SPE Denver General Meeting: November 2025

General Meeting Category: Reservoir

Speaker: Reidar Bratvold, Professor Emeritus, University of Stavanger

Title: Persistent Bias in Probabilistic Production Forecasting and Simple Methods to Overcome It

Abstract:

The one key idea I would like the members to take away: Unbiased probabilistic production forecasts are a crucial component in making good investment decisions — but typical ways of producing them result in persistent, value-destroying biases. There are quick and easy ways to make accurate, unbiased forecasts.

Increased awareness of uncertainty, combined with increasingly sophisticated tools and models for quantifying it, is causing a shift from deterministic to probabilistic production forecasting. For these forecasts to lead to better investment decisions (e.g. assessing how much it’s worth paying to reduce uncertainty, or incorporating flexibility to manage it), they need to be an accurate (unbiased) representation of the uncertainty. However, our industry has a general history of overconfidence (ranges too narrow) and, more damaging for value-creation, optimism (consistent over-estimation).

A large dataset of historical probabilistic production forecasts was investigated for potential bias by comparing them with actual outcomes. They were found to be both optimistic and overconfident, bringing into question their usefulness for decision-making and the value of the sophisticated uncertainty modeling techniques that were used to generate them.

Fortunately, there are quick and easy methods for creating accurate probabilistic forecasts. We describe these and show that they would have produced accurate forecasts for our case study fields (they do not make use of knowing the actual outcomes!).

Finally, preliminary results from a similar analysis of renewables projects indicate that the same problems exist. This could significantly impact investment decisions and policy development in renewable projects by governments and companies.

Bio:

Reidar B. Bratvold is Professor (emeritus) of Decision & Data Analytics at the University of Stavanger, where he teaches and supervises graduate students in decision and data analytics, including artificial intelligence and machine learning, project valuation, portfolio analysis, real-option valuation, and the behavioral challenges of decision-making. Before joining academia, Reidar spent 15 years in industry in various technical and leadership roles, including Vice President at Landmark Graphics Corporation (a Halliburton company) in Houston; Managing Director of Smedvig Technology Software Solutions (now Roxar); Senior Scientist with IBM; and Reservoir Engineer with Statoil. He began his career offshore as a roughneck and roustabout in the North Sea.

Reidar is a frequent speaker at industry conferences and delivers in-house short courses on decision-making and economic evaluation. He is one of only four individuals to have served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer four times:

• Uncertainty Assessment and Risk Management in Reservoir Optimization (1998–1999)

• Would You Know a Good Decision if You Saw One? (2003–2004)

• Creating Value from Uncertainty and Flexibility (2016–2017)

• Persistent Bias in Probabilistic Production Forecasting and Simple Methods to Overcome It

He has published extensively on topics such as decision-making, the value of information, the application of machine learning and AI to support decisions, Bayesian evidence learning, stochastic reservoir modeling, fuzzy logic, data assimilation, and reservoir management. He is co-author of the SPE book Making Good Decisions, commissioned by the SPE.

Reidar was the 2017 recipient of the SPE Management & Information Award, has served as Executive Editor for SPE Economics & Management, and in 2024 was selected as Energy Professional of the Year by the SPE Stavanger Chapter. He is a Fellow of both the Society of Decision Professionals and the Norwegian Academy of Technological Sciences, and a Founding Member of the Friends of SDP initiative.

He holds a PhD in engineering and an MSc in mathematics from Stanford University and has completed executive education in business and management science at INSEAD, MIT, and Stanford