Intelligent Field Centers IFCs: Integrating People, Processes and Technologies to Optimally Manage Giant Fields

Barghouty, Murad; Al-Dhubaib, Tofig A.; Jama, Ali Ahmed; Jaimes, Olmedo

doi:10.2118/128469-ms

Cited by 16 publications

(3 citation statements)

References 5 publications

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“…The drilling center enables collaboration with teams at other drilling centers, rigs, and the administrative staff so that people discuss ideas and exchange experiences and best practices [25].…”

Section: Dimension Cluster Main Questions Peoplementioning

confidence: 99%

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Drilling Centers Maturity Model Evaluation Based on Integrated Operation Key Elements: A Case Study from Brazil

Lima¹,

Pinto²,

Sobreira³

et al. 2016

TOPEJ

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The current economic situation is pushing the oil industry toward higher efficiency and safety, demanding different ways of work. Optimization is an increasingly important issue, which involves technology, sharing of real-time information, collaboration, and the application of multiple expertise across disciplines, organizations, and geographical locations. In this way, companies are introducing Integrated Operations to redesign and optimize many work processes. To address this challenging scenario, Petrobras, the Brazilian oil operator, decided to optimize the collaborative environments of its drilling centers which are critical for well construction, to introduce integration and improve efficiency. This article presents a methodological approach that is applicable across the oil industry, including a survey of drilling centers to document perceptions concerning the key Integrated Operations components: people, process, technology and organization. This approach applied an intensive assessment. The applicability and scalability of this methodology are reinforced by inclusion of statistical analysis of questionnaire responses. The study results were used to implement a unique collaborative environment that has decreased operating time and facilitated future operational improvements. The research pointed to positive impacts on both, the safety and performance aspects. The preliminary results are promising. For an example, it was observed a 7.25% decrease in time required for a casing run.

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Section: Dimension Cluster Main Questions Peoplementioning

confidence: 99%

“…The data and information of the drilling center processes are readily available for correct interpretation and understanding [25].…”

Section: Technologymentioning

confidence: 99%

Drilling Centers Maturity Model Evaluation Based on Integrated Operation Key Elements: A Case Study from Brazil

Lima¹,

Pinto²,

Sobreira³

et al. 2016

TOPEJ

View full text Add to dashboard Cite

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“…Intelligent Fields (also known as Smart Fields, Closed-Loop Reservoir Management, Fields of the Future, i-Fields among other designations) are becoming a reality (see e.g. AbdulKarim et al, 2010, van den Berg et al, 2010, and Barghouty et al, 2010. Typically this invokes huge amounts of data, and raises expectations that one should be able to make decisions based upon solid foundations.…”

Section: Introductionmentioning

confidence: 99%

Integrating Mathematical Optimization and Decision Making in Intelligent Fields

Echeverría-Ciaurri¹,

Conn

Mello³

et al. 2012

All Days

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In this paper a decision-making approach that can be applied to problems that are relevant to the oil and gas industry is presented. This methodology is supported by state-of-the-art mathematical optimization algorithms, and is based on the formal integration of the decisions in question with well-studied optimization procedures. The integration of the methodology with the application adds to its robustness. Two different types of problems are formulated and solved. The first kind is based on deciding which wells have to be shut in during a given production interval whilst simultaneously optimizing the controls for each selected well. The second category involves deciding for a group of wells which ones have to be injectors or producers, and at the same time searching for optimal well locations. In all the results obtained we can systematically see that the set of decisions proposed by the integrated approach mean substantial improvement in field production. For example, in the first class of problems studied, the production oil target is satisfied, and up to 50 percent of produced water is saved with respect to the reference case. The huge amount of information available, for example, in Intelligent/Smart Fields or Closed-Loop Reservoir Management can be utilized for rigorously making solid decisions. In this work we put an emphasis on integration of real-life decisions with a realistic simulation-based mathematical optimization framework. This framework can be also useful for establishing a common language for decision makers and researchers within a given organization, and as a consequence endowing the decision-making process with agility and robustness. It should be stressed that ultimately it is human interpretation and intuition that drives the making of crucial decisions. Automated tools should be understood as an additional (and hopefully valuable) source of information for making these important decisions.

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