CN-121995475-A - Identification method, device and equipment for controllable earthquake focus earth parameters

CN121995475ACN 121995475 ACN121995475 ACN 121995475ACN-121995475-A

Abstract

The invention relates to the technical field of production and manufacture and discloses a method, a device and equipment for identifying the ground parameters of a controllable seismic source, wherein the method comprises the steps of obtaining a function model established based on system parameters of a controllable seismic source system; the method comprises the steps of determining a parameter vector to be identified by utilizing least square based on a function model through an exponential window function, carrying out process parameter solving of the parameter vector based on the acquired heavy hammer acceleration and the flat plate acceleration, determining a parameter vector at the current moment, and identifying a geodetic damping coefficient and a geodetic elastic coefficient based on the parameter vector at the current moment. According to the scheme, on the basis of a function model, the exponential window function is introduced, so that the forgetting factor adapting to time variation is increased for least square, and therefore the system condition at the current moment can be accurately reflected by the process parameters solved through the heavy hammer acceleration and the flat plate acceleration, the time variation of data is reflected, and the accuracy of subsequent data identification is guaranteed.

Inventors

FAN HUIWEN
WU YONGSHENG
ZHANG YAMEI
DANG WEIZHONG
WU DI
LUAN HONG

Assignees

中国石油天然气集团有限公司
中国石油集团东方地球物理勘探有限责任公司

Dates

Publication Date: 20260508
Application Date: 20241104

Claims (10)

1. A method for identifying a vibroseis earth parameter, the method comprising: Acquiring a function model established based on system parameters of a controllable seismic source system; Based on the function model, determining a parameter vector to be identified by utilizing least square through an exponential window function; based on the acquired heavy hammer acceleration and the plate acceleration, carrying out process parameter solving of the parameter vector, and determining the parameter vector at the current moment; and identifying the geodetic damping coefficient and the geodetic elastic coefficient based on the parameter vector at the current moment.
2. The method of claim 1, wherein determining the parameter vector to be identified by least squares through an exponential window function based on the function model comprises: Converting the function model into a differential equation by using bilinear dispersion; based on the difference equation, determining least square iteration by using least square; and determining a parameter vector to be identified by introducing an exponential window function based on the least square iteration.
3. The method of claim 1, wherein the performing a process parameter solution for the parameter vector based on the acquired weight acceleration and plate acceleration, determining the parameter vector for the current time, comprises: determining a first initial value of the parameter vector, a second initial value of the covariance matrix, a measurement vector and a measurement transfer matrix based on the acquired heavy hammer acceleration and the acquired plate acceleration; And determining the parameter vector at the current moment based on the first initial value, the second initial value, the measurement vector and the measurement transfer matrix.
4. A method according to claim 3, wherein said determining said parameter vector for the current time based on said first initial value, said second initial value, said measurement vector and said measurement transfer matrix comprises: Determining an identification error corresponding to the current moment based on the first initial value, the measurement vector and the measurement transfer matrix; determining a forgetting factor corresponding to the exponential window function based on the identification error; Determining a gain matrix based on the forgetting factor and the second initial value; and determining the parameter vector at the current moment based on the gain matrix and the forgetting factor.
5. The method of claim 4, wherein the determining a forgetting factor corresponding to the exponential window function based on the recognition error comprises: Determining a calculation formula of the forgetting factor based on an exponential window function; and determining the forgetting factor by using the calculation formula based on a preset forgetting factor minimum value, an error gain and the identification error.
6. The method according to claim 4, further comprising: determining the covariance matrix at the current moment by utilizing the parameter vector based on the forgetting factor and the second initial value; and respectively updating the first initial value and the second initial value of the next moment based on the parameter vector of the current moment and the covariance matrix of the current moment.
7. The method of claim 3, wherein determining the first initial value of the parameter vector, the second initial value of the covariance matrix, the measurement vector, and the measurement transfer matrix based on the acquired weight acceleration and plate acceleration comprises: based on pre-acquired heavy hammer acceleration and plate acceleration, determining a first initial value of the parameter vector and a second initial value of a covariance matrix by utilizing batch least square; and determining a measurement vector and a measurement transfer matrix based on the values of the weight acceleration, the plate acceleration and the corresponding acquisition periods acquired in real time.
8. The method of claim 1, wherein the identifying the geodetic damping coefficient from the geodetic elastic coefficient based on the parameter vector at the current time comprises: based on the parameter vector at the current moment, the geodetic damping coefficient and the geodetic elastic coefficient are identified by using the following expression: Wherein S p represents a plate area, G v represents a geodetic damping coefficient, G s represents a geodetic elastic coefficient, M g represents an equivalent geodetic mass, M p represents a plate mass, a represents an equivalent geodetic damping coefficient, b represents an equivalent geodetic elastic coefficient, a 1 、a 2 represents a parameter to be identified, and T represents a discrete sampling interval.
9. An apparatus for identifying a vibroseis earth parameter, the apparatus comprising: The function model building module is used for obtaining a function model built based on system parameters of the controllable seismic source system; The parameter vector determining module is used for determining a parameter vector to be identified by utilizing least square through an exponential window function based on the function model; The parameter vector solving module is used for carrying out process parameter solving of the parameter vector based on the acquired heavy hammer acceleration and the acquired flat plate acceleration, and determining the parameter vector at the current moment; and the system identification module is used for identifying the geodetic damping coefficient and the geodetic elastic coefficient based on the parameter vector at the current moment.
10. A computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the method of identifying a vibroseis earth parameter as claimed in any one of claims 1 to 8.

Description

Identification method, device and equipment for controllable earthquake focus earth parameters Technical Field The invention relates to the technical field of controllable seismic sources, in particular to a method, a device and equipment for identifying the ground parameters of a controllable seismic source. Background In the petroleum geological exploration process, in order to realize accurate control on the vibration output behavior of the controllable vibration source, the geodetic damping coefficient and the geodetic elastic coefficient of the controllable vibration source coupled with the ground are needed to be utilized. The physical process of coupling the source to earth is complex and therefore time-varying and nonlinear, and it is difficult to obtain parameters of the model by theoretical analysis. Although a mechanism method is applied to establish a relatively accurate model of the change of the earth damping and the elastic coefficient along with the vibration frequency at present, the model is only suitable for a simple frequency sweeping vibration mode. In addition, the ground environment has diversity, for example, the type of the ground where the current seismic source is located may be cement ground, sand ground or marsh ground, etc., the vibration frequency also has time-varying diversity, for example, in a linear sweep mode, the vibration frequency linearly changes with time, in a logarithmic sweep mode, the vibration frequency changes in a logarithmic function form with time, etc., and meanwhile, the working mode of the seismic source may also change, for example, the seismic source may work in a pseudo-random or pulse vibration mode, and the vibration frequency does not have an explicit relation with time change, thus limiting the application of a mechanism accurate model. For the various reasons mentioned above, the earth damping coefficient and the earth equivalent spring coefficient will change over time, and no explicit function is available to describe this relationship. Therefore, in order to enhance the adaptability of the system for the vibration effect of the controllable vibration source, the damping and elastic coefficient of the controllable vibration source coupled with the ground needs to be identified on line and corrected in real time. Under the condition that the model structure is known, the parameter identification determines model parameters through collected data, and a controllable source and earth coupling model is constructed, so that the most common method at present is a least square method identification theory, and the controllable source and earth coupling model parameters can be identified by utilizing the theory. The recursive least square method is an identification method which is easy to understand and master, is simple to realize, and can give out parameter identification results with accurate statistical characteristics under most conditions. In parameter identification, the recursive least square method is an algorithm with infinite memory length, and for a controllable seismic source and earth coupling system, the least square method has the characteristic that old data are more and more in the recursive operation process, so that a recursive result cannot well reflect new data. Therefore, achieving a solution that is time-varying and has good recognition is a challenge. Disclosure of Invention In view of the above, the present invention provides a method, apparatus and device for identifying the geodetic parameters of a controllable seismic source, so as to solve the technical problems that the related art cannot adapt to time-varying and the geodetic damping coefficient and the geodetic elastic coefficient cannot be accurately identified. The invention provides a method for identifying the geodetic parameters of a controllable seismic source, which comprises the steps of obtaining a function model established based on system parameters of a controllable seismic source system, determining a parameter vector to be identified by least square based on the function model through an exponential window function, solving process parameters of the parameter vector based on acquired heavy hammer acceleration and flat plate acceleration, determining a parameter vector at the current moment, and identifying a geodetic damping coefficient and a geodetic elastic coefficient based on the parameter vector at the current moment. With reference to the first aspect, in one possible implementation manner of the first aspect, determining the parameter vector to be identified by using the least square through the exponential window function includes converting a function model into a differential equation by using bilinear dispersion, determining a least square iteration type by using the least square based on the differential equation, and determining the parameter vector to be identified by introducing the exponential window function based on the least square iter