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Production forecasting activity scheduling
Activity scheduling is an important, integral part of production forecasting that can have a significant impact on the reliability of the forecast. Once the subsurface input has been established and agreed upon by multiple disciplines, the production forecast should be created taking into account system constraints, scheduled and unscheduled downtime and new activities such as well and field optimization, changes to facilities capacity or design and new wells and developments coming on production.
Future development programs are a major component of activity scheduling. The timeline and production impact of the drilling program is estimated and layered onto the existing baseline forecast (commonly known as the “no further activity forecast”). This is typically done using type curves or a simulation model because the wells are not yet on production. The forecast for these activities needs to be truly incremental, ie. Account needs to be taken of any interaction/impact the activity may have on the baseline forecast.
The timing and duration of development activities can depend on a variety of factors and usually carries significant uncertainty. When scheduling 1st production dates, the forecaster should consider all factors that may come into play: economics, weather, landowner approval, rig availability, regulatory constraints, and facilities capacity are a few examples. Historical data and analogs will help add confidence when scheduling new wells and developments in both short-term and long-term forecasting and the uncertainty around this.
Usually activities are designed to increase production from an asset however it should be recognized that activities can also have a short term negative impact on production, known as downtime or deferment, while they are being undertaken. This includes plant turnarounds, maintenance work, well workover and stimulations, shutting in offset wells during drilling and completions and facilities tie-ins/construction. Projects such as these are typically pre-approved and scheduled so any associated downtime can be explicitly modeled in the production forecast, but the uncertainty in the timing and duration of these activities should be recognized. See the section on system availability and deferment for more detail on planned and unplanned deferment.
Optimization projects (at the well level and also field wide initiatives) can be scheduled into short- and long-term production forecasts. Some optimization opportunities are only scheduled once the need is apparent or the economic benefit has been demonstrated. For example, if a gas well begins to liquid load, one might plan artificial lift for the upcoming year. If a well shows signs of restricted flow, a scale treatment might be scheduled. Although these are often reactive projects, the use of analogs and historical data can help to estimate when such projects may be required. Using a similar approach to unplanned downtime (discussed in system availability and deferment), one may look at historical data to predict the point at which artificial lift or scale treatment may be required. Similarly, one may plan for field-wide optimization years in advance if analog fields support the initiative. Some examples of projects would be installation of a booster gas compressor, implementing a waterflood or other types of secondary or tertiary recovery. When representing optimization projects within a production forecast realistic estimates of lead time and associated deferment should be taken into account. It should be checked that such activities are realistic and likely to be economic, and approved, before assuming they will occur in a best estimate forecast. If planned projects do not yet meet reserves criteria in terms of project maturity as set out in PRMS, associated production and ultimate recovery should only be represented as contingent resources in the forecast.
The key is to understand the problems that may arise in your field because each is unique, and be prepared for how these problems may affect your production and ultimately the accuracy of your forecast.
In some cases, flush production may be included in a forecast when a well comes back online after being shut in for a length of time, due to pressure recharging and stabilization of flood fronts. In a gas field with accurate SCADA measurement, flush production is easy to quantify and can contribute a significant production volume. Historical data and reservoir analysis can be used to quantify likely flush production. In many fields, however, an increase in production is not possible. In an oil field, if the wells are optimized and pumping at maximum efficiency, then even though the fluid level in the wellbore may have risen during the shut in, the pump is unable to produce any additional fluid. Therefore, flush should not be included in the forecast in this case. If the pump is at low efficiency and is able to accommodate the increased fluid volume, however, there may be flush production forecast. Frequent and accurate well testing would be essential to quantify oilfield flush production, and should be taken into consideration while forecasting such an event. Unless a regularly witnessed phenomenon in a field, it may be prudent to categorise flush production as a potential upside rather than part of a base forecast.
In the end, most activities scheduled into the forecast will have an inevitable amount of uncertainty. Studying historical data and using analog fields whenever possible can maintain this uncertainty at an acceptable level. Furthermore, a collaborative approach to forecasting that incorporates feedback from operations, production, and reservoir engineering will increase consistency between the short-term forecast, the long-term forecast, the budget, and the reserves volumes assigned to the field. Integrated production system modeling further discuss the use of an IPSM and the benefits of a collaborative approach to forecasting.
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