Markov Bayes Simulation for structural uncertainty estimation

Samik Sil, Sanjay Srinivasan, Mrinal Sen, Jaime J. Ríos López, Madain Moreno Vidal, Alberto Rusic, Manuel González

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reservoir models are built using disparate datasets each of which may be prone to experimental and interpretational errors and therefore a resulting reservoir model is generally associated with uncertainties. One of the primary sources of uncertainties lies in the structure (or reservoir architecture) estimation from seismic data. Geostatistics can be used to integrate seismic data with well data for the purpose of structural uncertainty estimation. In this paper we present a case study from the Gulf of Mexico, where structural uncertainty associated with a seismic horizon is modeled using Markov-Bayes stochastic simulation. For this simulation, seismic data is used as “soft” or secondary data while well log derived marker depths are used as hard data. Simulation results show uncertainty distributions with smaller variance in the vicinity of the wells. However, in regions away from the wells, the interpreter-picked horizon appears to fall outside the error bounds predicted by our stochastic algorithm. Lack of well control, existence of faults, improper choice of seismic processing parameters (error in time migrated images) and interpreters' bias are some of the plausible causes of this disparity.

Original languageEnglish (US)
Title of host publication78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008
PublisherSociety of Exploration Geophysicists
Pages1491-1495
Number of pages5
ISBN (Print)9781605607856
StatePublished - Jan 1 2018
Event78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008 - Las Vegas, United States
Duration: Nov 9 2008Nov 14 2008

Other

Other78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008
CountryUnited States
CityLas Vegas
Period11/9/0811/14/08

Fingerprint

seismic data
well
horizon
simulation
Gulf of Mexico
geostatistics
markers
causes
parameter
gulf
marker
distribution

All Science Journal Classification (ASJC) codes

  • Geophysics

Cite this

Sil, S., Srinivasan, S., Sen, M., Ríos López, J. J., Vidal, M. M., Rusic, A., & González, M. (2018). Markov Bayes Simulation for structural uncertainty estimation. In 78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008 (pp. 1491-1495). Society of Exploration Geophysicists.
Sil, Samik ; Srinivasan, Sanjay ; Sen, Mrinal ; Ríos López, Jaime J. ; Vidal, Madain Moreno ; Rusic, Alberto ; González, Manuel. / Markov Bayes Simulation for structural uncertainty estimation. 78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008. Society of Exploration Geophysicists, 2018. pp. 1491-1495
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Sil, S, Srinivasan, S, Sen, M, Ríos López, JJ, Vidal, MM, Rusic, A & González, M 2018, Markov Bayes Simulation for structural uncertainty estimation. in 78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008. Society of Exploration Geophysicists, pp. 1491-1495, 78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008, Las Vegas, United States, 11/9/08.

Markov Bayes Simulation for structural uncertainty estimation. / Sil, Samik; Srinivasan, Sanjay; Sen, Mrinal; Ríos López, Jaime J.; Vidal, Madain Moreno; Rusic, Alberto; González, Manuel.

78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008. Society of Exploration Geophysicists, 2018. p. 1491-1495.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Sil S, Srinivasan S, Sen M, Ríos López JJ, Vidal MM, Rusic A et al. Markov Bayes Simulation for structural uncertainty estimation. In 78th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2008. Society of Exploration Geophysicists. 2018. p. 1491-1495