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Integration of seismic data in reservoir modeling through seismically constrained facies models

Maisha Amaru, Lewis Li and Aigul Tyshkanbayeva
Integration of seismic data in reservoir modeling through seismically constrained facies models (in Seismic reservoir modeling, Shauna Oppert (prefacer), Kathleen Baker (prefacer) and Arpita Bathija (prefacer))
Leading Edge (Tulsa, OK) (December 2022) 41 (12): 815-823

Abstract

Seismic data are an important source of information to guide and constrain reservoir modeling as it samples the subsurface in 3D away from wells. Seismic interpretations are used to constrain the structure of reservoir models. Different seismic attributes can support the identification and definition of stratigraphic features, and seismic inversion products can help constrain the rock properties. Different methods exist for integration of seismic data in the modeling process. Here, we present two new methods. The first method constrains facies definition and modeling with seismic data through a geobody earth modeling approach. The second method updates existing facies models with new seismic data using a Bayesian approach. Both methods are applied to a case study with good quality seismic data. The results show that the reservoir model becomes more consistent with the observed field seismic data when these fast and repeatable methods are applied (compared to not integrating seismic constraints or using time-intensive manual integration approaches), thus enabling more robust reservoir models and forecasts.


ISSN: 1070-485X
EISSN: 1938-3789
Serial Title: Leading Edge (Tulsa, OK)
Serial Volume: 41
Serial Issue: 12
Title: Integration of seismic data in reservoir modeling through seismically constrained facies models
Title: Seismic reservoir modeling
Author(s): Amaru, MaishaLi, LewisTyshkanbayeva, Aigul
Author(s): Oppert, Shaunaprefacer
Author(s): Baker, Kathleenprefacer
Author(s): Bathija, Arpitaprefacer
Affiliation: Chevron Technical Center, Houston, TX, United States
Affiliation: Chevron, Houston, TX, United States
Pages: 815-823
Published: 202212
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 16
Accession Number: 2023-004511
Categories: Economic geology, geology of energy sources
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. sects.
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2023, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 2023
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