Uncertainty in surface microseismic monitoring

Abstract

Uncertainty in a migration based approach to surface and near surface microseismic monitoring occurs in two ways: uncertainty in the validity of detected events and uncertainty in the estimated position of the event. Synthetic modeling and comparison to case studies show that sign-to-noise-ratio is a key indicator of both types of the uncertainties. In this paper we present an analysis of both types of uncertainty using synthetic modeling to illustrate the performance characteristics of the migration process in terms of signal detection and false-alarm rates, along with uncertainties in positional estimates. Examples from two case studies will illustrate that this kind of performance is achievable in actual monitoring surveys. Signal-to-noise-ratio (SNR) is a key indicator of the uncertainty in migration based imaging of microseismic events. Reliability, in terms of the ability to detect the complete set of events is a nearly binary function of SNR. Events with SNR above a threshold of 2-3 are readily detected, while events with SNR below the threshold are missed. Positional uncertainties likewise are driven by SNR. While vertical uncertainty is more sensitive to noise, both horizontal and vertical uncertainties decrease rapidly with increasing SNR.