Seismic source inversion method based on micro seismic data and SPSA optimization algorithm

Abstract

The invention relates to a seismic source inversion method based on micro seismic data and an SPSA optimization algorithm. The method comprises the following steps: building a horizontal layered velocity model according to the analysis of logging data and underground rock property data; fast modeling a micro seismic event, adjusting the angle of ray in a dichotomy approach to optimize the ray tracking path, calculating the first-arrival travel time, and then calculating the travel time difference between two adjacent detectors; adding the travel time difference to random perturbation as an observed value; using an SPSA algorithm to calculate the first-arrival travel time difference in the same way based on the location of a micro seismic source obtained through iterative updating, constantly optimizing the location of the seismic source by fitting calculated data and the observed value, and checking the difference between the calculated data and the observed value; if the precision is satisfied or the maximum number of iterations is achieved, stopping updating, outputting a result, and completing positioning; or, continuing next iteration. By calculating out a micro seismic event source rapidly and efficiently, the accuracy of seismic source locating is improved.

Description

technical field [0001] The invention belongs to the field of oil and gas seismic exploration, and in particular relates to a seismic source inversion method based on microseismic data and an SPSA optimization algorithm. Background technique [0002] In the production process of low-permeability oil and gas fields, fracturing technology is an important measure to increase production and injection, and the fractures generated by fracturing (the fracture orientation is closely related to in-situ stress) and fracturing scale are important factors for well pattern deployment. Therefore, in-depth study of fracture azimuth and shape, and timely adjustment of well patterns have always been urgent issues to be solved in oilfields. [0003] Artificial microseismic real-time monitoring and evaluation technology for fracturing wells is a dynamic monitoring technology for oilfield production based on microseismic monitoring technology. Microseismic monitoring is currently the most accur...

AI Technical Summary

Problems solved by technology

[0004] The core issue of data processing in microseismic monitoring is source location, and the most commonly used inversion method based on travel time, such as longitudinal and transverse wave time difference method or homotype wave time difference method, is a conventional method in microseismic source inversion. However, this method needs to solve linear or nonlinear equations, and there may be overdetermined, underdetermined, or ill-conditioned problems in the process of solving the equations. In addition, this method relies heavily on the event time detected by the geophone, and the positioning accuracy cannot meet the requirements.

[0005] There are also various inversion methods commonly used at present, including some gradient algorithms, such as Newton’s method and conjugate gradient method. The selection dependence is large; there are also some random algorithms, such as particle swarm algorithm, genetic algorithm, simulated annealing method, etc., which can solve the problem of local optimal solution well, but the solution speed of this type of algorithm is slow

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