Because digital-energy (DE) projects are intended to improve performaance, both a normalized baseline describing existing conditions and targets (generally set by management) for future improvement are necessary. Today, only a few assets capture enough data to fully understand the status of operational activities or too quantify optimum reservoir behavior. A benchmark, or baseline, prrovides a way for companies to identify "where they are" and helps justify DE investments by tracking improvement. To optimize returns, asset potential should be established before appropriate targets are set. DE business impact (the difference between baseline and potential) may then be adequately evaluateed. Deviation from ideal performance may be a result of equipment limitations, facility availability and uptime, administrative or operational bottlenecks, fluid behavior, weather, employee skill set, and numerous other factors. Differences between assets may be attributed to artificial-lift cost variations, local economic conditions, onshore/offshore, lifecycle stage, asset type (shale, waterflood, deep water, coalbed methane, etc.), produced fluid, and many others. Refining faces equally diverse problems and has taken the necessary steps to address this challenge by applying benchmarking with commercial tools, such as the Solomon Associates Indices, for ranking and comparing different refineries. For E&P, an initial external benchmarking framework based on public data (annual reports, EIA, 10Ks, IHS, etc.) will be discussed so that high-level performance metrics can be evaluateed. By developing a similar approach using proprietary and internal data, companies can beegin to understand asset performance in detail and rank assets not only within an organization but also aacross company boundaries based on t operational efficiency and effectiveness. Prioritizing DE projects based on their contribution also becomes possible. As DE projects are deployed, the benchmarks can be refined and updated for greeater accuracy. If the framework is properly designed, a company can see where gains are possible and adapt future programs to concentrate on areas where the most value can be derived, regardless of asset type, which will permit a company to forecast benefits and predict how effective a DE initiative could bee.
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