Shaping the Industry's Approach to Intelligent Energy
- Diane Langley (JPT Features Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- March 2006
- Document Type
- Journal Paper
- 40 - 46
- 2006. Copyright is held partially by SPE. Contact SPE for permission to use material from this document.
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SPE’s first Intelligent Energy conference, to be held 11–13 April in Amsterdam, will focus on the upstream industry’s drive to improve oilfield performance through the use of digital-age technologies. More than 60 technical, three plenary, and 14 poster sessions will address the challenges of integrating these new technologies across the different workflows and areas of activity in the oil and gas industry.
Program organizers chose five papers that will be presented at the conference as examples of some of the best uses of digital technology operating in the oil and gas sector today. The technical papers discussed in this article are listed at left.
Accelerating Mars Hydrocarbon Development
In SPE paper 99482, R. Peterson et al. state, “Real value in reservoir geoscience and engineering lies in the ability to optimize the coupling between static and dynamic components at both appraisal and development stages.” Elaborating on a joint Shell-Schlumberger project to upgrade capabilities and global processes on deepwater Gulf of Mexico fields such as Mars, the authors outline how an integrated solution enables the asset team (driven by group consensus) to optimize resources on the right reservoir scenarios and the most relevant sources of risk.
The project targets the area where there is the highest possibility of making decisions that could possibly erode significant value from the field—the reservoir-modeling and concept-solution phase. This area requires a high level of input from multiple asset team members. According to the authors, because an exhaustive number of uncertainties (Fig. 1) and a variety of development options must be considered, evaluation time can take years. Also, sometimes reservoir models are not developed to the appropriate level of detail to support the required decision making. Not only do the models take a long time to build, but they also identify uncertainties, and the resulting assumptions are understood only on a discipline-by-discipline basis.
The authors detail how technology enablers (e.g., scenario-options evaluation, decision support systems, collaborative environments) and organizational change (intelligent workflows, R&D, and business models) are used to improve execution of hydrocarbon-development and integrated-reservoir-management (IRM) processes. A solution embodying a combination of real-time R&D coupled with strong asset team project alignment to support “right-time” decisions is being leveraged on Shell’s Mars field. Solution elements include a Smart Workflow System, an Uncertainty Management Tool, and a Smart Collaborative Environment (Fig. 2) joined with new collaborative work processes.
The joint project scope will take data-management issues beyond existing architecture and functionality. Also, a prototype Smart Workflow System extends integrated framework capabilities and addresses such shortfalls as nontransparent tracking, poor audit trail of the multidisciplinary decision rationale, and lack of guides and prompts/best practices from within the application suite. The prototype system employs a Web-based environment that supports human workflow and automated processes.
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