oil and gas forecasting reserves management software graph

The Most Common Errors Used to Create Type Wells for Oil and Gas Forecasting

Author: Randy Freeborn, P.Eng., Chief Research Engineer

Studies have shown that the most common method for creating type wells for use in forecasting wells consistently leads to the overestimation of reserves. Some studies have shown these results to be off by as much as 25%. My work with hind casting studies shows those type wells are more likely to overstate EUR, and by an amount as high as 40%.

This becomes a problem because these errors are used to guide important capital decisions within an organization, and can lead to poor allocation of resources or decreased investor confidence. When times are good, companies can overcome such bad projections with higher pricing. But in times like these, overspending on capital projects like plants or extra drills could result in bankruptcy. It’s time to look at these common errors inherent in the standard way of doing type wells and learn how to avoid them.

Forecasting groups instead of grouping forecasts

When only using history, we average representative wells first and then forecast from the average – I call this forecasting groups and it can affect forecast integrity.

Instead, we should first forecast all the wells individually, and then average – in other words, we should group forecasts, not forecast groups. By forecasting each well first, we are given more opportunity to see trends develop. Forecasting from an averaged group tends to mask trends. Forecasting individual wells has the added advantage of having forecast differences in some wells offset the differences in other wells.

forecasting groups vs group forecast type curves decline analysis oil and gas forecasting reservoir management systems

In the example above, I used a decline and type curve software to hind cast 9 wells that produced for 27 continuous years. I truncated the history to 8 years to build a type well, and used the remaining 19 years to confirm the results. The white line shows the type well one would choose using the common method of forecasting from the grouped results. The blue shows the actual data for the full 27 years. The yellow line shows the type well one would choose using the recommended grouped forecast method. As you can see, there is a tremendous difference between the effectiveness of the two methods.

Depleted wells and declining well counts

The other error in creating type wells results from shifting the time scale before averaging so that all wells start producing at the same time. At various times, wells will no longer have data to average; either because they have been depleted or have produced for fewer months than the other wells. In both cases, there is a “Survivor Bias” or focus on the wells that survive.

There is an unintended consequence when the well count is reduced, which is that the type well rate behaves as though the depleted or shorter history well continues to produce at the average rate. When that happens, you get a spike or drop in the type well due to the shrinking number of wells in the sample.

monthly production rate forecast errors table drill well field total

Here’s a simple example to illustrate survivor bias. Three wells are used to create a type well, which will in turn be used to predict the performance from three undrilled wells. Both should have the same total field rate. The type well rate is the field rate divided by the number of wells with data to average: 3 for 2 months, then 2.

To use the type well, we multiply the type well rates by the 3, the number of wells we plan to drill. We do not multiply by 3 until the end of month 24, then multiply by 2 because the number of wells in the type well decreased. Comparing yellow numbers in the “drill 3 wells” row to the “field total” row, demonstrates that the common method of creating a type well inherently assumes that a well without production will produce at the type well rate. Clearly, that’s not logical and can result in an overstatement of EUR.

The Answer: Forecast Wells First

These are errors inherent in the common method of doing type wells. Not mistakes made by bad engineering, but rather flaws in the process itself. The solution for all of them is to change how you do type wells: forecast EVERY well first, then group those forecasts together to make your type well. Doing so will better identify trends in ALL wells in the sample and remove the errors associated with survivor bias.

In the past, it wasn’t feasible to forecast every well, which is why the common method became the standard method. Concessions were made due to the labor-intensive methods for creating forecasts of the past. Modern software solutions make forecasting wells much faster, thereby allowing engineers to create better, more reliable type wells when they forecast first, then average the history and the forecast.

If you are interested in learning more, we invite you to visit 3esi-Enersight (booth #601) at URTeC in Austin, TX, July 24-26th! 3esi-Enersight is presenting this paper and several other technical presentations designed to maximize your development of unconventional resources.

Randy Freeborn SPE Distinguished Lecturer

About the Author

Randy Freeborn is a Distinguished Lecturer of the SPE on the subject of type wells and a subject matter expert in empirical forecasting and related technology. Currently, he is Chief Research Engineer at 3esi-Enersight where he is responsible for identifying and inventing reservoir engineering technology for inclusion in our Value Navigator software. He has been a professional engineer for 43 years and is a member of the Society of Petroleum Evaluation Engineers (SPEE) and the Society of Petroleum Engineers (SPE). He has given guest lectures at the University of Houston and Texas A&M, and has been called as an expert witness.