Source: https://propertibazar.com/article/factors-affecting-the-variability-of-stray-gas-concentration-and_5b63a48dd64ab2692d3066b7.html
Timestamp: 2019-04-21 12:23:36+00:00

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ABSTRACT Identifying the source of stray gas in drinking water supplies principally relies on comparing the gas composition in affected water supplies with gas samples collected in shows while drilling, produced gases, casing head gases, pipeline gases, and other potential point sources. However, transport dynamics of free and dissolved gas migration in groundwater aquifers can modify both the concentration and the composition of point source stray gases flowing to aquifers and occurring in the groundwater environment. Accordingly, baseline and forensic investigations related to stray gas sources need to address the effects of mixing, dilution, and oxidation reactions in the context of regional and local hydrology. Understanding and interpreting such effects are best addressed by collecting and analyzing multiple samples from baseline groundwater investigations, potential point sources, and impacted water resources. Several case studies presented here illustrate examples of the natural variability in gas composition and concentration data evident when multiple samples are collected from produced gases, casing head gases, and baseline groundwater investigations. Results show that analyses of single samples from either potential contaminant point sources or groundwater and surface water resources may not always be sufficient to document site-specific baseline conditions. Results also demonstrate the need to consistently sample and analyze a variety of baseline groundwater and gas composition screening parameters. A multidisciplinary approach is the best practice for differentiating among the effects of fluid and gas mixing, dilution, and natural attenuation.
AUTHOR Anthony W. Gorody  Universal Geoscience Consulting, Inc., 1214 West Alabama Street, Houston, Texas; [email protected] Dr. Gorody received his master’s degree and Ph.D. as a Weiss Fellow at Rice University in 1980. He is the president of Universal Geoscience Consulting, Inc., Houston, Texas, and is licensed to practice geology in the states of Texas, Pennsylvania, and Wyoming. He has been principally involved in site-specific casework related to identifying and mitigating stray gas and gasoline range hydrocarbon sources in groundwater. His research interests are on forensic methods useful for evaluating the influence of naturally occurring bacteria on the fate of dissolved hydrocarbons in groundwater.
ACKNOWLEDGEMENTS I thank the Colorado Oil and Gas Conservation Commission (COGCC), Encana Oil and Gas (USA), Inc., and BP America for providing data and for supporting the costs of data analysis and interpretation.
position data from water well samples collected for pre-drill baseline investigations. Case study results presented here illustrate the importance of collecting groundwater quality parameter data when interpreting the significance of dissolved gas concentration and composition data. Multiple samples are required to satisfactorily demonstrate that declining dissolved gas concentrations in contaminated groundwater are the result of natural attenuation and not the result of groundwater mixing dynamics.
*Multiple produced (Prod) and casing head (BHD) samples were collected from these wells during the last quarter of 2010 as indicated. Perf. = perforated.
a small amount of water level decline of water can lead to exsolution and effervescence. Such effects can allow headspace gas concentrations to increase from near detection limits to above the lower explosive limit (LEL). For this reason, baseline headspace measurements at a water well should be conducted and recorded both before and after well purging protocols are completed. In rare instances, high-volume and high-rate pumping of certain aquifers used as water sources can provide another source for stray gas if aquifers contain naturally occurring high concentrations of dissolved hydrocarbons. Pressure drawdown associated with pumping can cause the aquifer to become supersaturated, thereby releasing stray gas into an aquifer system (Yager and Fountain, 2001). Baseline sampling projects should therefore plan on sampling and analyzing fluids and gases from such aquifers whenever a large volume of groundwater is extracted for use in drilling and completion operations. A water well close enough to be in pressure communication with a pumped aquifer can become directly affected by stray gas if local water levels decline sufficiently to allow dissolved gas to exsolve into a well’s headspace. Aquifers associated with relatively thick coal or lignite seams can be particularly susceptible to such effects. Gas desorption induced by rapidly declining ambient hydrostatic pressure equilibrium conditions can release additional stray gas into the groundwater aquifer.
BDH = bradenhead or casing head; C1 = methane; C2 = ethane; C3 = propane; iC4 = isobutane; nC4 = normal butane; d13C = carbon isotope ratio; dD = hydrogen isotope ratio.
Figure 1. Example of range and differences in methane-to-ethane ratios in casing head and produced gases from five wells at a single well pad and all wells completed in the Williams Fork Formation.
Figure 2. Variability of selected parameters in mud gas samples from three different wells drilled within the Marcellus Shale interval, Pennsylvania.
source is deemed similar to, but not identical to, the composition of gases in contaminated well. Collecting and analyzing multiple gas samples from such sources might instead show considerable overlap and help identify gas well point sources with greater confidence. The suggested best practice is to sample potential point sources multiple times to coincide with times when gas and water quality samples are collected from a contaminated water well or surface water resource.
Figure 3. Results of duplicate analyses, Piceance Basin water samples.
Figure 4. Results of split sample analyses sent to different commercial laboratories, Piceance Basin water samples.
from a well, it is important to demonstrate that any measured decreasing or increasing concentration trends are significantly greater than the variability arising from the additive effects of both sampling and analytical errors. In this context, it is necessary to routinely collect blind duplicate samples. It is ideal to collect one duplicate sample for every 10 samples collected in small sample sets or, at a minimum, one duplicate sample for every 20 samples collected in large sample sets such as those typical of regional baseline sampling programs.
Variability Caused by Mixed Fluid Sources Fluid mixing dynamics in water wells can have a significant impact on dissolved methane concentrations. A good example of this is illustrated in Figure 5. As indicated by the annotated dates on the sample points, multiple samples were collected from a single domestic water well in the Piceance Basin for a period of 6 months during the same year. All samples were collected as previously described and sent to the same commercial Figure 5. Dissolved microbial methane concentrations from a water well in the Piceance Basin vary proportionately as a function of the relative concentration of dissolved chloride (Cl- [meq/L]/total anions [meq/L]). Cation-anion balances of all samples less than 10%.
Figure 6. Minimum and maximum dissolved methane concentrations corresponding to the pair of samples with the largest difference in calculated TDS concentrations in water wells sampled multiple times, San Juan Basin.
analyses have cation-anion charge balances of at least ±10% (Fritz, 1994). Variability Caused by Bacterially Mediated Hydrocarbon Oxidation Colorado Oil and Gas Conservation Commission (COGCC) orders 112-156 and 112-157 require San Juan Basin operators to sample dissolved methane in water wells before and 1, 3, and 6 yr after drilling new coalbed methane wells. Results of these analyses provide a unique opportunity to analyze water quality and dissolved methane data from water wells sampled multiple times over a large geographic region: the Colorado part of the San Juan Basin. Figure 6 illustrates the distribution of the lowest and highest dissolved methane concentrations among sample sets from 84 wells sampled two or more times within a 14-yr period. Data shown are all derived from water wells with submersible pumps. All samples for dissolved methane were collected in VOA vials under a head of water in a 5-gal bucket at sample line flow rates of less than 1 gallon per minute. Each of the samples was analyzed by the same analytical service company within less than 24 h of the time they were collected. At least one of the samples in each pair has a dissolved methane concentration of 2 mg/L. This is the threshold concentration in COGCC regulations requiring stable isotopic analysis of dissolved methane.
Figure 7. Maximum dissolved methane concentrations at any given dDC1 ratio decline with increasing enrichment toward positive values as indicated by the dotted line.
Figure 8. The effect of dissolved methane oxidation is confirmed by the linear relationship between the stable hydrogen isotope ratio in methane and the difference between this ratio and that of the groundwater in which methane is dissolved.
Based on bacterial activity reaction test (BART™) cultures routinely collected from San Juan Basin water well baseline samples, nearly all domestic water wells are infected with aggressive bacterial colonies of sulfatereducing bacteria (SRB), iron-related bacteria, and slime formers (Cullimore, 2008). The term “aggressive” is defined by the rapid growth rates detected on the basis of the BART technique (time lag to a colorimetric response). The SRB bacterial groups alone occur in most water wells as high-density colonies totaling more than 1 million CFU/mL (BP America, proprietary data). Elevated dissolved sulfide concentrations commonly measured in a range of 1 to 5 mg/L using colorimetric HACH™ test kits further confirm the presence of aggressive SRB colonies. Their ubiquitous presence and occurrence in high population densities provide empirical evidence linking bacterially mediated sulfate reduction, isotopically fractionated dissolved methane, and declining dissolved methane concentrations in water well samples.
baseline sampling and analysis screening tool needed to differentiate between thermogenic and biogenic stray gas sources. As a rule and as documented here, thermogenic gases have methane-to-ethane ratios of less than 100, whereas biogenic gas sources have ratios more than 1000 (Aravenaa et al., 1995; Zhang et al.,1998; Breen et al., 2007; Hirsche and Mayer, 2007). For these reasons, all groundwater samples should be routinely analyzed for both dissolved methane and ethane using method RSK-175. All samples with low (<100) methane-toethane ratios should be routinely sent for, at a minimum, stable isotope analysis of carbon in methane and ethane and stable isotope analysis of hydrogen in methane. Although propane and butane are also excellent indicators for the presence of thermogenic gas in groundwater, their low concentrations relative to methane and ethane in thermogenic gas sources often render them undetectable in groundwater samples.
for addressing whether stray gas sources are derived from one or more shallow gas reservoirs, from production intervals, or from one or more mixed sources. • Multiple samples and analyses of free and dissolved hydrocarbons from affected water wells can help unravel the effects of mixing, dilution, and intrinsic bioremediation on gas composition and gas concentration data. Interpreting such dynamics can be greatly facilitated by including water quality data, such as major ion analyses, with every sample collected for dissolved hydrocarbon analysis. Results from such a multidisciplinary approach are particularly useful, if not necessary, for demonstrating the effectiveness of remediation activities and a return to baseline conditions. To minimize the inherently large variability in analytical data derived from springs and water wells, sampling and analytical protocols need to be fully documented and consistently applied. Laboratory data should also be routinely evaluated for quality control using splits and blind duplicate analyses.
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