Events

Rock Property Estimation Using Prestack Inversion with Stochastic Refinement - an Eagle Ford Example

February 07, 2017
Webinar is now available for on-demand viewing.
PDM_Virtual-Lecture.jpg

Presented by:  Joanne Wang, Manager Integrated Geoscience Workflow Development
Featured Domain:  Interpretation, Modeling
Featured Technology:  Paradigm QSI Solutions, SKUA-GOCAD

View_Presentation.jpg

Abstract

Shale is highly heterogeneous in nature, leading to challenges in shale reservoir exploration and production. Geoscientists have been searching for solutions that can determine and qualify the “sweet spots” where the production and recovery rate are highest in the shale formation.
 
Seismic data carries important information about subsurface geology and rock properties.  When properly processed, imaged and analyzed, the seismic data becomes a vital source of information for the characterization and assessment of shale heterogeneity, in situ stress, TOC and brittle/ductile quality. However, the use of seismic data is often limited by the seismic resolution.
 
As increasing amounts of well data become available, incorporating seismic with well data provides a mechanism for accurately estimating rock properties that delineate the reservoir quality.  In this presentation we propose a workflow using prestack inversion with stochastic refinement to study shale property distribution in the Eagle Ford formation.

Biography

Joanne-Wang_cropped.jpgJoanne Wang is Manager for Integrated Geoscience Workflow Development at Paradigm. In this role, she is responsible for developing integrated workflows in the areas of reservoir characterization (conventional and unconventional), pore pressure prediction, velocity model building and time-to-depth conversion.  Joanne has over 20 years of industry experience and holds a Master of Science degree in Geophysics from the Graduate School of China University of Geosciences.