Microseismic monitoring — Introduction

Grechka, Vladimir; Artman, Brad; Eisner, Leo; Heigl, Werner M.; Wilson, Stephen

doi:10.1190/2015-0917-spseintro.1

Cited by 7 publications

(1 citation statement)

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“…More recently, additional geophysical technol ogies are extending their application to reservoir exploration and description. This includes: elec tromagnetic surveys (MacGregor and Tomlinson, 2014), microseismicity (Goodway, 2012;Grechka et al, 2015), multicomponent seismic recording (Caldwell, 1999;Gaiser et al, 2001), broader fre quency band seismic acquisition (Moldoveanu et al, 2007;Chiu et al, 2013;Vassallo et al, 2013), increased spatial density of seismic receiv ers (Ramsdem et al, 2005;Winter et al, 2014), Downloaded 07/08/17 to 186.88.151.214. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/ permanent instrumentation of oil fields for short er timelapse monitoring (Ebrom et al, 2000;Lumley, 2001), and seismic tomography based on receiver interferometry Schuster, 2009;Curtis et al, 2006;Grechka and Zhao, 2012).…”

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7. Seismic, rock physics, spatial models, and their integration in reservoir geophysics

Bosch

Mukerji²,

González

2014

Encyclopedia of Exploration Geophysics

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seismic inversion and rock physics models. Furthermore well logs allow for local validation of the estimations and constraint for the struc ture and properties. Combining the spatially dis tributed information provided by seismic surveys with the localized information obtained from well logging tools requires handling disparate property support scales and use of spatial statisti cal models. Most common models are based on the spatial homogeneity of the mean (one point statistics) and the spatial covariance (two point statistics). Cokriging estimation and multivariate Gaussian simulation are examples of these meth ods, which are very useful in the spatial combina tion of information. In addition, methods based on multipoint statistics are used to model com plex morphology. The integration of the overall data, information, geophysical, and geological knowledge into a reliable reservoir model is elab orated via diverse workflows. A basic sequence includes seismic interpretation, seismic inver sion, reservoir characterization, geostatistical es timation, geostatistical simulation, and dynamic fluid flow modeling. It is common to cycle within the sequence to update the model as additional information about the reservoir arrives. Some workflows proceed in a stepwise manner, while others, with increasing computational require ments, employ joint inversion formulations where multiproperty models are estimated to jointly satisfy the complete set of available data.

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