Quantitative Assessment of Optimal Completion Philosophy in Coal Seam Gas

Developing the best solutions to problems requires an understanding of the solution space. As the problem complexity increases the solution space also tends to become more complex and is consequently more important to understand. A model is often a highly effective way to explore the solution space and develop optimal solutions.

Open hole slotted liner completions in the coal seam gas industry is an example of such a problem where there are multiple competing objectives. At a high level the goal is to use as few parts as possible, achieve perfect coal exposure and perfect isolation of non-coal (read more about isolation). Intuitively, the optimal completion will be a balance of addressing each of these individual objectives. The question is, what is that balance? More specifically we want to know:

1. What does the solution space look like in relation to interburden isolation, coal exposure and part usage?
2. What is the best location in our solution space according to economic analysis?
3. What inputs map to the best location?

To answer our questions, we need a model of the solution space that we can use to conduct an economic analysis. AlphaTally is generally used live in the field to develop the completion tally to be installed downhole but it also allows us to conduct analysis from historical input data to make informed decisions about future drilling and completion target philosophies.

The solution space for this analysis is constructed from 14 philosophies (doing this for real we would be looking at great than 500 philosophies). The 14 philosophies are bounded by triangle formed from using as few parts as possible, achieving the best isolation possible, and exposing 100% of the coal. Of these 14, philosophy 0 represents the approach that we would be applying based on my judgement and experience with AlphaTally.

Using AlphaTally to generate the casing tallies for a series of example wells under the 14 philosophies produces a solution space that the two plots below summarize. As we expect, increasing part usage improves coal exposure and interburden isolation.

Additionally, interburden isolation is inversely related to coal exposure.

Now that we have information about the solution space we can apply an estimated economic value to each of our objectives. It is important to recognize these are illustrative values and if you conduct your own analysis these values would change to reflect your operations.

Applying our cost estimates, we produce the following box plot which shows the outcome for each of our example wells under a sample completion philosophy. It shows the spread of performance of each completion philosophy across the sample of wells in the study. The ideal philosophy has a median marginal estimated cost of $0 and a tight spread. Based on this analysis we would change from our original philosophy (philosophy 0 - yellow) to philosophy 9 (blue) for our future wells because it will produce outcomes closer to what we defined as the ideal completion.

How does knowing the ideal philosophy add value? Even in our simplified solution space, this analysis revealed adopting philosophy 9 on average will add $4500 in value to each well we drill compared to my initial philosophy (Philosophy 1). You could argue that we just had poor judgement of the initial philosophy, or simply rigged it to get an attractive looking outcome.

To show this is not the case, below is a plot as above but with a subset of 30 philosophies bounded by the newly selected philosophy 9 (we are exploring the region of solutions around the selected philosophy by adding granularity to each of the inputs). Philosophy 9 that was selected in the first analysis is labelled as philosophy 0 in this plot and shown in blue. Once again, we get a further improvement in the median performance of $500 per well by selecting philosophy 3 (green). More significantly, this change further tightens the performance spread, reducing the 3rd quartile value by $800 per well. The law of diminishing returns is at play here (the step is less than the original improvement), but this solution space is complex, and we can reasonably expect to continue to get improvement by further exploring the solution space.

Conducting analysis of complex problems requires models of the solution space to effectively explore the landscape. Until AlphaTally was created, there has been no available model to explore the optimal philosophy for open hole slotted liner completions of coal seam gas wells. As we have demonstrated here, the value that can be unlocked by determining the ideal philosophy can potentially be very significant. If you would like to learn more about how Endla and AlphaTally can help you find your optimal philosophy get in contact with us using the form below.