Saudi Aramco is continuously implementing many new innovative techniques and approaches to assist in meeting the industry's increasing challenges. One of these innovations is the new study approach "The Event Solution." Theapproach leads to better synergy among different stakeholders and enables faster decisions that fully encompass the complex uncertainties associated with today's projects. The Event Solution is a short, intensively collaborative event that compresses major decision cycles, reduces uncertainty and provides a wider range of alternatives solutions. The concept is simple: identify the most important objective and focus the collective skills and creativity of a team of experts on meeting that objective in a special event that lasts just for a few weeks. The team is enabled with the latest hardware and software in a large team room where they can work together. A facilitator leads the team with the process that helps them to see "The Big Picture" and understand what matters to the bottom line. The team composition is enriched with representatives from all of the stakeholders (including technical experts, management, and facilitators) so that the results can be concluded and implemented immediately, with maximum buy-in. The Event Solution includes a detailed uncertainty analysis and risk assessment process that has been successfully implemented in many events. The most important deliverable of the Event Solution, however, is that all the stakeholders develop a clear and common understanding of the critical uncertainties, project risk, and the agreed plans to move forward---the decisions. This volume of work, which traditionally requires months or years, is completed in weeks using the Event Solution process. This paper presents the elements and processes of this new approach. Critical elements to a successful Event Solution include software, workroom, team members, and a facilitator. Once the elements are in place, the facilitator leads the team through processes that include project preparation, parallel workflows, uncertainty analysis, critical information plans, project risk assessment, and mitigation plans. Note that uncertainty analysis is not a simple by-product of the study; it is an integral component of success. Techniques are presented that can be applied to any study. Introduction Oil and gas producers are familiar with the performance improvement that multi-discipline teams can contribute to the industry. Joeseph Warren notes that the success of individual team can be variable when he states, "the fundamental idea of cross functional teams and goals appears to surface about every 10 years with a new label. Usually, attempts to implement this concept in the E & P business ended with utter failure for a variety of reasons."1,4 The Event Solution extends the multi-discipline team concept by formalizing key success factors:identifying the most important objective,focusing the collective skills and creativity of a team of experts on meeting that objective, andcollaborating via a special event that lasts weeks rather than months or years. In the 1980s the concept of asset teams was introduced. Unfortunately, integrated software was too immature at that time to enable real integration of the asset team members. As integrated software became more powerful in the early-to-mid 1990s the asset teams began showing more success. In the late 1990s, common processes were adapted by most major oil and gas companies to ensure repeatable success from team to team. Highly formalized processes, often employing gatekeepers, were developed to integrate the management (decision makers) and technical (asset) teams.
Detailed compositional simulation of a giant reservoir with many components is not practical. However, detailed multimillion cell black oil simulation of giant reservoirs is now quite feasible. In this work we apply an efficient method to generate the compositional rates from a black oil simulation of the giant Shaybah field. In situations where the reservoir recovery mechanism is not dominated by compositional effects, an Equation of State (EOS) based stream conversion method can be used. This stream conversion method relies on the fact that when laboratory PVT data measured on available well stream compositions are used to generate the black oil PVT tables, some of the compositional information is lost. The stream conversion model retains this valuable compositional information and applies it to each producing well completion in the black oil simulation at every time step. As proof of concept, the stream conversion method was applied to a black oil simulation and to a limited (eightcomponent) compositional simulation to generate a 17component compositional stream and the results were compared to the respective full EOS compositional simulation for a relatively small sector (250,000 cells) of the giant Shaybah field. The compositional stream rates are in excellent agreement with the stream converted black oil results. As would be expected, the computational costs of using the EOS based compositional simulator (with 17 components) is in excess of 40 times the black oil simulation time for the small sector model. In general, the stream conversion method can be used to generate the dynamically varying compositional streams from any black oil simulation for use in the design and operation of surface facilities and in calculating the amounts of a certain cut (e.g. NGL) from the production streams.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractDetailed compositional simulation of a giant reservoir with many components is not practical. However, detailed multimillion cell black oil simulation of giant reservoirs is now quite feasible. In this work we apply an efficient method to generate the compositional rates from a black oil simulation of the giant Shaybah field.In situations where the reservoir recovery mechanism is not dominated by compositional effects, an Equation of State (EOS) based stream conversion method can be used. This stream conversion method relies on the fact that when laboratory PVT data measured on available well stream compositions are used to generate the black oil PVT tables, some of the compositional information is lost. The stream conversion model retains this valuable compositional information and applies it to each producing well completion in the black oil simulation at every time step.As proof of concept, the stream conversion method was applied to a black oil simulation and to a limited (eightcomponent) compositional simulation to generate a 17component compositional stream and the results were compared to the respective full EOS compositional simulation for a relatively small sector (250,000 cells) of the giant Shaybah field. The compositional stream rates are in excellent agreement with the stream converted black oil results. As would be expected, the computational costs of using the EOS based compositional simulator (with 17 components) is in excess of 40 times the black oil simulation time for the small sector model. In general, the stream conversion method can be used to generate the dynamically varying compositional streams from any black oil simulation for use in the design and operation of surface facilities and in calculating the amounts of a certain cut (e.g. NGL) from the production streams.
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