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Establishing input for production forecasting
The production forecast should be consistent with the current reservoir drainage strategy and should include production from existing and new wells, side-tracks and well interventions. A reservoir drainage strategy should cover the following aspects related to the production forecast:
- Hydrocarbon phases initially in place.
- The amount of hydrocarbon that has been produced and is remaining.
- Spatial distribution of remaining hydrocarbon, saturation and reservoir pressure distribution.
- Current understanding of ultimate recovery factors.
- Activity timing and recovery methods to be applied to produce remaining hydrocarbon volumes.
The subsurface input for the production forecast should provide sufficient understanding about:
- Reservoir description
- Reservoir drainage strategy
- Well performance
The following key reservoir description data should be considered to establish reliable production forecasts:
- Reservoir structure.
- Faulting and flow barriers.
- Sand connectivity.
- Reservoir properties: porosity, horizontal and vertical permeability, and net-to-gross ratio.
- Fluid saturation and reservoir pressure distribution.
- Fluid PVT properties (API, viscosity, GOR, bubble point).
- Dynamic SCAL input (relative permeability and capillary pressure).
- Reservoir Heterogeneity (variation in reservoir properties across the field).
- Aquifer properties (strength and location).
- Drive mechanism (water, gas, depletion, compaction, gravity drainage).
Short-term forecasts are most dependent on activity levels (number and timing of new wells and well interventions), while long-term forecasts are more affected by reservoir type and the above-mentioned subsurface assumptions.
The above reservoir description should be based on all available field data, the quantity and quality of which will vary considerably from asset to asset depending on field location, maturity and the level of appraisal and surveillance. Key data includes 2D/3D seismic, well logs, PVT analysis, core analysis and well tests.
Reservoir drainage strategy
The production profiles and ultimate recovery from a field are affected by the following:
- Selected reservoir depletion plan.
- Well placement and well types.
- Reservoir management scheme.
- Improved recovery methods.
- Production start-up and build-up assumptions.
Static and dynamic reservoir understanding, G&G and petrophysical interpretations, reservoir modelling and detailed analysis of both the reservoir and well performance are key factors in establishing the most optimal drainage strategy.
A correct estimate of well performance is one of the most important factors affecting the quality of the production forecasts. Key factors to consider are well design and completion methods, well spacing, infill drilling, sand production and need for artificial lift.
Voidage replacement is an important parameter affecting long-term reservoir pressure and well performance. To focus on production and to establish a forecast for future injection is an important part of the field forecast. The following issues are important to address:
- Current voidage situation.
- Reliable estimates for reservoir pressure decline and potential impact on:
- Increased lift requirements and need for lower wellhead pressure.
- Sand production problems.
- Future drilling problems in heterogeneous reservoirs.
A thorough multidisciplinary uncertainty analysis should be performed to address uncertainties involved in all significant and relevant parameters, including uncertainties related to geological interpretations, reservoir deliverability, well performance, well intervention activity, new wells and production efficiency, including planned turnarounds and capacity constraints. It is important that each asset evaluate which elements are the most important contributors and ensure that these uncertainties are included in the analysis. Chapter 4 addresses different approaches to this uncertainty analysis.
Noteworthy papers in OnePetro
Jalilova, N., Tautiyev, A., Forcadell, J., Rodriguez, J. C., & Sama, S. 2008. Production Optimization in an Oil Producing Asset - The BP Azeri Field Optimizer Case. Society of Petroleum Engineers. http://dx.doi.org/10.2118/118454-MS.
Okoh, E., Sathyamoorthy, S., Olaniyan, E., & Ezeokeke, O. 2010. Application of Integrated Production System Modelling in Effective Well and Reservoir Management of the Bonga Field. Society of Petroleum Engineers. http://dx.doi.org/10.2118/140632-MS.
Roadifer, R. D., Sauve, R. E., Torrens, R., Mead, H. W., Pysz, N. P., Uldrich, D. O., & Eiben, T. 2012. Integrated Asset Modeling for Reservoir Management of a Miscible WAG Development on Alaska. Society of Petroleum Engineers. http://dx.doi.org/10.2118/158497-MS.
Production forecasts and reserves estimates in unconventional resources. Society of Petroleum Engineers. http://www.spe.org/training/courses/FPE.php
Production Forecasts and Reserves Estimates in Unconventional Resources. Society of Petroleum Engineers. http://www.spe.org/training/courses/FPE1.php