Analysis Methods to Identify the Instrument Response Function (IRF) for Deconvolution
Award last edited on: 1/5/2023

Sponsored Program
Awarding Agency
Total Award Amount
Award Phase
Solicitation Topic Code
Principal Investigator
Jacob Haldorsen

Company Information

MagiQ Technologies Inc

11 Ward Street Suite 300
Somerville, MA 02143
   (617) 661-8300
Location: Multiple
Congr. District: 07
County: Middlesex

Phase I

Contract Number: DE-SC0021824
Start Date: 6/28/2021    Completed: 3/27/2022
Phase I year
Phase I Amount
As part of the process when oil and gas leases are opened for bids, or otherwise sold, interesting bidders/purchasers are given access to a “data room” with access to key accumulated data for the lease. These data may be quite varied in age or quality. Legacy recordings of seismic or infrasonic/acoustic events, are tainted by the system used to acquire the data. It is necessary to remove the response function for the data acquisition system from the data in order to use the data with modern processing technology to make images of the subsurface. In many cases, the instrument response is not known. We propose a processing sequence for legacy seismic data where we remove the Instrument Response Function together with the signature of the seismic source, when the data are generated as a result of a surface-seismic survey. We contend that this can be achieved by forming patches of surface receivers, extract the incoming signal as a function of wave number and frequency and deconvolve the estimate from the rest of the traces. This leaves the responses to an impulsive source at the location of the receiver patch. Using a semblance-weighted deconvolution operator for stability, the deconvolved data will be independent on the receiver response and the source function, providing data which accurately represents the original geophysical conditions and meeting the objectives of the solicitation. During Phase I, the concepts will be validated using appropriate synthetic and legacy data, and – if necessary - adjusted reflecting the results of the validation tests. Re-analyzing legacy data with modern methods can provide the energy industry with valuable surveys and analyses while avoiding costly ($ 1M or more) re-acquisition efforts. Allows reviewing historical records for past seismic events related to nuclear test activities or other large scale industrial or defense activities. Allows new geophysical analysis for benefits to geology, environmental science, and other scientific efforts.

Phase II

Contract Number: DE-SC0021824
Start Date: 8/22/2022    Completed: 8/21/2024
Phase II year
Phase II Amount
Seismic acquisition involves recording ground motion due to seismic waves (either natural or produced by an active source) and analyzing the resulting wavefields. The goal of many seismic investigations is to map inhomogeneities which scatter waves in order to identify fossil or geothermal energy resources, environmental or safety hazards, or fluid migration during oil and gas production or CO2 storage. Other goals include localizing and characterizing induced seismicity or characterizing nuclear and non-nuclear detonations for treaty enforcement. However, traditional seismic analysis methods require accurate knowledge of sources and detectors and assume simplified formations; this results in poor accuracy and resolution in situations with complex formations, inaccurate survey descriptions, or poorly characterized sources. We have demonstrated a method of Semblance-Weighted Deconvolution for seismic data where both the source signature and the earth response can be adaptively determined from received waveforms alone, even when data is marginal. The method automatically optimizes the bandwidth, resolution, and the signal-to-noise ratio, obtaining best estimates for images and source properties from any seismic dataset. It can be applied to new acquisition campaigns for optimum results, or it can be applied to historical data to improve results and obtain new information without repeating the acquisition process. During Phase I the method was demonstrated on example datasets (real and synthetic), while during Phase II we propose to integrate the method into a full analysis workflow which could directly service government agencies and energy companies, as well as developing a software module that can be licensed for use by other seismic analysts.Commercial Applications and Other