Quality assurance in forecast

Given the important role production profiles play in key decision making and the inherent uncertainty and bias existing in the process of building them, it is essential that the QA/QC process is sufficient to test the robustness of the forecast range and ensure there is a shared understanding and buy-in of the assumptions behind it across the stakeholders involved in an asset. Different ways to try and ensure the quality of the forecast are as follows:

Peer review

Getting other qualified professionals not directly involved in the development of this particular forecast to review inputs, methodology and outputs of the forecast. This is a powerful tool, particularly in mitigating the effects of human bias. Each reservoir and development is unique so there are likely to be different approaches that should all be considered.

Benchmarking

As has been mentioned throughout this document, it is essential to compare your forecast to the historical production of the field if it is already on production and appropriate analogues if it is not in production. This should include plateau length and production rates as well as individual well rates, decline, response to injection and recovery factors. If your field is already on production it is still useful to make a comparison of this production and the forecasts from developed models against more mature analogous fields. The use of analogues is discussed in more detail in production forecasting analog methods.

Audit trail

The purpose of an audit trail is to clearly state the assumptions and decisions underpinning the forecast so that it can be understood and replicated if necessary. Unfortunately, historically this has not always been done which prevents lessons being learned and improvements identified and implemented. Documentation is discussed in more detail in Documentation and reporting in production forecasting.

Look backs and forecast verification

Key to an effective improvement process is documentation of forecast cases to a level sufficient to understand the assumptions and replicate the results, regular comparison and reconciliation of actual results against predictions and a determination of the root causes of variances to determine process improvements. These improvements must be implemented so that subsequent forecasts improve. Look backs and forecast verification shares industry look back data, highlights some significant causes of poor forecasting and provides advice on implementing a successful look back process. Appendix C gives more detail on Forecasting Diagnostics workflows that can be applied as part of this process.

Noteworthy books

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

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