Well Spacing (with Insights into the DJ Basin)

What is the biggest unknown in unconventional horizontal plays now? It is what is the correct spacing to use to generate either the highest $NPV or highest IRR depending upon the company. It is this question that is causing so much angst, corporate consolidations and is having a ripple effect across the economy beyond the oil & gas industry. Developing a section of land can now cost upward of $100 MM. It is no surprise that this kind of capital investment can only really be done by integrated oil companies. Banks are restricting lending for this kind of drilling which impacts small and mid-sized independents equally.

What is to be done about it? Big data analytics is all the rage right now. It takes seemingly disparate data points and aims to predict performance. However even the best AI right now can only explain 30 to 40% of the variability in EURs across individual plays. Important causal factors from this include frac sand/water loading and reservoir quality among others. However, if even this cutting-edge technology can’t fully explain the variation to a robust 60 or 70%, we are forced to rely on field experimentation. I would argue that simple statistical methods such as cumulative probability charts are a great way to take a mass of data and make it mean something. The downside of such a technique is that it doesn’t handle multiple variable changing very well. Still big data analytics seems to point to just a couple of causal factors, so this method should work well if the user is cautious about parsing the variables.

I am going to talk about the DJ Basin next since that is where my most recent experience is from. Every basin and zone are going to have individual characteristics that will make it differ from the DJ, but this basin has the benefit of having a large number of wells drilled in varying GOR and having experiments with different kinds of completion techniques and sand loadings.

In the oil leg of the DJ Basin (NE Extension), experiments were done with up to 16 wells per section (WPS). With cumulative probability charts it was found that 8 WPS was the optimal spacing to use when sand loadings were around 900-1200 lbs/ft. When the frac size went up to 1500-3000 lbs/ft, the optimal well spacing dropped to 6 WPS. This makes complete sense because the frac energy per unit area is going up rapidly. In a previous article I talked about how only so much frac energy can be used due to local natural fracture networks growing together.

As we move to a higher GOR area, the optimal well spacing was found to be 12 WPS (dropping to 8 WPS) with the use of higher frac sand loading. It was also found that areas of the DJ that had vertical wells (up to 32 per section) outperformed areas without vertical wells by 5 to 10%. This is a bit counterintuitive. How could an area with depletion outperform an area that didn’t have depletion? The simple answer is reservoir quality. In areas with vertical wells, the reservoir quality was high enough to allow for vertical wells to produce in economic quantities. This translates to horizontal wells having higher RQ. This same effect can be seen in the Cleveland play of the NE Texas Panhandle.

What is the answer? Beyond using statistical techniques to identify causal factors, there isn’t much else that can be done beyond what is being done already. It is a headache to all of us, but I don’t see any simple answers. Hopefully AI will develop in our industry to the point that this complex problem can be solved.