Framework for time lapse fracture characterization using seismic, microseismic &amp; well log data

Maity, Debotyam; Aminzadeh, Fred

doi:10.1190/segam2012-0387.1

Cited by 6 publications

(1 citation statement)

References 13 publications

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“…The V P and V S can be related to elastic properties including bulk modulus, shear modulus, and Poisson's ratio, and these can be used to characterize zones of interest using available frameworks to relate the geophysical and geomechanical properties with reservoir attributes such as fractures (Toksöz and Johnston, 1981). Estimation of rock properties based on microseismic-derived wave velocity estimates has been demonstrated as a viable tool for reservoir characterization (Maity and Aminzadeh, 2012). We know that V P and V S can be used to derive Lamé's parameters (Mavko et al, 2003), which in turn are used to estimate the inertial properties of the rock (Beer et al, 2009).…”

Section: Passive Seismic Data Analysismentioning

confidence: 99%

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

Maity

Aminzadeh

2015

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We have characterized a promising geothermal prospect using an integrated approach involving microseismic monitoring data, well logs, and 3D surface seismic data. We have used seismic as well as microseismic data along with well logs to better predict the reservoir properties to try and analyze the reservoir for improved mapping of natural and induced fractures. We used microseismic-derived velocity models for geomechanical modeling and combined these geomechanical attributes with seismic and log-derived attributes for improved fracture characterization of an unconventional reservoir. We have developed a workflow to integrate these data to generate rock property estimates and identification of fracture zones within the reservoir. Specifically, we introduce a new "meta-attribute" that we call the hybrid-fracture zone-identifier attribute (FZI). The FZI makes use of elastic properties derived from microseismic as well as log-derived properties within an artificial neural network framework. Temporal analysis of microseismic data can help us understand the changes in the elastic properties with reservoir development. We demonstrate the value of using passive seismic data as a fracture zone identification tool despite issues with data quality.

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Section: Passive Seismic Data Analysismentioning

confidence: 99%

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

Maity

Aminzadeh

2015

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Four Phenomena Observed on Microseismic Data

St-Onge¹

2013

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Fracture Characterization in Unconventional Reservoirs using Active and Passive Seismic Data with Uncertainty Analysis through Geostatistical Simulation

Maity

Aminzadeh

2013

SPE Annual Technical Conference and Exhibition

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This study discusses a new workflow for fracture characterization and modeling using geophysical (microseismic and 3D surface seismic) data along with independent reservoir information (such as well logs). The framework is ideally suited for unconventional environments such as shale and tight reservoirs where modern technologies such as the use of hydraulic fracturing and passive seismic monitoring allow application of the proposed workflow.The workflow involves generating geomechanical property estimates (including stress and weakness estimates) as derived from passive seismic data analysis and relevant seismic attributes derived from 3D seismic data combined using ANN based reservoir property modeling framework. The training information for the networks is generated based on a-priori information through image logs. Resolution of passive seismic derived velocity models is improved by using sequential Gaussian co-simulation by combining low resolution velocity maps high resolution seismic impedance data for phase velocity estimation. Uncertainty estimates are quantified by adequate number of realizations and associated probability density functions for fracture properties within study volume.In this paper, different properties estimated through ANN modeling have been shared. New fracture identifier (FZI) properties have been defined and the models have been used to characterize fracture zones and major discontinuities for a representative unconventional reservoir (geothermal setting) used in our study. We also share uncertainty estimates for the identified fracture zones for improved characterization. Finally fracture property estimates for the study area (derived using FZI and other properties) have been generated for future reservoir simulation studies.The proposed method allows for improved understanding of shale and other unconventional reservoirs through fracture mapping and provides a workflow for improved volumetrics of the reservoir by making use of identified properties for fracture modeling. This work validates the potential for using relatively low resolution passive seismic data for improved reservoir characterization using Geostatistical tools. It also provides a valuable framework for pseudo 4D characterization where a single 3D seismic survey can be used as the basis to characterize the reservoir in a time lapse fashion using new information collected in time through passive seismic arrays as well as new well logs being obtained within the area of interest.

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Framework for time lapse fracture characterization using seismic, microseismic & well log data

Cited by 6 publications

References 13 publications

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

Four Phenomena Observed on Microseismic Data

Fracture Characterization in Unconventional Reservoirs using Active and Passive Seismic Data with Uncertainty Analysis through Geostatistical Simulation

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