Reservoir modelling of complex geological systems—A multiple point perspective

K. Eskandari, Sanjay Srinivasan

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

Abstract

Accurate characterization of subsurface oil reservoirs is an essential prerequisite to the design and implementation of enhanced oil recovery (EOR) scenarios. Specifically, in reservoir characterization, integrating static and dynamic data into reservoir models to construct accurate and realistic models has received considerable attention. Unlike most of the conventional geostatistical approaches of integrating data into reservoir models that are based on semi-variograms (two point statistics) as a measure of spatial connectivity, a complete multiple point statistic framework is presented in this paper. In contrast to two point statistic methods, multiple point statistics based methods are capable of reproducing curvilinear geological structures. The algorithm starts with extracting multiple point statistics from training images using an optimal spatial template. After collecting different patterns and building the mp histogram, the pattern reproduction process commences. It begins from data locations and then grows to fill the whole reservoir domain. The algorithm accounts for three main practical issues: uncertainty in geological scenarios, scanning template and non-stationarity. Growthsim is capable of integrating data from multiple data sources. One of these data types is dynamic data or flow history. The conventional approach to integrate production information into reservoir models is by iterative perturbation of the reservoir model until the production history of the reservoir is matched. Iterative methods have been applied till date to random fields that are completely characterized by a two-point covariance function. In contrast, this paper presents a forward modeling approach that investigates history matching within a multiple point modeling framework. A novel technique is implemented in this research is based on the merging of mps inferred from history matched and geological models. Pattern growth is performed subsequently by sampling from the merged mp histograms. History matched models using the presented approach show an excellent agreement with underlying geological descriptions and match production history.

Original languageEnglish (US)
Title of host publicationCanadian International Petroleum Conference 2008
PublisherPetroleum Society of Canada (PETSOC)
ISBN (Print)9781613991152
StatePublished - Jan 1 2018
EventCanadian International Petroleum Conference 2008, CIPC 2008 - Calgary, Canada
Duration: Jun 17 2008Jun 19 2008

Other

OtherCanadian International Petroleum Conference 2008, CIPC 2008
CountryCanada
CityCalgary
Period6/17/086/19/08

Fingerprint

Statistics
modeling
history
histogram
Oils
enhanced oil recovery
reservoir characterization
variogram
forward modeling
Iterative methods
geological structure
Merging
connectivity
perturbation
statistics
Sampling
Scanning
Recovery
oil
sampling

All Science Journal Classification (ASJC) codes

  • Geochemistry and Petrology
  • Energy Engineering and Power Technology

Cite this

Eskandari, K., & Srinivasan, S. (2018). Reservoir modelling of complex geological systems—A multiple point perspective. In Canadian International Petroleum Conference 2008 Petroleum Society of Canada (PETSOC).
Eskandari, K. ; Srinivasan, Sanjay. / Reservoir modelling of complex geological systems—A multiple point perspective. Canadian International Petroleum Conference 2008. Petroleum Society of Canada (PETSOC), 2018.
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Eskandari, K & Srinivasan, S 2018, Reservoir modelling of complex geological systems—A multiple point perspective. in Canadian International Petroleum Conference 2008. Petroleum Society of Canada (PETSOC), Canadian International Petroleum Conference 2008, CIPC 2008, Calgary, Canada, 6/17/08.

Reservoir modelling of complex geological systems—A multiple point perspective. / Eskandari, K.; Srinivasan, Sanjay.

Canadian International Petroleum Conference 2008. Petroleum Society of Canada (PETSOC), 2018.

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

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Eskandari K, Srinivasan S. Reservoir modelling of complex geological systems—A multiple point perspective. In Canadian International Petroleum Conference 2008. Petroleum Society of Canada (PETSOC). 2018