The focus of this blog post is the influence of stress on the Eagle Ford Shale Play in the Gulf Coast Basin. By using a few data points from the suite of data offerings from Drillinginfo, as well as some open source data taken from the geoscience community, some quick and confirming observations can be made.
The direction of the drill
The first step in this analysis was to take the azimuth value for all Eagle Ford horizontal wells. This is computed by taking the geometric orientation from the surface hole location to the bottom hole location of each well and reference to true north.
In order to quality check the azimuth orientations I also brought in some actual wellbore trajectories. These trajectories are taken from database of digitized directional surveys – another new data offering provided by Drillinginfo.
Stress patterns of the geology
Next, I visited the World Stress Map (WSM) website to download and map the tectonic stress orientations pertinent to my study area. If you’re unfamiliar with the WSM database, there are four types of stress indicators used to determine the orientation of tectonic stress:
- earthquake focal mechanisms
- wellbore breakouts and drilling induced fractures
- in-situ stress measurements (overcoring, hydraulic fracturing, borehole slotter)
- and young geologic structural data from fault-slip analysis and volcanic vent alignments.
All WSM data is sourced from Heidbach, O., Tingay, M., Barth, A., Reinecker, J., Kurfeß, D. and Müller, B., The World Stress Map database release 2008 doi:10.1594/GFZ.WSM.Rel2008, 2008. (https://dc-app3-14.gfz-potsdam.de/pub/stress_data/stress_data_frame.html)
A first look
The map below shows only Eagle Ford horizontal wellbore trajectories and the closest stress orientation measurements were taken just to the north of the core play area in Frio County. There are actually a couple of measurements taken from this point. The first is from the well bore breakout orientation and the analysis of individual breakouts in the Olmos field. This particular measurement provides a stress azimuth orientation of 119 degrees from true north. The second measurement comes from drilling induced fractures of the borehole wall in the Austin Chalk. The azimuth orientation of this measurement is 127 degrees.
For a closer look I’ve zoomed in on the central portion of the play to get a better depiction of the orientation of the wells.
For the most part, one can observe spatially the wellbore orientation does have a relationship with the orientation of stress on the rock. To take this observation a bit further, we can look at the impact of the well’s lateral orientation to production.
The series of box plots below show all Eagle Ford wells, oil window, and condensate window and their azimuth orientation in eight separate bins in 45 degree increments. Peak rate, or the max month of production (usually the second month of production for the well), is the production metric used. Using the peak rate provides the most complete dataset.
Well completion data is not taken into account in this observation, which could be a reason that the 90 to 135 degree bin does not have the highest median in the oil window. However, it also possibly indicates the importance of planning wellbore trajectories perpendicular to fractures, which is a product of stress. That segues into the impacts of faults and the effects that has not only on production of hydrocarbons but also that of water.
For further analysis I visited the Mineral Resources On-Line Spatial Data website provided by the USGS at https://mrdata.usgs.gov/geology/state/state.php?state=TX. The fault data that I downloaded is for Texas specifically and only shows surface faults. However, for the purpose of this post, it provides interesting results when comparing a group of well’s performance with proximity to a major surface fault. The first step was to spatially tag wells that are within a 1 mile buffer zone of a fault and then to tag wells within a 5 mile buffer zone of a fault. I’ve clipped only the faults that are within the Eagle Ford play areal extent. See the map below.
I used cumulative three months water production since it provided the largest and cleanest dataset to work with, same as with using peak rate. While this is not exactly ground-breaking analysis and most of this is common knowledge, it is interesting to see the results shown with actual data and go through some basic workflows to make these observations.
Please feel free to provide any personal insights or remarks in the comments section below.
What do you think? How much of a part does stress play in your well plan? Leave a comment below.
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