Instilling Realism in Production Forecasts: Dos and Don'ts
- Avnish K. Rajvanshi (Petroleum Development Oman) | Robert Gmelig Meyling (Petroleum Development Oman) | Danny Ten Haaf (Petroleum Development Oman)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 8-10 October, San Antonio, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2012. Society of Petroleum Engineers
- 4.3.4 Scale, 5.5 Reservoir Simulation, 2.2.2 Perforating, 5.2.1 Phase Behavior and PVT Measurements, 4.2 Pipelines, Flowlines and Risers, 5.1.5 Geologic Modeling, 5.1.1 Exploration, Development, Structural Geology, 5.5.8 History Matching, 5.5.2 Core Analysis, 5.6.9 Production Forecasting, 1.6 Drilling Operations, 7.1.10 Field Economic Analysis, 7.1.9 Project Economic Analysis, 5.4.1 Waterflooding, 5.7.2 Recovery Factors, 5.8.7 Carbonate Reservoir
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Historically, and across the E&P industry, several projects were found to underperform in their actual performance as compared to the promises made at the time of project approval. Investment decisions on upstream projects rely, to a large extent, on the robustness of the predicted ultimate recovery and production forecast associated with the chosen development concept. A 2010 upstream industry benchmarking consortium reviewed global performance of E&P projects and concluded that the majority of production forecasts presented at project approval were not attained. In many cases, this underdelivery resulted in eroded project economics and reputation damage with stakeholders.
The challenge for the E&P industry is to ensure that project approvals are based on realistic forecasts (P50 case). Modern technology has offered a paradigm shift in the amount of detail which can be included in the subsurface static and dynamic models. However, a universal truth is that no single model is the perfect representation of reality, and the recovery processes based on modelling are, therefore, always approximations of real life situations. Simulation models are guiding tools rather than sources of perfect answers.
This work is intended to increase awareness amongst the forecasters and the decision makers about pitfalls associated with production forecasting (especially those generated by dynamic models). It provides insight into the need to condition model input data or alternatively the model output to ensure that forecasts and resource volumes generated by these models are realistic. Root causes of unrealistic forecasts are identified. Dos and don'ts are described that help instil realism in the forecasting process. Pragmatic techniques to adjust the output obtained from dynamic modelling are illustrated using real-life examples.
This work presents a pragmatic approach to create reliable long-term production forecasts which can form the basis for sound business decisions.
Historically, most projects in the E&P industry have seen under-delivery against business plan forecasts and production growth targets. Recently, an industry benchmarking consortium concluded the sixth of a series of long-term production attainment studies, which reviewed the production profiles of 59 major development projects from different hydrocarbon producing regions (Nandurdikar and Wallace, 2010). For the majority of projects, the forecasted production was not achieved.
|File Size||767 KB||Number of Pages||12|