Analytic solutions to the joint estimation of microseismic event locations and effective velocity model

Blias, E.; Grechka, Vladimir

doi:10.1190/geo2012-0517.1

Cited by 31 publications

(15 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Although equation 5 can be adopted for downhole microseismic geometries, as is done in Blias and Grechka (2013), in what follows, I limit the discussion to surface microseismic and extend the model to tilted transverse isotropy.…”

Section: Solution For Isotropymentioning

confidence: 99%

“…Here, extending the results of Blias and Grechka (2013), I remove the assumption of isotropy and concentrate on transversely isotropic models with tilted symmetry axes (TTI). Importantly, I turn the attention from downhole to surface microseismic data because the assumption of subsurface homogeneity, still needed for deriving equations and gaining insights into the joint microseismic inversion, is more appropriate for surface than for downhole microseismic geometries.…”

Section: Introductionmentioning

confidence: 99%

“…Arguably, this is possible only with analytic or semianalytic techniques. Such techniques were introduced to downhole microseismic monitoring by Blias and Grechka (2013) under the assumptions of homogeneity and isotropy of the earth models. Those assumptions, although essential for deriving the exact event locations and velocities, might also be viewed as limitations for practical applications because of the perceived inability of simple models to handle the complexity of realistic heterogeneous and anisotropic reservoirs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Tilted TI models in surface microseismic monitoring

Grechka

2015

GEOPHYSICS

Self Cite

View full text Add to dashboard Cite

A recently published analytic technique for computing locations of microseismic events jointly with velocities of homogeneous isotropic media was extended to surface microseismic monitoring and transversely isotropic models with tilted symmetry axes (TTI). The analysis of traveltimes of the direct P-, SV-, and SH-waves, conducted under the assumptions of homogeneity and weak anisotropy, indicated that the SV-wave data acquired in modern wide-azimuth surface microseismic surveys yield uniquely solvable joint inverse problems for an arbitrary symmetry-axis tilt, whereas the tilts should be close to 90°from the vertical for the P-waves propagating in anelliptically anisotropic media and strictly equal to 90°for the SH-waves to maintain the uniqueness of the joint inversion. These theoretical findings, confirmed on ray-tracing synthetic, were applied to a field microseismic data set. The P-waves excited by microseismic events were found to exhibit significantly flatter moveouts and better focused stacks when located in a constructed effective TTI model compared to those located in a horizontally layered isotropic model provided as a part of conventional microseismic service.

show abstract

Section: Solution For Isotropymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tilted TI models in surface microseismic monitoring

Grechka

2015

GEOPHYSICS

Self Cite

View full text Add to dashboard Cite

show abstract

“…The in situ technique records higher frequencies and smaller events allowing for improved velocity and amplitude analysis, and smaller depth errors than surface microseismic surveys (Shekar and Tsvankin 2012;Grechka and Heigl 2017). Over the last decade, development of new reservoir characterization and imaging tools has improved the estimation of hydraulic stimulation effects, and the interpreter's ability to * E-mail: mabray@alumni.mines.edu estimate fracture properties (Liu, Fomel and Chen 2011;Coffin et al 2012;Blias and Grechka 2013;Grechka and Heigl 2017;Jechumtálová et al 2018;Su et al 2018;Zhang, Rector and Nava 2018).…”

Section: Introductionmentioning

confidence: 99%

Understanding acquisition and processing error in microseismic data: An example from Pouce Coupe Field, Canada

Bray

White

2019

Geophysical Prospecting

View full text Add to dashboard Cite

A B S T R A C TA challenge in microseismic monitoring is quantification of survey acquisition and processing errors, and how these errors jointly affect estimated locations. Quantifying acquisition and processing errors and uncertainty has multiple benefits, such as more accurate and precise estimation of locations, anisotropy, moment tensor inversion and, potentially, allowing for detection of 4D reservoir changes. Here, we quantify uncertainty due to acquisition, receiver orientation error, and hodogram analysis. Additionally, we illustrate the effects of signal to noise ratio variances upon event detection. We apply processing steps to a downhole microseismic dataset from Pouce Coupe, Alberta, Canada. We use a probabilistic location approach to identify the optimal bottom well location based upon known source locations. Probability density functions are utilized to quantify uncertainty and propagate it through processing, including in source location inversion to describe the three-dimensional event location likelihood. Event locations are calculated and an amplitude stacking approach is used to reduce the error associated with first break picking and the minimization with modelled travel times. Changes in the early processing steps have allowed for understanding of location uncertainty of the mapped microseismic events.

show abstract

“…In some cases, it may cause velocity-related errors in locating the microseismic events in areas not covered by the ray trajectories of the perforation shots (Grechka 2010;Grechka, Singh and Das 2011). Secondly, a velocity model can be updated simultaneously with locations using event traveltime information (Blias and Grechka 2013;Yu, Reshetnikov and Shapiro 2013;Li et al 2014). Most of the microseismic tomography methods are adapted from global seismology.…”

mentioning

confidence: 99%

Cross double‐difference inversion for simultaneous velocity model update and microseismic event location

Tian

Zhang

2017

Geophysical Prospecting

View full text Add to dashboard Cite

Microseismic monitoring is an approach for mapping hydraulic fracturing. Detecting the accurate locations of microseismic events relies on an accurate velocity model. The one‐dimensional layered velocity model is generally obtained by model calibration from inverting perforation data. However, perforation shots may only illuminate the layers between the perforation shots and the recording receivers with limited raypath coverage in a downhole monitoring problem. Some of the microseismic events may occur outside of the depth range of these layers. To derive an accurate velocity model covering all of the microseismic events and locating events at the same time, we apply the cross double‐difference method for the simultaneous inversion of a velocity model and event locations using both perforation shots and microseismic data. The cross double‐difference method could provide accurate locations in both the relative and absolute sense, utilizing cross traveltime differences between P and S phases over different events. At the downhole monitoring scale, the number of cross traveltime differences is sufficiently large to constrain events locations and velocity model as well. In this study, we assume that the layer thickness is known, and velocities of P‐ and S‐wave are inverted. Different simultaneous inversion methods based on the Geiger's, double‐difference, and cross double‐difference algorithms have been compared with the same input data. Synthetic and field data experiments suggest that combining both perforation shots and microseismic data for the simultaneous cross double‐difference inversion of the velocity model and event locations is available for overcoming the trade‐offs in solutions and producing reliable results.

show abstract

Analytic solutions to the joint estimation of microseismic event locations and effective velocity model

Cited by 31 publications

References 22 publications

Tilted TI models in surface microseismic monitoring

Tilted TI models in surface microseismic monitoring

Understanding acquisition and processing error in microseismic data: An example from Pouce Coupe Field, Canada

Cross double‐difference inversion for simultaneous velocity model update and microseismic event location

Contact Info

Product

Resources

About