Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Tracking microseismic signals from the reservoir to surface

Authors: S.C. Maxwell; D. Raymer; M. Williams; P. Primiero;

Tracking microseismic signals from the reservoir to surface

Abstract

Since the launch of commercial microseismic mapping of hydraulic fracturing in the Barnett Shale in 2000, microseismic has become the de facto geophysical technique to characterize stimulated fracture networks in unconventional reservoirs. Effective stimulation of these resources through hydraulic stimulations along multiple intervals of horizontal wells is critical to economic production from tight and shale oil and gas resources. The inherent low permeability of these formations necessitates creation of permeable flow paths between the reservoir and wellbore through injection of high-pressure fluids. Microseismic observations over the last decade have led to a paradigm shift in our concept and engineering models of hydraulic fractures from simple, planar fractures to complex fracture networks controlled by the stress state and the existence of pre-existing fractures. Injected fluids in rock tend to follow the “path of least resistance” that minimizes the work done, preferentially growing into pre-existing fractures and lower stress intervals. Microseismic is the only technology that can image these fracture networks and has led to the incredible expansion of microseismic monitoring. Over the past decade, a vast microseismic database has been collected covering all North American shale oil and gas fields, in addition to key international fields. The microseismic results have demonstrated the significant variability in hydraulic fracturing responses on all scales: across a field, along the horizontal length of a well, and even between perforations of a single frac stage.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    35
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!