset model.
Further, in the working condition judgment model, the underground working condition judgment is performed based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters, and the method includes:
determining the change state of each working condition characteristic parameter;
and determining elements of the target characteristic vector according to the change state of each working condition characteristic parameter.
Further, each standard feature vector corresponds to the determined downhole condition, and accordingly, determining the downhole condition according to the standard feature vector corresponding to the degree of association includes:
determining the standard feature vector corresponding to the relevance;
and determining the underground working condition corresponding to the standard characteristic vector as the underground working condition corresponding to the working condition characteristic parameter and the ground parameter.
Further, the operating condition characteristic parameters comprise: at least one of a near bit weight state, a near bit revolution state, a near bit torque state, an inner annular pressure state, an outer annular pressure state, a transverse vibration state, an axial vibration state, a near bit bending moment state, a downhole temperature state, a well depth state, a bit position state, a hook load state, a bit weight state, a drilling state and a hook height state.
Further, the downhole conditions include: drilling normally, drilling with no pressure, drilling normally, fixed pressure, circulating rotary table opening, single joint connecting, tripping, drilling down, positive reaming, reverse reaming, well collapse, drilling down meeting resistance, tripping meeting clamp, jumping, well leakage, drilling tool puncture leakage, water dropping hole, water plugging hole, drilling tool dropping, sliding drilling, drilling tool cutting measuring upper part, drilling tool cutting measuring lower part, drilling bit later stage, screw rod later stage, overflow, drilling tool clamping pump opening and drilling clamping pump stopping.
In a second aspect, an embodiment of the present invention further provides an automatic identification apparatus for downhole conditions of drilling, including:
the input module is used for inputting the acquired working condition characteristic parameters and the ground parameters into the working condition judgment model as input information;
the judging module is used for judging underground working conditions based on the working condition characteristic parameters and the ground parameters in the working condition judging model, and the obtained output information is target characteristic vectors corresponding to the working condition characteristic parameters and the ground parameters;
and the calculation module is used for calculating the association degree of the target characteristic vector and each standard characteristic vector, and determining the underground working condition according to the standard characteristic vector corresponding to the association degree if any association degree is greater than or equal to the critical association degree.
In a third aspect, the embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for automatically identifying a downhole condition of a drilling well according to any one of the first aspect.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer executable instructions for performing the method for automatically identifying downhole conditions in a well as described in any one of the first aspect when executed by a computer processor.
In a fifth aspect, the present application provides a computer program product comprising computer instructions which, when run on a computer, cause the computer to perform the method for automatically identifying a downhole condition of a well as provided in the first aspect.
It should be noted that all or part of the computer instructions may be stored on the computer readable storage medium. The computer-readable storage medium may be packaged with the processor of the device for automatically identifying the downhole condition of the drilling well, or may be packaged separately from the processor of the device for automatically identifying the downhole condition of the drilling well, which is not limited in this application.
For the description of the second, third, fourth and fifth aspects in this application, reference may be made to the detailed description of the first aspect; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not repeated here.
In the present application, the names of the automatic identification device for downhole conditions of drilling described above do not limit the devices or functional modules themselves, and in practical implementations, the devices or functional modules may be presented by other names. Insofar as the functions of the respective devices or functional modules are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalents.
These and other aspects of the present application will be more readily apparent from the following description.
Drawings
FIG. 1 is a flow chart of a method for automatically identifying downhole conditions of a drilling well according to an embodiment of the present invention;
FIG. 2 is a schematic view of a measuring device for obtaining characteristic parameters of a working condition and ground parameters according to a first embodiment of the present invention;
FIG. 3 is a flow chart of a method for automatically identifying downhole conditions of a drilling well according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of an automatic recognition device for downhole conditions of drilling according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention.
Reference numerals:
1-a ground sensing device, 2-a drill rod, 3-other measuring short sections, 4-a near bit measuring short section and 5-a drill bit.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone.
The terms "first" and "second" and the like in the description and drawings of the present application are used for distinguishing different objects or for distinguishing different processes for the same object, and are not used for describing a specific order of the objects.
Furthermore, the terms "including" and "having," and any variations thereof, as referred to in the description of the present application, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like. In addition, the embodiments and features of the embodiments in the present invention may be combined with each other without conflict.
It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present relevant concepts in a concrete fashion.
In the description of the present application, the meaning of "a plurality" means two or more unless otherwise specified.
Example one
Fig. 1 is a flowchart of a method for automatically identifying a downhole condition of a drilling well according to an embodiment of the present invention, where the present embodiment is applicable to a situation where a downhole condition needs to be accurately determined, and the method may be executed by a downhole condition automatic identification device of a drilling well, as shown in fig. 1, and specifically includes the following steps:
and step 110, inputting the acquired working condition characteristic parameters and the ground parameters into a working condition judgment model as input information.
Specifically, the operating condition characteristic parameters and the ground parameters can be obtained through the measuring device.
Fig. 2 is a schematic diagram of a measuring device used for acquiring operating condition characteristic parameters and ground parameters in the first embodiment of the present invention, and as shown in fig. 2, the measuring device may include a ground sensing device 1, a drill rod 2, and a measuring nipple, where the measuring nipple is used to acquire the operating condition characteristic parameters, and the ground sensing device 1 is used to acquire the ground parameters. The measuring short section can comprise a near-bit measuring short section 4 and other measuring short sections 3, the near-bit measuring short section 4 is installed on the lower portion of the drilling tool assembly and used for measuring working condition characteristic parameters of the bottom of the well, and the other measuring short sections 3 are sequentially arranged along a drill rod. The measuring device may also comprise a drill bit 5. The measuring nipple middle section circumferential position is opened seven circular seal grooves and four rectangular long seal grooves, in seven circular seal grooves, wherein four grooves are used for placing mechanical measuring strain gauge groups, can be accurate measuring the torque, axial force and bending moment that the drilling tool receives, two groove installation annular internal and external pressure sensors are respectively communicated with measuring nipple external ring hole and internal water hole, and are used for measuring the annular liquid column pressure inside and outside the nipple, and a groove is used for placing a preprocessing circuit board for preprocessing a plurality of groups of signals. Circular seal groove and rectangular seal groove adopt the form of apron and supporting sealing washer to realize sealed, and the apron is connected with measurement nipple joint body through the form of countersunk screw, between the different cell bodies, realizes circuit connection through the line hole of crossing of processing in advance. A main control circuit of a measuring system is arranged at one position in rectangular strip sealing grooves of the four measuring short sections, a temperature sensor and an acceleration sensor can be arranged on a chip of the main control circuit and used for measuring the temperature and vibration conditions of the underground drilling tool during working, and a wireless electromagnetic wave communication device is arranged at the other position and used for transmitting signals to a receiving device on the ground in an electromagnetic wave mode for analysis and processing; the remaining two rectangular slots can accommodate batteries and spare parts.
The condition characteristic parameters can comprise at least one of a state of near bit weight, a state of near bit revolution, a state of near bit torque, a state of inner annular pressure, a state of outer annular pressure, a state of transverse vibration, a state of axial vibration, a state of near bit bending moment, a state of downhole temperature, a state of well depth, a state of bit position, a state of hook load, a state of bit weight, a state of drilling time and a state of hook height. Specifically, the value, the mean value and the relative standard deviation of the near bit weight, the value, the mean value and the relative standard deviation of the near bit revolution, the value, the mean value and the relative standard deviation of the near bit torque, the value, the mean value and the relative standard deviation of the inner annulus pressure, the value, the mean value and the relative standard deviation of the outer annulus pressure, the value, the mean value and the relative standard deviation of the lateral vibration, the value, the mean value and the relative standard deviation of the axial vibration, the value, the mean value and the relative standard deviation of the near bit bending moment, the value, the mean value and the relative standard deviation of the downhole temperature, the value, the mean value and the relative standard deviation of the well depth, the value, the mean value and the relative standard deviation of the bit position, the value, the mean value and the relative standard deviation of the hook load, the value, the mean value and the relative standard deviation of the weight of the bit, the mean value and the relative standard deviation of the hook height may be included.
Surface parameters may include downhole temperature and humidity, etc.
And the working condition judgment model is used for determining underground working conditions corresponding to the working condition characteristic parameters and the ground parameters according to the input working condition characteristic parameters and the ground parameters.
In the embodiment of the invention, the underground working condition determined by combining the characteristic parameters of the underground working condition of the well drilling and the ground parameters on the well is more accurate.
And 120, in the working condition judgment model, performing underground working condition judgment based on the working condition characteristic parameters and the ground parameters, wherein the obtained output information is target characteristic vectors corresponding to the working condition characteristic parameters and the ground parameters.
Specifically, after the operating condition characteristic parameters and the ground parameters are input into the operating condition judgment model as input information, the obtained output information is target characteristic vectors corresponding to the operating condition characteristic parameters and the ground parameters.
According to the embodiment of the invention, the corresponding target characteristic vector is automatically determined according to the working condition characteristic parameter and the ground parameter.
Wherein, the downhole operating mode includes: drilling normally, drilling with no pressure, drilling normally, fixed pressure, circulating rotary table opening, single joint connecting, tripping, drilling down, positive reaming, reverse reaming, well collapse, drilling down meeting resistance, tripping meeting clamp, jumping, well leakage, drilling tool puncture leakage, water dropping hole, water plugging hole, drilling tool dropping, sliding drilling, drilling tool cutting measuring upper part, drilling tool cutting measuring lower part, drilling bit later stage, screw rod later stage, overflow, drilling tool clamping pump opening and drilling clamping pump stopping.
Specifically, downhole conditions may be determined based on a grey correlation method. The grey correlation method for determining the underground working conditions is to determine the probability of each underground working condition by calculating the correlation degree of a target characteristic vector and a standard characteristic vector and calculate a target characteristic vector YTAnd the standard feature vector XRThe closer the geometrical shapes of the curve space are, the greater the degree of association between the feature vectors is. In site construction, parameters acquired by a ground sensing device and working condition characteristic parameters uploaded by a measuring short section are combined, underground working conditions are judged by a grey correlation analysis method, different underground working conditions have the change characteristics of various corresponding parameters, the ground and underground parameters have certain signs before the working conditions change and show corresponding signal number characteristics, the grey system theory can effectively analyze and process the information, the mutual relation between the information and the underground working condition states is established, and the underground working conditions can be effectively and automatically identified.
Assuming that the number of types of the working conditions to be identified is m, the standard characteristic vector of each working condition consists of n elements, and the target characteristic vector Y can be determinedT＝[y1 y2 … yn]Standard feature vector
Wherein, XRThe m row vectors in the matrix represent standard eigenvectors of m underground working conditions, and the standard eigenvector of each underground working condition consists of different characteristics of a working condition characteristic parameter and a ground parameter.
Target feature vector Y can be determined based on equation 1TAnd the standard feature vector XRThe minimum absolute error value delta of each corresponding element in theminBased on equation 2, the target feature vector Y can be determinedTAnd the standard feature vector XRThe maximum error value delta of each corresponding element in the tablemaxBased on equation 3, the target feature vector Y can be determinedTAnd each standard feature vector XRCoefficient of degree of association ξijBased on equation 4, the target feature vector Y can be determinedTWith each standard feature vector XRThe degree of association r (i).
Wherein rho is a preset resolution coefficient and satisfies 0< rho.
Determining a target feature vector and each standard feature vector XRAfter the correlation degree is obtained, a correlation degree sequence [ R ] can be obtained]＝[r1，r2，…，rm]When the relevance between the target characteristic vector and a standard characteristic vector exceeds a given critical relevance theta i, the underground working condition corresponding to the standard characteristic vector can be taken as the underground working condition corresponding to the target characteristic vector, and the automatic identification of the underground working condition is realized. Due to different working condition characteristicsThe influence degree of the number on the underground working condition is different, and in order to show the importance of each working condition characteristic parameter, different weight omega can be given to each working condition characteristic parameterjAnd, therefore,
wherein, the sum of the weight values of all the characteristic parameters satisfies
Of course, in the actual application process, since the value ranges of different parameters may be very different, normalization processing needs to be performed on the characteristic parameters of each working condition in the target characteristic vector.
At present, most of working condition analysis and complex condition judgment are mainly finished by manpower, only a plurality of simple working conditions and analysis are automatically judged by a computer, in the process of manual finishing, errors exist in working condition and complex condition judgment due to individual differences, changes of related ground and underground multiple parameters can be caused before and after the change process of each underground working condition, underground automatic identification basis is increased by combining underground near bit measurement parameters and parameters measured by a ground sensor, a gray correlation method is applied to process and analyze related data to form an automatic identification rule, a drilling working condition and complex condition database model is established, logic reasoning and self learning are carried out on the underground working condition, the underground working condition and real underground working condition are corrected, the optimization database model is continuously perfected, the underground working condition automatic identification method is finally formed, automatic prejudgment and early warning are carried out in advance on the underground working condition of drilling, and safe and rapid drilling is realized.
The embodiment of the invention provides a method for automatically identifying the underground working condition of a drilling well, which comprises the following steps: inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model; in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters; and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree. According to the technical scheme, the working condition characteristic parameters and the target characteristic vectors corresponding to the ground parameters are determined by combining the working condition characteristic parameters and the ground parameters, after the correlation degree of the target characteristic vectors and the standard characteristic vectors is calculated, if any correlation degree is larger than or equal to the critical correlation degree, the underground working condition corresponding to the standard characteristic vectors corresponding to the correlation degrees is determined as the underground working condition corresponding to the working condition characteristic parameters and the ground parameters, automatic identification of the underground working condition is achieved, the judgment types of the underground working condition are enriched, the judgment accuracy of the real underground working condition is improved, the underground complex condition is prevented, and powerful support is provided for realizing intelligent drilling technology and remote technical support.
Example two
Fig. 3 is a flowchart of a method for automatically identifying a downhole condition of a drilling well according to a second embodiment of the present invention, which is embodied on the basis of the second embodiment. As shown in fig. 3, in this embodiment, the method may further include:
And step 320, determining historical underground working conditions according to the historical working condition characteristic parameters and historical characteristic vectors corresponding to the historical ground parameters.
And 330, if the training underground working condition is inconsistent with the historical underground working condition, updating the preset model until the training underground working condition is consistent with the historical underground working condition.
In one embodiment, updating the preset model includes: and modifying the weight of each element in the standard feature vector contained in the preset model.
And 340, determining the preset model when the training downhole working condition is consistent with the historical downhole working condition as the working condition judgment model.
In the embodiment of the invention, the determined underground working condition can be more accurate by optimizing the working condition judgment model.
And 350, inputting the acquired working condition characteristic parameters and the ground parameters as input information into a working condition judgment model.
And 360, in the working condition judgment model, carrying out underground working condition judgment based on the working condition characteristic parameters and the ground parameters, wherein the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters.
In one embodiment, step 360 may specifically include:
determining the change state of each working condition characteristic parameter; and determining elements of the target characteristic vector according to the change state of each working condition characteristic parameter.
In the automatic judgment process, a threshold value is set, and when the increase and decrease amount exceeds the threshold value, the parameter is considered to be changed. The increase of the characteristic parameter value of the working condition can be represented by 1, the increase of the mean value of the characteristic parameter of the working condition can be represented by 2, the increase of the relative standard deviation of the characteristic parameter of the working condition can be represented by 3, the decrease of the characteristic parameter value of the working condition can be represented by-1, the decrease of the mean value of the characteristic parameter of the working condition can be represented by-2, the decrease of the relative standard deviation of the characteristic parameter of the working condition can be represented by-3, the no change of the characteristic parameter of the working condition can be represented by 0, and the no characteristic parameter of the working condition can be represented by/. In each standard feature vector, different weight coefficients are given because the importance of each working condition feature parameter is different. When two or more standard characteristic vectors have similar characteristics, a certain weight omega should be given to the distinguishing working condition characteristic parametersj. According to the thought, common standard characteristic vectors and corresponding weight coefficients in the drilling process can be constructed, and the table 1 shows.
The condition characteristic parameter denoted by "/" in table 1 indicates a downhole condition in which the condition characteristic parameter is independent of or ignores the effect of the corresponding downhole condition. In order to highlight the main characteristics of the underground working condition and ignore the secondary characteristics, the weights of the working condition characteristic parameters in the table are set to be 0.
TABLE 1
In order to determine the target characteristic vector, reference values of characteristic parameters of all working conditions in the drilling process must be determined, then the parameters measured in real time within a certain time interval are processed, and values of the characteristic parameters of all the working conditions in the target characteristic vector are extracted. After the standard characteristic vector, the target characteristic vector and the weight of each working condition characteristic parameter are determined, the association degree r (i) of the target characteristic vector and each standard characteristic vector can be calculated.
When r (i) is greater than or equal to the critical correlation rc (i), a downhole condition may be determined. Table 2 shows the criticality of each downhole condition. And if the judged underground working condition is not accordant with the actual condition, correspondingly modifying the weight, repeatedly testing, perfecting a working condition judgment model, and finally realizing automatic judgment of the underground working condition of the drilling.
TABLE 2
In one embodiment, each of the standard feature vectors corresponds to the determined downhole condition, and accordingly, determining the downhole condition according to the standard feature vector corresponding to the degree of association includes:
determining the standard feature vector corresponding to the relevance; and determining the underground working condition corresponding to the standard characteristic vector as the underground working condition corresponding to the working condition characteristic parameter and the ground parameter.
In practical application, the effectiveness of identifying the underground working condition by using the gray correlation analysis method can be verified through simulation experiments, and the accuracy and the resolution of an identification result can be improved by using a method of multiple groups of standard characteristic vectors. The simulation experiment sets five groups of vectors to be measured according to different underground working conditions, working condition characteristic parameters and variation ranges of different characteristics of the ground parameters.
The simulation experiment mainly comprises the following steps: setting standard characteristic vectors and weights of the standard characteristic vectors, wherein four groups of standard vectors are preset for each type of standard characteristic vector, the vectors can be modified and perfected, and new vectors can be added when necessary; setting a target characteristic vector, and carrying out normalization processing on the standard characteristic vector and the target characteristic vector in advance; and respectively calculating five groups of critical association degrees, and selecting the maximum value as an automatic identification basis.
The embodiment of the invention provides a method for automatically identifying the underground working condition of a drilling well, which comprises the following steps: inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model; in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters; and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree. According to the technical scheme, the working condition characteristic parameters and the target characteristic vectors corresponding to the ground parameters are determined by combining the working condition characteristic parameters and the ground parameters, after the correlation degree of the target characteristic vectors and the standard characteristic vectors is calculated, if any correlation degree is larger than or equal to the critical correlation degree, the underground working condition corresponding to the standard characteristic vectors corresponding to the correlation degree is determined as the underground working condition corresponding to the working condition characteristic parameters and the ground parameters, the automatic identification of the underground working condition is realized, the judgment types of the underground working condition are enriched, the judgment accuracy of the real underground working condition is improved, the underground complex condition is prevented, and powerful support is provided for realizing the intelligent drilling technology and the remote technical support.
EXAMPLE III
Fig. 4 is a schematic structural diagram of an automatic recognition device for downhole conditions of drilling provided by a third embodiment of the present invention, and the device can be applied to situations where downhole conditions need to be accurately determined, so as to improve accuracy of determining actual downhole conditions. The apparatus may be implemented by software and/or hardware and is typically integrated in a computer device.
As shown in fig. 4, the apparatus includes:
an input module 410, configured to input the obtained operating condition characteristic parameters and the ground parameters into the operating condition judgment model as input information;
a judging module 420, configured to perform downhole condition judgment based on the condition characteristic parameter and the ground parameter in the condition judgment model, where the obtained output information is a target characteristic vector corresponding to the condition characteristic parameter and the ground parameter;
and the calculating module 430 is configured to calculate the association degrees of the target feature vectors and each standard feature vector, and if any one of the association degrees is greater than or equal to a critical association degree, determine a downhole working condition according to the standard feature vector corresponding to the association degree.
The automatic recognition device for the underground drilling working condition provided by the embodiment inputs the obtained working condition characteristic parameters and the ground parameters serving as input information into a working condition judgment model; in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters; and calculating the association degree of the target characteristic vector and each standard characteristic vector, and determining the underground working condition according to the standard characteristic vector corresponding to the association degree if any association degree is greater than or equal to the critical association degree. According to the technical scheme, the working condition characteristic parameters and the characteristic vectors corresponding to the ground parameters are determined by combining the working condition characteristic parameters and the ground parameters, after the correlation degree of the characteristic vectors and the standard characteristic vectors is calculated, if any correlation degree is larger than or equal to the critical correlation degree, the underground working condition corresponding to the standard characteristic vectors corresponding to the correlation degree is determined as the underground working condition corresponding to the working condition characteristic parameters and the ground parameters, the automatic identification of the underground working condition is achieved, the judgment types of the underground working condition are enriched, the judgment accuracy of the real underground working condition is improved, the underground complex condition is prevented, and powerful support is provided for the realization of intelligent drilling technology and remote technical support.
On the basis of the above embodiment, the apparatus further includes: the working condition judgment module is used for inputting the acquired historical working condition characteristic parameters and the acquired historical ground parameters into a preset model to obtain training characteristic vectors corresponding to the historical working condition characteristic parameters and the historical ground parameters, and determining training underground working conditions according to the training characteristic vectors; determining historical underground working conditions according to the historical working condition characteristic parameters and historical characteristic vectors corresponding to the historical ground parameters; if the training underground working condition is not consistent with the historical underground working condition, updating the preset model until the training underground working condition is consistent with the historical underground working condition; and determining the preset model when the training underground working condition is consistent with the historical underground working condition as the working condition judgment model.
In one embodiment, updating the pre-set model comprises:
and modifying the weight of each element in the standard characteristic vector contained in the preset model.
On the basis of the foregoing embodiment, the determining module 420 is specifically configured to:
determining the change state of each working condition characteristic parameter;
and determining elements of the target characteristic vector according to the change state of each working condition characteristic parameter.
On the basis of the above embodiment, each of the standard feature vectors corresponds to the determined downhole condition, and accordingly, determining the downhole condition according to the standard feature vector corresponding to the degree of association includes:
determining the standard feature vector corresponding to the association degree;
and determining the underground working condition corresponding to the standard characteristic vector as the underground working condition corresponding to the working condition characteristic parameter and the ground parameter.
In one embodiment, the operating condition characteristic parameters include: the method comprises the following steps of (1) a near bit weight state, a near bit revolution state, a near bit torque state, an inner annular pressure state, an outer annular pressure state, a transverse vibration state, an axial vibration state, a near bit bending moment state, a downhole temperature state, a well depth state, a bit position state, a hook load state, a bit weight state, a drilling state and a hook height state.
In one embodiment, the downhole condition comprises: drilling normally, drilling with no pressure, drilling normally, fixed pressure, circulating rotary table opening, single joint connecting, tripping, drilling down, positive reaming, reverse reaming, well collapse, drilling down meeting resistance, tripping meeting clamp, jumping, well leakage, drilling tool puncture leakage, water dropping hole, water plugging hole, drilling tool dropping, sliding drilling, drilling tool cutting measuring upper part, drilling tool cutting measuring lower part, drilling bit later stage, screw rod later stage, overflow, drilling tool jamming pump opening and drilling tool jamming pump stopping.
The automatic identification device for the underground drilling working condition provided by the embodiment of the invention can execute the automatic identification method for the underground drilling working condition provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 5 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary computer device 5 suitable for use in implementing embodiments of the present invention. The computer device 5 shown in fig. 5 is only an example and should not bring any limitation to the function and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer device 5 is in the form of a general purpose computing electronic device. The components of the computer device 5 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The computer device 5 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of embodiments of the invention as described.
The processing unit 16 executes various functional applications and page displays by running programs stored in the system memory 28, for example, implementing the automatic identification method for downhole conditions of drilling provided by the embodiment of the present invention, the method includes:
inputting the obtained working condition characteristic parameters and the ground parameters as input information into a working condition judgment model;
in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters;
and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree.
Of course, those skilled in the art can understand that the processor can also implement the technical solution of the method for automatically identifying the downhole condition of the drilling provided by any embodiment of the present invention.
EXAMPLE five
An embodiment five of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for automatically identifying a downhole condition of a drilling well, for example, the method provided by the embodiment of the present invention includes:
inputting the obtained working condition characteristic parameters and the ground parameters serving as input information into a working condition judgment model;
in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters;
and calculating the association degree of the target characteristic vector and each standard characteristic vector, and determining the underground working condition according to the standard characteristic vector corresponding to the association degree if any association degree is greater than or equal to the critical association degree.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-readable storage medium may be, for example but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or computer device. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It will be understood by those skilled in the art that the modules or steps of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented by program code executable by a computing device, such that it may be stored in a memory device and executed by a computing device, or it may be separately fabricated into various integrated circuit modules, or it may be fabricated by fabricating a plurality of modules or steps thereof into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for automatically identifying downhole conditions of a well drilling is characterized by comprising the following steps:
inputting the obtained working condition characteristic parameters and the ground parameters serving as input information into a working condition judgment model;
in the working condition judgment model, underground working condition judgment is carried out based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters;
and calculating the association degrees of the target characteristic vectors and each standard characteristic vector, and if any association degree is greater than or equal to a critical association degree, determining the underground working condition according to the standard characteristic vector corresponding to the association degree.
2. The method for automatically identifying the downhole condition of the drilling well according to claim 1, wherein the condition judgment model is obtained by the following method:
inputting the acquired historical working condition characteristic parameters and the acquired historical ground parameters into a preset model to obtain training characteristic vectors corresponding to the historical working condition characteristic parameters and the historical ground parameters, and determining training underground working conditions according to the training characteristic vectors;
determining historical underground working conditions according to the historical working condition characteristic parameters and historical characteristic vectors corresponding to the historical ground parameters;
if the training underground working condition is not consistent with the historical underground working condition, updating the preset model until the training underground working condition is consistent with the historical underground working condition;
and determining the preset model when the training underground working condition is consistent with the historical underground working condition as the working condition judgment model.
3. The method of claim 2, wherein updating the pre-set model comprises:
and modifying the weight of each element in the standard characteristic vector contained in the preset model.
4. The method according to claim 1, wherein in the working condition judgment model, the underground working condition judgment is performed based on the working condition characteristic parameters and the ground parameters, and the obtained output information is a target characteristic vector corresponding to the working condition characteristic parameters and the ground parameters, and the method comprises the following steps:
determining the change state of each working condition characteristic parameter;
and determining elements of the target characteristic vector according to the change state of each working condition characteristic parameter.
5. The method of claim 1, wherein each standard feature vector corresponds to the determined downhole condition, and accordingly, the method of automatically identifying downhole conditions according to the standard feature vector corresponding to the degree of association comprises:
determining the standard feature vector corresponding to the relevance;
and determining the underground working condition corresponding to the standard characteristic vector as the underground working condition corresponding to the working condition characteristic parameter and the ground parameter.
6. The method of claim 1, wherein the operating condition characteristic parameters comprise: at least one of a near bit weight state, a near bit revolution state, a near bit torque state, an inner annular pressure state, an outer annular pressure state, a transverse vibration state, an axial vibration state, a near bit bending moment state, a downhole temperature state, a well depth state, a bit position state, a hook load state, a bit weight state, a drilling state and a hook height state.
7. The method of claim 1, wherein the downhole condition comprises: the method comprises the following steps of drilling normally, drilling with no pressure, drilling normally, fixed pressure supporting, circulating rotary disc opening, single joint receiving, tripping, drilling down, positive reaming, reverse reaming, well collapse, drilling down meeting resistance, tripping, jumping, well leakage, drilling tool puncture, water dropping hole, water plugging hole, drilling tool dropping, sliding drilling, drilling tool cutting measurement upper part, drilling tool cutting measurement lower part, drilling bit later stage, screw rod later stage, overflowing, drilling tool clamping pump opening and drilling tool clamping pump stopping.
8. An automatic identification device for downhole conditions of drilling, comprising:
the input module is used for inputting the acquired working condition characteristic parameters and the ground parameters serving as input information into the working condition judgment model;
the judging module is used for judging underground working conditions based on the working condition characteristic parameters and the ground parameters in the working condition judging model, and the obtained output information is target characteristic vectors corresponding to the working condition characteristic parameters and the ground parameters;
and the calculation module is used for calculating the association degree of the target characteristic vector and each standard characteristic vector, and determining the underground working condition according to the standard characteristic vector corresponding to the association degree if any association degree is greater than or equal to the critical association degree.
9. A computer apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method for automatic identification of downhole conditions in a well according to any of claims 1-7.
10. A storage medium containing computer executable instructions for performing the method of automatically identifying downhole conditions of a well according to any one of claims 1 to 7 when executed by a computer processor.
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| CN118032062A (en) * | 2024-04-11 | 2024-05-14 | 克拉玛依市城投油砂矿勘探有限责任公司 | SAGD downhole temperature and pressure monitoring system and method based on artificial intelligence |
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