
doi: 10.2118/99963-ms
Abstract In E &P, from asset managers to front end operations staff, there is a common problem — we are data rich, but information poor. In particular, timely well-by-well production surveillance and allocation often remains a problem. Gathering data, even real time data, from wells and facilities hasn't been an issue, but validating the data and relating this data to individual well production rates in a coherent, consistent and timely manner and then taking prompt action, is a challenge. Traditional routine well testing simply provides a series of snap-shots of a well's performance, which may or may not reflect the production during the intervening period. Errors are typically spread across the wells and reservoirs through a reconciliation process comparing estimated well productions and actual metered sales on a weekly or monthly basis. This paper describes the development and application of a new tool, FieldWare* PRODUCTION UNIVERSE * (PU)1, which estimates real time well production rates from simple field measurements and provides online reconciliation against bulk measurements and export meters. The novel aspect of the technique is that it uses dynamic, data-driven models to describe the production process, together with a new well test methodology for capturing the data to build the initial models. Well tests include a deliberate disturbance to the production to determine the dynamic characteristics of a well. The models do not require underlying physical or process models, predetermined multiphase flow correlations, compositional data or well/piping/equipment details. This has made the models quick to set-up and easy to maintain. FieldWare PRODUCTION UNIVERSE is now fully operational and used for well-by-well production surveillance and monitoring at many of Shell's production facilities worldwide, both onshore and offshore. The application of PU has helped increase production through improved monitoring, resolved hydrocarbon allocation problems through real time reconciliation, allowed an increase in time between well tests and reduced travel to field locations. The availability of real time production data is a key enabler for future smart optimization and intelligent diagnostics. PU is a foundation element for Shell's Smart Fields initiative.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 37 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
