Ex 3: Relating distance between wells to communication type and fault presence

Question that I asked:

Is there a relationship between the distance between wells, their communication status based on a pumping interference test, and whether or not they are separated by a fault?

Name of the tool or approach used:

Polyline creation and classification in ArcGIS Pro, boxplot creation and two-sided t-tests in R.

Method:

29 wells in my study area were evaluated by the Oregon Water Resources Department during pumping interference tests in 2018 and 2019. This test involves pumping one well, and seeing whether the water levels in nearby wells drop in response. I received a verbal account of the wells that did and did not communicate, sketched it on a map, and then transferred that information to ArcIS Pro. I drew polylines using the well locations as snapped endpoints. Then, I created and populated fields containing the well communication type (“communicate” for wells that respond to pumping at a nearby well, and “does not communicate” for wells that do not) and whether or not the path between two wells crosses a fault. Shape_Length in feet was automatically calculated when I created the polylines, on account of the projection I used for the shapefile.

I exported that data table to a csv and imported it in R, where I subset it into three categories: all paths, paths between wells that communicate, and paths between wells that do not communicate. I then created box plots and ran t-tests to see differences between means and distributions of path length based on communication type or fault length.

Results:

Comparing the path length and the communication type of all 29 wells involved in the communication test, there is not significant evidence of a difference in mean path length between wells that do and do not communicate because the p-value of a two-sided t-test was 0.152. While the mean distance between wells that do not communicate is larger than the mean distance between wells that do communicate, the overlapping interquartile ranges in both categories make this difference less significant. There is not clear evidence that distance plays a role in well communication.

There is some evidence for a difference in mean path lengths between wells that do and do not cross faults, based on a p-value of 0.047 in a two-sided t-test. The mean path length that crosses a fault is 5,139 ft, while the mean path length that does not cross a fault is 3,608 ft. Wells that are closer together are less likely to be separated by a fault.

For wells that do communicate, there is evidence of a difference between the mean path lengths that cross faults and the mean path lengths that do not cross faults. The p-value for a two-sided t-test was 0.024. Wells that communicate but are not separated by a fault are more likely to be closer together than wells that are separated by a fault.

For wells that do not communicate, there is no evidence of a difference in mean path lengths between paths that do and do not cross faults, given a p-value of 0.98 in a two-sided t-test. Wells that do not communicate are likely to be separated by the same mean distance whether or not they are separated by faults, although there is a larger range of path length values for wells separated by a fault that do not communicate.

 

Summary of results:

Wells that communicate in pumping tests do not have a significantly different mean distance between them than wells that do not communicate (p = 0.152)

Wells that are closer together are less likely to be separated by a fault. (p = 0.047)

Wells that communicate but are not separated by a fault are more likely to be closer together than communicating wells that are separated by a fault. (p = 0.024)

Wells that do not communicate are likely to be separated by the same mean distance whether or not they are separated by faults, although there is a larger range of path length values for non-communicating wells separated by a fault. (p = 0.98)

Critique: I wish I had more sample points and paths to work with, so I could use a more interesting analysis such as ANOVA.

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2 thoughts on “Ex 3: Relating distance between wells to communication type and fault presence

  1. vanstolc Post author

    Hi Julia! I hadn’t originally compared chemistry because out of the 29 wells in the interference test I only have chemistry for 12 of them. Compiling those twelve wells into groups that communicate within themselves but not with the other groups results in 1 group of 3 wells, 3 groups of 2 wells, and three single wells. I have a full suite of data for 9 of those 12 wells. For all 12 wells, I have information on pH, specific conductivity, temperature, d2H, and d18O.

    I ran ANOVA on those variables and came up with the following p-values:
    pH: 0.3265
    Specific conductivity: 2.193e-6
    Temperature: 0.1095
    d2H: 0.0014238
    d18O: 0.02668

    So it looks likes there’s some evidence for a difference in means between disconnected groups of wells for the parameters of specific conductivity and stable isotopes, but not for pH or temperature. However, this analysis might contain error because of the small sample sizes and the fact that within these groupings there are differences in well construction.

  2. jonesju

    Courtney, the “communicate/does not communicate” data seem to be very valuable for your analyses. I was expecting to see some analysis of differences in chemistry based on this distinction. For example, would you not expect that wells that communicate would be likely to share chemistry, and (for example) have more similar values (smaller differences) in their PC1 and PC2 values? Could you construct an ANOVA to test how pairwise differences in (e.g.) PC2 (dependent variable) are related to path length, the communicate/does not communicate, and intervening fault/no intervening fault variables? Would be cool if you could get this done before your defense! No pressure. 🙂

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