Implementing i-field-Integrated Solutions for Reservoir Management: A San Joaquin Valley Case Study

Popa, Andreï; Horner, Katie; Cassidy, Steven C.; Opsal, Steven John

doi:10.2118/143950-pa

Cited by 6 publications

(1 citation statement)

References 13 publications

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“…The rejection sampling method described above is also called the filtering method. Filtering method has been widely used in the industry together with proxies to obtain posterior distribution (Popa and Cassidy, 2012). Theoretically, if we have a reliable model for the distribution and the correlation of the data error (which includes measurement error and modeling error), a corresponding acceptance probability can be derived using the Bayes' rule.…”

Section: Step 4: Generate Plausible Surveillance Data Realizationsmentioning

confidence: 99%

Model-Based A Priori Evaluation of Surveillance Programs Effectiveness using Proxies

Xie

Sarma

et al. 2015

SPE Reservoir Simulation Symposium

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Surveillance programs play an important role in reservoir management and are crucial for minimizing subsurface risks and improving decision quality. Optimal design and selection of the surveillance plan requires predicting the performance (e.g. in terms of the expected amount of uncertainty reduction in an objective function) of a given surveillance plan before it is implemented. Because the data from the surveillance program is uncertain at the time of the analysis, multiple history matching runs are required to evaluate the effectiveness of the surveillance program for different plausible realizations of the observed data. As such, the computational cost may be prohibitive as the number of reservoir simulations needed for the multiple history matching runs would be substantial. This paper proposes a framework based on proxies and rejection sampling (filtering) to perform the multiple history matching runs with a manageable number of reservoir simulations. The workflow proposed enables qualitative and quantitative analysis of a surveillance plan. Qualitatively, heavy hitter alignment analysis for the objective function and the observed data provides actionable measures for screening different surveillance designs. Quantitatively, the evaluation of expected uncertainty reduction from different surveillance plans allows for optimal design and selection of surveillance plans.

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Section: Step 4: Generate Plausible Surveillance Data Realizationsmentioning

confidence: 99%

Model-Based A Priori Evaluation of Surveillance Programs Effectiveness using Proxies

Xie

Sarma

et al. 2015

SPE Reservoir Simulation Symposium

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Toward an Automatic Metadata Management Framework for Smart Oil Fields

Chelmis

Zhao

Sorathia

et al. 2013

SPE Economics &Amp; Management

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Vast volumes of data are continuously generated in smart oilfields from swarms of sensors. On one hand, increasing amounts of such data are stored in large data repositories and accessed over high-speed networks; On the other hand, captured data is further processed by different users in various analysis, prediction and domain-specific procedures that result in even larger volumes of derived datasets. The decision making process in smart oilfields relies on accurate historical, real-time or predicted datasets. However, the difficulty in searching for the right data mainly lies in the fact that data is stored in large repositories carrying no metadata to describe them. The origin or context in which the data was generated cannot be traced back, thus any meaning associated with the data is lost. Integrated views of data are required to make important decisions efficiently and effectively, but are difficult to produce; since data is being generated and stored in the repository may have different formats and schemata pertaining to different vendor products. In this paper, we present an approach based on Semantic Web Technologies that enables automatic annotation of input data with missing metadata, with terms from a domain ontology, which constantly evolves supervised by domain experts. We provide an intuitive user interface for annotation of datasets originating from the seismic image processing workflow. Our datasets contain models and different versions of images obtained from such models, generated as part of the oil exploration process in the oil industry. Our system is capable of annotating models and images with missing metadata, preparing them for integration by mapping such annotations. Our technique is abstract and may be used to annotate any datasets with missing metadata, derived from original datasets. The broader significance of this work is in the context of knowledge capturing, preservation and management for smart oilfields. Specifically our work focuses on extracting domain knowledge into collaboratively curated ontologies and using this information to assist domain experts in seamless data integration.

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An Integration between Geological and Reservoir Engineering Data to Design a Conceptual Waterflood Program

Ela

Monem²,

Samir³

et al. 2013

All Days

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Field development plan is a set of operations and decisions by which oil reservoirs are identified, evaluated and developed. Making smart reservoir development plan depends on the ability to analyze and integrate the available data. In this work, a conceptual short-term study was performed with the objective of determining the optimum conditions for required application of waterflooding pilot project in Upper Bahariya Formation (Ferdaus field / Egypt) in order to maintain the pressure and increase the oil production rate. The integration between the geological and engineering data identified the reservoir structure of Upper Bahariya formation which includes two isolated formations: Upper Baharia 2 and Upper Baharia 3. The original oil in place of Upper Baharia 2 is about 5 MMSTB, while for Upper Baharia 3 is about 11.9 MMSTB. An efficient monitoring program design, for the waterflooding pilot, including three different injection scenarios with 12 response cases, to investigate the uncertainties of the static model are presented. The results of the pilot study scenarios are very encouraging to implement the waterflooding pilot. Recoverable amount of 2 MMSTB will be achieved upon performing the full scale waterflooding project. Such study is an original conceptual contribution to the knowledge of the integration between geological and reservoir engineering data to design of a comprehensive waterflood program.

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Implementing i-field-Integrated Solutions for Reservoir Management: A San Joaquin Valley Case Study

Cited by 6 publications

References 13 publications

Model-Based A Priori Evaluation of Surveillance Programs Effectiveness using Proxies

Model-Based A Priori Evaluation of Surveillance Programs Effectiveness using Proxies

Toward an Automatic Metadata Management Framework for Smart Oil Fields

An Integration between Geological and Reservoir Engineering Data to Design a Conceptual Waterflood Program

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