Figure 65- Mass ratio graphs for all watershed surface water samples, with produced water, flowback samples, and oil brine from Pennsylvania (a) Ba/Ca vs. Sr/Ca ratio (Chapman et al., 2012) (b) Ba/Cl vs. Br/SO4 ratio (Brantley et al., 2014) (c) Ca/Sr vs. Ca/Mg ratio (d) SO4/Cl vs. Br ratio (Wilson, 2013)
124 4.7.8 Log(Ca) vs. Log(Cl)
Figure 66-Log(Ca) vs Log(Cl) ratio values for all groundwater samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot, Vidic, Gregory, & Vidic, 2013)
Figure 67-Log(Ca) vs Log(Cl) ratio values for all surface water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
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Figure 68-Log(Ca) vs Log(Cl) ratio values for all water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
4.7.9 Log(Mg) vs. Log(Cl)
Figure 69-Log(Mg) vs Log(Cl) ratio values for all groundwater water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
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Figure 70-Log(Mg) vs Log(Cl) ratio values for all surface water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
Figure 71-Log(Mg) vs Log(Cl) ratio values for all water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
127 4.7.10 Log(Na) vs. Log(Cl)
Figure 72-Log(Na) vs Log(Cl) ratio values for all groundwater water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
Figure 73-Log(Na) vs Log(Cl) ratio values for all surface water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
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Figure 74-Log(Na) vs Log(Cl) ratio values for all water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
4.7.11 Log(Sr) vs. Log(Cl)
Figure 75-Log(Sr) vs Log(Cl) ratio values for all groundwater water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
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Figure 76-Log(Sr) vs Log(Cl) ratio values for all surface water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
Figure 77-Log(Sr) vs Log(Cl) ratio values for all water samples, compared to Pennsylvania produced water, Marcellus Shale brine, various oil and gas brines, Southwestern Pennsylvania flowback, and Venango County conventional oil brine (Barbot et al., 2013)
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4.7.12 Summary of Potentially Impacted Samples
A total of 224 samples were identified as potentially impacted using the mixing spaces proposed by Chapman et al. (2012), Brantley et al. (2014), and Wilson et al (2013). These samples were identified as potentially impacted by either convention oil brines, produced waters, abandoned mine drainage, or saline groundwater based on their similar to mass ratios of endmembers of these fluids (Table 13).
Table 13-Number of samples, potentially impacted samples, and percentage of potentially impacted samples sorted by watershed
Watershed Number of Samples Number of Potentially Impacted
4.8.1 Unconventional Wells within Study Watersheds
ArcMap was used to determine the number of unconventional wells in each of the eight watersheds that were studied (Figure 78). Within the eight watersheds there are a total of 3,748 unconventional wells that were drilled between 2004 and 2016. The
number of water samples taken, and unconventional wells drilled between 2004 and 2016 in each watershed can be found in Table 14.
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Table 14- Number of well water samples taken compared to number of unconventional wells, drilled between 2004 and 2016, in each watershed
Watershed Number of Samples
Number of Unconventional
Wells
Beaver 1 9
Connoquenessing 271 433
Kiskiminetas 9 134
Lower Allegheny 193 190
Lower Monongahela 56 1797
Shenango 3 95
Upper Ohio 227 655
Upper Ohio-Wheeling 6 435
Total 766 3748
Figure 78-Map showing the number of groundwater samples, surface water samples, and unconventional wells in the eight watersheds studied
132 4.8.2 Distance to Unconventional Wells
ArcMap was used to measure the distance from each sample taken, both
groundwater and surface water, to the closest unconventional well. DEP SPUD data for all unconventional wells drilled between 2004 and 2016 was used for this measurement.
For all samples the average distance to the nearest unconventional well was 6560 ft.
According to the Pa.C.S.§3218(c) if an unconventional well is within 2500 feet of a well water supply deemed as impacted, then the well operator is presumed responsible (2012 Oil and Gas Act, 2012). For this study, it was found that 41% of samples taken were less than 2500 feet from an unconventional well drilled between 2004 and 2016. Table 15 contains the average distance to the nearest unconventional well for each watershed, broken into groundwater and surface water.
Table 15-Average distance to nearest unconventional well, in feet, for each watershed (SPUD)
Watershed Sample Type Average Distance to Nearest UC Well (ft.)
All Both 6560
Beaver Groundwater N/A
Connoquenessing Groundwater 3778
Connoquenessing Surface Water 5375
Kiskiminetas Groundwater 18546
Lower Allegheny Groundwater 24740
Lower Allegheny Surface Water 9542
Lower Monongahela Groundwater 6244
Lower Monongahela Surface Water 8979
Shenango Groundwater 889
Upper Ohio Groundwater 3949
Upper Ohio Surface Water 2488
Upper Ohio-Wheeling Groundwater 8134
Upper Ohio-Wheeling Surface Water 2005
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4.8.3 Potentially Impacted Points and Distance to Unconventional Wells
Once potentially impacted samples were identified using the four chemical ratios, the distance to each point was determined using ArcMap. Appendix I lists the distance from each sample taken to the nearest unconventional well. The unconventional well data was gathered from PA DEP SPUD website, and contains only unconventional wells that were drilled between 2004 and 2016.
A total of 224 (29%) samples from all watersheds were considered potentially impacted. Some of these samples were taken at the same location, and some were identified as potentially impacted in more than one chemical ratio graph. The
Connoquenessing Watershed had the greatest number of samples considered potentially impacted, and 26% of those samples were within 2500 feet of an unconventional well.
The Upper Ohio-Wheeling Watershed had the highest percentage of samples (2 out of 2) considered as potentially impacted within 2500 feet of an unconventional well. These two samples were both within 2500 feet (Table 16).
Table 16-Number of potentially impacted samples, potentially impacted samples within 2500 ft., and percentage of potentially impacted samples
Watershed Number of Potentially Impacted Samples
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4.8.4 Methane Levels and Distance to Unconventional Wells
Below is a graph of methane levels compared to distance to the nearest unconventional well. Given the r2 value there appears to be little to no correlation between the methane levels of a groundwater or surface water samples and the sample’s distance to the nearest unconventional well (Figure 79).
Figure 79-Scatter plot of methane levels (mg/L) and distance to nearest unconventional well (ft.) for all samples R² = 0.013
0.1 1 10 100 1000 10000
0 10000 20000 30000 40000 50000 60000
Methane (mg/L)
Distance to Nearest Unconventional Well (ft)
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CHAPTER 5: DISCUSSION
5.1 Potential for Contamination due to Extractive Activities 5.1.1 Fracture Creation and Fluid Migration
According to the 2016 EPA report Hydraulic Fracturing for Oil and Gas: Impacts from the Hydraulic Fracturing Water Cycle on Drinking Water Resources in the United States, there are multiple areas of concern in terms of fracturing fluid migration. One of those is that of movement along underground pathways. The two major pathways are considered to be the well hole itself and the fractures created in the strata created during the HVHF process. Typically, these fractures are not of major concern due to the
difference in vertical depth between most drinking water aquifers, and the shale fractured for natural gas. However, the EPA report states that the fractures created in the Marcellus Shale have a median of 120 meters (400 ft.). This is far greater than median fracture height in other shale, such as the Woodford (50 meters), and Eagle Ford (40 meters) (US EPA, 2016).
Adding to the concern is that fractures created during HVHF are infrequently mapped and therefore little is known about their actual location. Little is also known about the bottom of most drinking water resources. Aquifers are typically only mapped at the near surface, where residential well drilling is done (US EPA, 2016). However, some of the water wells in this study were deep (e.g. 400’ to 900’). Furthermore shallower conventional oil and gas plays, as well as coal seems lie between the surface and
Marcellus (Allewattagama et al., 2015). Though natural gas containing shale formations are very rarely a source of groundwater, due to their low permeability, the potential for
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aquifers to be located near these formations remains (Swistock, 2007). Therefore, drinking water resources in the Marcellus Shale Formation should be of special concern.
Modeling done by Myers (2012) also indicates that the rate of groundwater movement could be increased due to anthropogenic activities. This could result in the fracturing fluids, thought to be safety trapped for thousands of years, reaching aquifers and surface waters in far less time. This reinforces the need for proper subsurface mapping both before and after HVHF (Myers, 2012).
5.1.2 Abandoned Wells and Fluid Migration
It has been estimated that over 325,000 abandoned and orphaned wells exist in Pennsylvania today. Although the Pennsylvania Department of Environmental Protection has worked to catalog and map these wells, many still remain unaccounted (Figure 80) (PA DEP, 2016). These abandoned and orphaned wells pose a serious threat when combined with HVHF. If one of these wells is located near a hydraulic fracturing
operation, then the potential for contamination of a drinking water resource increases. As a state with a history of extractive activities, the possibility of fracturing near an
abandoned well in Pennsylvania is highly likely (US EPA, 2016).
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Figure 80-Map of all oil and gas wells in the Commonwealth of Pennsylvania (PADEP, 2017)
5.2 Parameters of Concern 5.2.1 Manganese Exposure
In the last five years, an increasing amount of research has been done on the link between neurodevelopment damage and elevated manganese levels. Much of this work has focused on the potentially harmful effects of increased manganese levels on children.
A review of recent studies by Rodriguez-Barranco et al. (2013) found that in all studies a 50% increase in manganese levels, as measured in hair, led to a 0.7 point decrease in IQ for children ages 6-13 (Rodríguez-Barranco et al., 2013). Evidence suggests that
exposure between 100 to 1000 µg/L can lead to negative impacts on the
neurodevelopment of children. This amount can often be found in drinking water (Benson et al., 2017) and 44% (339) of the groundwater and surface water samples analyzed in this study had manganese levels above 100 µg/L.
5.3 Water Quality on the Watershed Scale 5.3.1 Beaver Watershed
Clearly the Beaver Watershed is one that requires more study and more samples before any meaningful conclusions can be made. Since only one sample was collected in the Beaver Watershed it is difficult to determine any trends present. However, the one sample that was collected did have detectable levels of bromide, a useful indicator in determining impact due to extractive activities (Wilson & Van Briesen, 2013) (Figure 63).
5.3.2 Connoquenessing Watershed
The Connoquenessing Watershed was the most heavily sampled of all watersheds in this study. This is due in large part to two Stolz Lab dedicated projects centering in Butler County, the county in which most of the Connoquenessing Watershed is located.
A total of 271 water samples were taken in the Connoquenessing Watershed between 2011 and 2016. In general, there remain high quality drinking water resources in the watershed. However, there were many instances of potential impact.
Iron and manganese were the two parameters measured of greatest concern in the Connoquenessing Watershed. Both median and average manganese levels were above the SMCL for groundwater and surface water in the Connoquenessing Watershed. Iron levels were also high, with the average above the SMCL for groundwater, but not for surface water. Though both iron and manganese had elevated levels, manganese clearly had the greatest levels in the Connoquenessing Watershed (Figure 36, Figure 37). The iron and manganese levels in the Connoquenessing Watershed were above those of most other watersheds sampled during this study.
The Connoquenessing Watershed has both the highest number of samples that were identified as potentially impacted (105/271) using four different chemical ratio graphs, and the highest number of samples with bromide detected (101/265) (Table 7, Figure 36, Figure 37). As bromide is a potential indicator of extractive activities the fact that 101 of the 265 groundwater samples taken had bromide seems to suggest some level of impact occurring within the watershed. The areas of potential impact appear to be localized, and often are contained to a single location. Three such areas are identified and circled in red in Figure 81. Of those samples determined to be impacted, 28 (27%) of
them were within 2500 ft. of an unconventional well. This could indicate that unconventional wells are impacting those drinking water resources.
For most of the chemical ratio graphs potentially impacted samples fell either close to the Venango County conventional brine, or between the brine and the flowback or produced waters (Figure 59, Table 7). This could indicate that there are several instances in the Connoquenessing Watershed where drinking water resources have been impacted by underground pathways with access to brines, flowback or produced waters.
The high number of unconventional wells drilled within the Connoquenessing Watershed, and the number of samples identified as potentially impacted either by conventional oil brines, or produced waters, suggest they have been impacted by oil and gas operations.
Figure 81-Map showing all points taken, impacted points, and unconventional wells in the Connoquenessing Watershed, red circles indicate areas of high density for potentially impacted points. Potentially impacted points are indicated in red. (SPUD, PASDA)
5.3.3 Kiskiminetas Watershed
Since no surface water samples were taken in the Kiskiminetas Watershed during this study no conclusions can be made about the potential impacts of anthropogenic activities on the surface water within the watershed. Nine groundwater samples were taken, four of which were all in the same general area. This makes it difficult to make any meaningful conclusions regarding the general groundwater quality in the Kiskiminetas Watershed. Within the nine samples taken, water quality was generally very good.
Neither the average nor the median for either iron or manganese were above the SMCL.
Though one water sample, MS341, did have a very similar Ca/Sr and Ca/Mg ratio to that of the Venango County conventional oil brine, it was not located near any unconventional
wells, and therefore no conclusions can be drawn about the impacts of unconventional wells on this sample (Figure 63, Table 11).
Figure 82-Map showing all points taken, impacted points, and unconventional wells in the Kiskiminetas Watershed. Potentially impacted points are indicated in red. (SPUD, PASDA)
5.3.4 Lower Allegheny Watershed
At present the Lower Allegheny Watershed, though large, does not have a large number of unconventional wells drilled since 2004. This can be attributed to the fact that much of the Lower Allegheny Watershed contains the city of Pittsburgh, and drilling is currently banned within city limits (Lampe & Stolz, 2015). The Allegheny Watershed includes the city of Pittsburgh, PA and much of its surrounding suburbs (Figure 5). The Lower Allegheny Watershed was one of the more heavily sampled watersheds in this study. Most of these samples were surface water samples taken in Deer Lakes Park in
association with a current project. These surface water samples, several of which
appeared to be influence by AMD, led to increased levels of both iron and manganese in the surface water for the watershed. For most watersheds studied iron and manganese levels in surface waters were far less than those in groundwater.
Though the surface water appeared, based on visual analysis, to be impacted by AMD, it was all groundwater samples that were identified as potentially impacted. Of the groundwater samples taken (58), 19 within the Lower Allegheny Watershed had
detectable levels of bromide. This allowed those points to be compared to other products associated with drilling activities. The points identified as potentially impacted graphed either close to the Venango County conventional oil brine, or close to the 10262012 flowback (Figure 60, Table 8). Some of these samples were taken in locations relatively close to each other, but most points were too spread out to be able to determine a specific cause or point of origin for this contamination.
Three zones were identified as areas of moderate to high impact based on points identified as potentially impacted. Two of these areas do not occur near any
unconventional wells and therefore it can reasonably be assumed that HVHF has not caused the impact to those samples. However, the most northern area is located around a considerable number of unconventional wells. This is Deer Lakes Park which is the subject of a current Stolz Lab project (Figure 83).
Figure 83-Map showing all points taken, impacted points, and unconventional wells in the Lower Allegheny Watershed, red circles indicate areas of high density for potentially impacted points (SPUD, PASDA)
5.3.4.1 Pine Creek Watershed
Both the groundwater samples and surface water samples within the Lower Allegheny Watershed showed increased levels of chloride. This increase is mostly due to a small group of samples contained in the Pine Creek Watershed. Pine Creek Watershed is a small, sub-watershed of the Lower Allegheny Watershed. The Pine Creek Watershed is of particular interest due to the elevated levels of chloride documented in Pine Creek itself. Unpublished studies by Dr. Porter and students have shown that the entire Pine Creek system from its mouth to the headwaters have elevated chloride levels throughout the year, making point sources (like salt barns or road runoff) unlikely. A small-scale
study was conducted to determine if the groundwater had chloride levels similar to those found in Pine Creek Watershed surface waters.
For this study 26 groundwater and 17 surface water samples were collected and analyzed. The groundwater samples were taken first by the Stolz Lab, then surface water locations were selected based on the groundwater samples. The goal was to collect surface water samples located as close as possible to the groundwater samples already taken. These two sample types were then compared in an attempt to determine if the high chloride levels found in Pine Creek were originating from an underground source.
Figure 84-Map of groundwater and surface water samples taken in Pine Creek Watershed (PASDA)
As can be seen in the two graphs below both surface water and groundwater samples for the Pine Creek Watershed showed elevated levels of chloride (Figure 85,
Figure 86). The mean chloride level for the surface water samples was 271 mg/L, where the groundwater was 193 mg/L. This increased level of chloride in the groundwater samples could indicate that these drinking water resources are connected to a brine that has migrated from its original formation. In turn this groundwater is potentially feeding the surface water, as is the case with many streams in Pennsylvania, and causing an increase in chloride levels in Pine Creek and its tributaries (Swistock, 2007).
Figure 85-Box plot of anion concentrations for groundwater samples in the Pine Creek Watershed 0.00
0.01 0.10 1.00 10.00 100.00 1000.00 10000.00
Fluoride Chloride Nitrite Bromide Nitrate Phosphate Sulfate
mg/L
Anions
Mean MCL
Figure 86-Box plot of anion concentrations for surface water samples in the Pine Creek Watershed
There were only two groundwater samples with detectable levels of bromide (Figure 85). This is of note because elevated bromide levels are often found in
wastewaters from extractive activities (Wilson, 2013). Therefore, bromide may be of use in determining the impact of any future extractive activities within the Pine Creek
Watershed.
5.3.5 Lower Monongahela Watershed
The surface water samples taken in the Lower Monongahela Watershed, 13 in total, had the largest range for pH out of all the watersheds. The surface water samples also had unusually high levels of aluminum. Seven (54%) out of the thirteen surface
The surface water samples taken in the Lower Monongahela Watershed, 13 in total, had the largest range for pH out of all the watersheds. The surface water samples also had unusually high levels of aluminum. Seven (54%) out of the thirteen surface