Production forecasting principles and definition

A sound production forecast is the basis for any project-based resource estimate, and the same production forecast is also the basis for any business or development decision. Thus, forecasting aligns resource estimation, decision making and business planning and perhaps even operational short-range forecasts.

Principles

• At any point in time, there is only one best estimate forecast for a project that reflects the current understanding of subsurface uncertainty and best development and commercial assumptions.
• This forecast should always be accompanied by an uncertainty range.
• The forecast uncertainty range should always have remaining reserves or EUR as an objective function.
• The forecast and uncertainty range should be based on defined projects, with incremental forecasts for subsequent projects.

With these principles, forecasting is part of asset management throughout the year. It may be envisaged as a continuous loop through the whole upstream lifecycle Fig 1. Forecast updates are triggered by reserves and corporate planning, but also by ad hoc changes and events, such as studies and subsurface information and development plan updates. Note that for the official forecasts (reserves and corporate planning), reasonable freeze dates should be agreed upon for input data and should be adhered to. Subsequent changes due to new wells, workovers or wells failing should be reflected in the ad hoc updates, The forecast model is kept up-to date and consistent with the latest surveillance data and development assumptions and when reserves or corporate forecast need to be updated, it may simply be derived from the latest model.

Hagedorm's paper Integrated Reservoir Management Via Full Field Modeling, Pt. McIntyre Field, Alaska is a good example of keeping a model evergreen and managing all decision with that single model.

INSERT Figure 1 - Forecast as a continuous loop through the field lifecycle (Pending permission approval)

Definitions

The following definition of forecast uncertainties is based on the PRMS definition of resource uncertainty, but broadens it to also address forecast uncertainties in the short and medium term (thus the whole time line). This forecast definition will enable a lean forecasting process by allowing for a single, consistent forecast that will be the basis for resource estimation, decision making and business planning. The basic principle is that for any given project and subproject, there is a single “best” forecast and a single best uncertainty range that describes the imperfections in the input data and fully captures the current risks and upsides of the forecast.

Low (P90) Forecast is defined as:

P90 with regard to cumulative production at end of field life (EOFL)

Reasonably certain (P90) with regard to schedule, ramp-up, system capacity and system availability

With a consistent reasonably certain model from start of forecast to EOFL

Best Estimate (P50) Forecast is defined as:

P50 with regard to cumulative production at end of field life

Best Estimate (P50) with regard to schedule, ramp-up, system capacity and system availability

With a consistent best estimate model from start of forecast to EOFL

High (P10) Forecast is defined as:

P10 with regard to cumulative production at end of field life

Optimistic Estimate (P10) with regard to schedule, ramp-up, system capacity and system availability

With a consistent optimistic model from start of forecast to EOFL

Notes

• Forecast uncertainty ranges may be derived probabilistically or by deterministic scenarios, but they must always cover both the long term and the short term uncertainties Fig 2.
• The low case (P90) forecast therefore combines the low case in ultimate recovery (or remaining reserves) with a low case in project delivery and system availability. The “consistent model” could be a simulation model or IPSM (integrated production system model), but it could also be a decline curve or proxy model that combines the near-term uncertainty with the low (P90) case for ultimate recovery.
• Making the best estimate forecast with an IPSM and the low case with a decline curve model could still be considered a “consistent model” if properly justified; however, making the first two years with a decline curve model and the out years with an IPSM would not be considered a consistent model.
• Forecasting methods, such as decline curve analysis, type curve analysis, material balance, analog methods, simulation models and IPSM.
• How to establish forecast input uncertainty, with respect to subsurface, activity scheduling and system constraints.

INSERT Figure 2 -Uncertainty range derived probabilistically (left) or with three distinct deterministic scenarios (right).  (Pending permission approval)

For new projects (i.e., green field or incremental projects within a brown field), a key uncertainty is the first oil date. The definitions explicitly allows for this uncertainty to be included Fig 3 . This may have implications for reserves. For example, if the field has a fixed term contract of 20 years, then the low (P90) forecast will be aborted earlier and the low (P90) ultimate recovery will be even lower.

INSERT Figure 3 - Uncertainty in production startup (Pending permission approval)

The definitions fulfills the following criteria

The definition fulfills the following criteria, as will be shown by the examples covered in the Production forecasting frequently asked questions and examples:

• Ensures consistency between the corporate forecast and reserves and resources estimation (Examples 1 through 10)
• Applicable to any time horizon, short and long term, with long-term and short-term uncertainties equally weighted (Example 5)
• Applies to all phases of the field lifecycle, from exploration (Examples 1 and 2) through to abandonment (Example 7)
• Consistent with corporate forecasting and any decision-based forecasting (Examples 1 and Example 2)
• Allows for aggregation and comparison of forecasts across the whole company (Example 4)
• Provides a common forecasting language for the whole industry , for Acquisition & Divestment work and joint ventures, it will benefit the industry if all companies are working with the same definition (Example 3)

Noteworthy books

Society of Petroleum Engineers (U.S.). 2011. Production forecasting. Richardson, Tex: Society of Petroleum Engineers. WorldCat or SPE Bookstore

External links

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

See also

Production forecasting glossary

Aggregation of forecasts

Challenging the current barriers to forecast improvement

Commercial and economic assumptions in production forecasting

Controllable verses non controllable forecast factors

Discounting and risking in production forecasting

Documentation and reporting in production forecasting

Empirical methods in production forecasting

Establishing input for production forecasting

Integrated asset modelling in production forecasting

Long term verses short term production forecast

Look backs and forecast verification

Material balance models in production forecasting

Probabilistic verses deterministic in production forecasting

Production forecasting activity scheduling

Production forecasting analog methods

Production forecasting building blocks

Production forecasting decline curve analysis

Production forecasting expectations

Production forecasting flowchart

Production forecasting frequently asked questions and examples

Production forecasting in the financial markets

Production forecasting principles and definition

Production forecasting purpose

Production forecasting system constraints

Quality assurance in forecast

Reservoir simulation models in production forecasting

Types of decline analysis in production forecasting

Uncertainty analysis in creating production forecast

Uncertainty range in production forecasting

Using multiple methodologies in production forecasting