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Ensemble Learning Improves the Efficiency of Microseismic Signal Classification in Landslide Seismic Monitoring. [PDF]
Sensors (Basel)Xin B, Huang Z, Huang S, Feng L.
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Interferometric Imaging of Microseismic Data
SEG Technical Program Expanded Abstracts 2015, 2015Interferometric imaging of microseismic data can provide high-resolution images of the subsurface. Each microseismic event can be used as a seismic source to image the subsurface in the vicinity of the event location. Combining thousands of events yields a three-dimensional image with a resolution on the order of a few feet, much finer than typical ...
Steve Cole +7 more
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Noise suppression in surface microseismic data
The Leading Edge, 2012We introduce a passive noise suppression technique, based on the τ − p transform. In the τ − p domain, one can separate microseismic events from surface noise based on distinct characteristics that are not visible in the time-offset domain. By applying the inverse τ − p transform to the separated microseismic event, we suppress the surface noise in the
Farnoush Forghani-Arani +5 more
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Geomechanical Reservoir Characterization with Microseismic Data
SPE Eastern Regional Meeting, 2013Abstract Bulk fluid injection into low permeability geologic formations been observed to trigger microearthquakes (MEQs). Triggering of MEQ events has been linked to pore pressure, temperature, and in-situ stress variations. The resulting clouds of micro-seismic events are believed to carry information about the underlying coupled flow ...
Mohammadali Tarrahi +2 more
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ADIPEC, 2023
Abstract This study proposes a new workflow for analyzing microseismic data using causal inference techniques. This approach allows us to identify the causal relationships between a new microseismic event and its spatiotemporally proximal, prior microseismic events, while taking into account confounding variables that influence both the ...
Oliver Rojas Conde +2 more
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Abstract This study proposes a new workflow for analyzing microseismic data using causal inference techniques. This approach allows us to identify the causal relationships between a new microseismic event and its spatiotemporally proximal, prior microseismic events, while taking into account confounding variables that influence both the ...
Oliver Rojas Conde +2 more
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Microseismic Data vs. Surface Heaving Data: Qualitative Correlation
Proceedings, 2014We attempt to correlate a set of surface heaving (or uplift) data, well head pressure and injection rate with microseismic data. This correlation may give a high-confidence indication of fracture development or fault reactivation during injection or production operation.
J. Park +3 more
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2020
We discuss the elements of a generalized processing workflow for a single well geometry. Key elements of the processing workflow including data loading, filtering, event detection, arrival picking, velocity model building, hypocenter location and magnitude estimation are explained in detail.
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We discuss the elements of a generalized processing workflow for a single well geometry. Key elements of the processing workflow including data loading, filtering, event detection, arrival picking, velocity model building, hypocenter location and magnitude estimation are explained in detail.
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Microseismic Data Interpretation
2020We review the value of information retrieved from microseismic data sets in the unconventional resource development. We explain the key information that can be extracted by using microseismic, seismic, well logs, geological and engineering data individually.
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Data-acquisition design for microseismic monitoring
The Leading Edge, 2010Microseismic monitoring of hydraulic well treatments is one of the most useful seismic techniques that can aid the development of tight-gas and shale-gas fields. The main challenge in these fields is an extremely low formation permeability, which lies in the microdarcy or even nanodarcy range and requires thousands of closely spaced wells to drain the ...
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Identifying Reservoir Drainage Patterns from Microseismic Data
Proceedings, 2013A method and system for identifying reservoir drainage patterns from microseismic data for illustrating flow paths towards ports. The method includes: determining moment tensor data for each of a plurality of microseismic events in the reservoir; inferring crack formation data in the reservoir in dependence on the moment tensor data; and calculating ...
T.I. Urbancic, A. Wuestefeld, A. Baig
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