With the rise of unconventionals and the increase in wells permeating already tapped fields, Well Spacing has become the hot topic du jour. But, what is well spacing? Does it refer simply to how many wells are in one area? If so, is that area defined by a circle or rectangle or other definition? What is the make-up of the nearby wells? Today, we will examine some common terms and approaches to analyzing well spacing.
Two templates that utilize the features that we will discuss in today’s post are Well Spacing Feature Calculations and Horizontal Well Spacing Model.
Key terms we will discuss today: Voronoi Diagram, circular and rectangular radius, Area of Interest, intersect area, intersecting wells, closest wells, closest distance, aggregated well statistics.
In analyzing Well Spacing, reservoir engineers naturally first look at the wells nearby. How many are there, which is the closest one, what are the common characteristics, how are they performing? To answer any of these questions, we must first define an Area of Interest (or Influence), whether that be with a rectangular buffer, a circular radius, or any other partitioning method.
Our Horizontal Well Spacing Model template creates a rectangular buffer based on a user input around every well, then counts the buffers from other wells that intersect it.
Not only that, it can partition wells by time and formation…
This way, we are only counting wells that actually affect the well in question because they are both producing at a shared depth at the same time.
Voronoi Diagrams provide another approach to defining an area around a well by partitioning points using the Voronoi Tessellation algorithm. The algorithm creates an area around a well that includes any point closer to that well than any other well.
We can also calculate the Voronoi Diagram over time, allowing us to look at how the inclusion of new wells has affected the calculus.
Above, we see a table with variables for how long the field has been in production, the total acreage, and how many wells are in production during the selected time point. The actual Voronoi Diagram visualization will represent that point in time.
Our Well Spacing Feature Calculations template, which creates the above Voronoi Diagrams, also uses a user inputted radius to create a circular Area of Interest, or neighborhood around a well. While the Voronoi diagram only includes one well per area in an effort to provide maximum spacing, a neighborhood incorporates the closest wells in an effort to identify trends and proxies through aggregation.
Below, you can see how the template shows the wells within the neighborhood both in a map visualization and as a list of APIs.
With a neighborhood defined for each well, we can perform a neighborhood analysis, aggregating statistics for the wells that intersect the circle. Let’s take a look at different parts of the header for the output table in this template:
We see above that, for each well, we get info on the distance to the closest well and what well that is. We also get basic information on the neighborhood we have created for our well such as the radius size and area.
Additionally, we get info on the amount of wells and operators in the neighborhood and information on how many started production before and after the selected well.
Finally, the template creates aggregate statistics for the wells in the neighborhood created from the completion data. This helps creates proxies for the selected well. We then can run a variety of analyses on the effect that changes in different variables in different groups have on production.
The Horizontal Well Spacing Model template also has the ability to create aggregate variables as well spacing features:
This template has the added functionality of letting you choose which variables you want to aggregate.
So, we have seen there are many ways one might determine an area around a well like rectangular buffers, circular radii, and Voronoi Diagrams. Also, areas around a well might serve different purposes. Voronoi Diagrams only include one well and can guide optimal spacing while our rectangular and circular areas can give information on intersecting wells. We can count, tally, or measure many variables in those areas like total area, closest well distance, and number of wells and operators. Also, there are many aggregations that we can do to get a feel for the comps of surrounding wells using variables like Avg Horizontal Length, Total Proppant, Perforated Interval Length, and Stage Count.
Today, we examined common terms and metrics related to well spacing and how to measure them. Check out the Horizontal Well Spacing Model and Well Spacing Feature Calculation templates. In a follow up post, we will look at how those well spacing variables affect production.
Jason is a Data Scientist at Petro.ai with a master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Support Vector Machines. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.