An Intuitive Classification Method for Microseismic Events

Abstract

The invention discloses an intuitive microearthquake event classification method. The technical scheme includes: firstly, performing de-noising processing on original observation records and increasing signal-to-noise ratio of the records; finding out possible microearthquake events by a long time window and short time window proportion method; collecting first arrivals of the microearthquake events according to continuity of synthetic shafts, performing arrangement processing on the acquired first arrivals and finally superimposing all the first arrivals of the microearthquake events to display. According to distribution of the superimposed first arrivals, the microearthquake events similar in first arrival forms are defined as the same microearthquake event group, unified selection of parameters in post-processing is facilitated, and the events with the curve forms different from the overall trend are defined as stray events or invalid microearthquake events. The intuitive microearthquake event classification method has the advantages that classification of the microearthquake events is convenient, intuitive and reliable.

Description

Technical field [0001] The invention relates to the field of hydraulic fracturing microseismic monitoring, in particular to an intuitive microseismic event classification method. Background technique [0002] Hydraulic fracturing technology is the main way to improve the recovery rate of unconventional oil and gas reservoirs such as shale oil and gas. Microseismic monitoring is to collect the signals generated by the rock fragmentation caused by hydraulic fracturing and locate the fracture position, thereby guiding the fracturing construction and Evaluation of fracturing results. The existing microseismic data processing program usually picks up the first arrival of the microseismic event and directly locates it, and then divides the microseismic event according to the distribution of the location of the microseismic event. The processing flow has the following problems: First, there is no prior knowledge to classify microseismic events, and the same positioning parameters are u...

AI Technical Summary

Problems solved by technology

The processing flow has the following problems: First, there is no prior knowledge to classify microseismic events, and the same positioning parameters are usually selected in the positioning process, which often affects the positioning accuracy of microseismic events; Earthquake events are located, which will greatly waste computing resources, which is especially evident in the real-time monitoring process

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