The isometric log-ratio (ilr)-ion plot: A proposed alternative to the Piper diagram

Abstract The Piper diagram has been a staple for the analysis of water chemistry data since its introduction in 1944. It was conceived to be a method for water classification, determination of potential water mixing between end-members, and to aid in the identification of chemical reactions controlling a sample set. This study uses the information gleaned over the years since the release of the Piper diagram and proposes an alternative to it, capturing the strengths of the original diagram while adding new ideas to increase its robustness. The new method uses compositional data analysis to create 4 isometric log-ratio coordinates for the 6 major chemical species analyzed in the Piper diagram and transforms the data to a 4-field bi-plot, the ilr-ion plot. This ilr-ion plot conveys all of the information in the Piper diagram (water mixing, water types, and chemical reactions) while also visualizing additional data, the ability to examine Ca2+/Mg2+ versus Cl-/SO42−. The Piper and the ilr-ion plot were also compared using multiple synthetic and real datasets in order to illustrate the caveats and the advantages of using either diagram to analyze water chemistry data. Although there are challenges with using the ilr-ion plot (e.g., missing or zero values zeros in the dataset must be imputed by positive real numbers), it appears that the use of compositional data analysis coupled with the ilr-ion plot provides a more in-depth and complete analysis of water quality data compared to the original Piper diagram

Repetitive Sampling and Control Threshold Improve 16S rRNA Gene Sequencing Results From Produced Waters Associated With Hydraulically Fractured Shale

Sequencing microbial DNA from deep subsurface environments is complicated by a number of issues ranging from contamination to non-reproducible results. Many samples obtained from these environments – which are of great interest due to the potential to stimulate microbial methane generation – contain low biomass. Therefore, samples from these environments are difficult to study as sequencing results can be easily impacted by contamination. In this case, the low amount of sample biomass may be effectively swamped by the contaminating DNA and generate misleading results. Additionally, performing field work in these environments can be difficult, as researchers generally have limited access to and time on site. Therefore, optimizing a sampling plan to produce the best results while collecting the greatest number of samples over a short period of time is ideal. This study aimed to recommend an adequate sampling plan for field researchers obtaining microbial biomass for 16S rRNA gene sequencing, applicable specifically to low biomass oil and gas-producing environments. Forty-nine different samples were collected by filtering specific volumes of produced water from a hydraulically fractured well producing from the Niobrara Shale. Water was collected in two different sampling events 24 h apart. Four to five samples were collected from 11 specific volumes. These samples along with eight different blanks were submitted for analysis. DNA was extracted from each sample, and quantitative polymerase chain reaction (qPCR) and 16S rRNA Illumina MiSeq gene sequencing were performed to determine relative concentrations of biomass and microbial community composition, respectively. The qPCR results varied across sampled volumes, while no discernible trend correlated contamination to volume of water filtered. This suggests that collecting a larger volume of sample may not result in larger biomass concentrations or better representation of a sampled environment. Researchers could prioritize collecting many low volume samples over few high-volume samples. Our results suggest that there also may be variability in the concentration of microbial communities present in produced waters over short (i.e., hours) time scales, which warrants further investigation. Submission of multiple blanks is also vital to determining how contamination or low biomass effects may influence a sample set collected from an unknown environment

Lithosphere versus asthenosphere mantle sources at the Big Pine Volcanic Field, California

[1] Here we report the first measurements of the H2O content of magmas and mantle xenoliths from the Big Pine Volcanic Field (BPVF), California, in order to constrain the melting process in the mantle, and the role of asthenospheric and lithospheric sources in this westernmost region of the Basin and Range Province, western USA. Melt inclusions trapped in primitive olivines (Fo82–90) record surprisingly high H2O contents (1.5 to 3.0 wt.%), while lithospheric mantle xenoliths record low H2O concentrations (whole rock <75 ppm). Estimates of the oxidation state of BPVF magmas, based on V partitioning in olivine, are also high (FMQ +1.0 to +1.5). Pressures and temperatures of equilibration of the BPVF melts indicate a shift over time, from higher melting temperatures (∼1320°C) and pressures (∼2 GPa) for magmas that are >500 ka, to cooler (∼1220°C) and shallower melting (∼1 GPa) conditions in younger magmas. The estimated depth of melting correlates strongly with some trace element ratios in the magmas (e.g., Ce/Pb, Ba/La), with deeper melts having values closer to upper mantle asthenosphere values, and shallower melts having values more typical of subduction zone magmas. This geochemical stratification is consistent with seismic observations of a shallow lithosphere-asthenosphere boundary (∼55 km depth). Combined trace element and cryoscopic melting models yield self-consistent estimates for the degree of melting (∼5%) and source H2O concentration (∼1000 ppm). We suggest two possible geodynamic models to explain small-scale convection necessary for magma generation. The first is related to the Isabella seismic anomaly, either a remnant of the Farallon Plate or foundered lithosphere. The second scenario is related to slow extension of the lithosphere

Repetitive Sampling and Control Threshold Improve 16S rRNA Gene Sequencing Results From Produced Waters Associated With Hydraulically Fractured Shale

Sequencing microbial DNA from deep subsurface environments is complicated by a number of issues ranging from contamination to non-reproducible results. Many samples obtained from these environments – which are of great interest due to the potential to stimulate microbial methane generation – contain low biomass. Therefore, samples from these environments are difficult to study as sequencing results can be easily impacted by contamination. In this case, the low amount of sample biomass may be effectively swamped by the contaminating DNA and generate misleading results. Additionally, performing field work in these environments can be difficult, as researchers generally have limited access to and time on site. Therefore, optimizing a sampling plan to produce the best results while collecting the greatest number of samples over a short period of time is ideal. This study aimed to recommend an adequate sampling plan for field researchers obtaining microbial biomass for 16S rRNA gene sequencing, applicable specifically to low biomass oil and gas-producing environments. Forty-nine different samples were collected by filtering specific volumes of produced water from a hydraulically fractured well producing from the Niobrara Shale. Water was collected in two different sampling events 24 h apart. Four to five samples were collected from 11 specific volumes. These samples along with eight different blanks were submitted for analysis. DNA was extracted from each sample, and quantitative polymerase chain reaction (qPCR) and 16S rRNA Illumina MiSeq gene sequencing were performed to determine relative concentrations of biomass and microbial community composition, respectively. The qPCR results varied across sampled volumes, while no discernible trend correlated contamination to volume of water filtered. This suggests that collecting a larger volume of sample may not result in larger biomass concentrations or better representation of a sampled environment. Researchers could prioritize collecting many low volume samples over few high-volume samples. Our results suggest that there also may be variability in the concentration of microbial communities present in produced waters over short (i.e., hours) time scales, which warrants further investigation. Submission of multiple blanks is also vital to determining how contamination or low biomass effects may influence a sample set collected from an unknown environment

Geochemical data for produced waters from conventional and unconventional oil and gas wells: Results from Colorado, USA

Geochemical data for more than 120,000 oil and natural gas wells from the major sedimentary basins in the USA are listed in the USGS National Produced Waters Geochemical Database [1]. In this summary, we report and discuss the geochemical data on produced waters obtained from published literature and the Colorado Oil and Gas Conservation Commission (COGCC) from close to 4,000 new oil and gas wells in Colorado. We emphasize geochemical data of produced waters from shale and tight reservoirs that have increased dramatically in Colorado since 2011, due to deep horizontal drilling, downhole telemetry and massive multi-stage hydraulic fracturing. These operations require large volumes of fresh water, but contamination of groundwater is the major environmental concern. Also, induced seismicity caused by water injection has been reported from several areas in Colorado, including Trinidad, Raton basin, and Greely, Denver basin. Produced water salinities in Colorado obtained from unconventional oil and gas wells are relatively low, generally less than 30,000 mg/L TDS. Produced water salinities from conventional oil and gas wells overlap those from unconventional wells, but many wells have higher salinities (up to 90,000 mg/L TDS) and different chemical compositions

Probabilistic Aggregation of Uncertain Geological Resources

Abstract Commodities such as oil and gas occur in isolated reservoirs or accumulations, more generically called basic units here. To understand a study area’s economic potential and to craft plans for exploration and development, resource analysts often aggregate (sum, accumulate) basic unit magnitudes in distinct spatial subsets of the study area and then appraise the total area’s potential by summing these intermediate sums. In a probabilistic approach, magnitudes are modeled as random variables. Some have asked, “Do different methods of partitioning basic units into subsets lead to different probability distributions for the sum of all basic unit magnitudes?” Any method of aggregation of basic unit magnitudes which obeys the rules of probability leads to the same probability distribution of the sum of all unit magnitudes as that computed by direct summation of all basic unit magnitudes. A Monte Carlo simulation of a synthetic example in which the magnitude of resource in each unit is marginally lognormal and pairwise correlations among basic unit magnitudes are specified illustrates key features of probabilistic aggregation. The joint distribution of certain pairs of aggregates are closely approximated by a bivariate lognormal distribution

Inzichten in de effectiviteit van preventieve instrumenten in de strijd tegen georganiseerde criminaliteit

Georganiseerde criminaliteit vormt een bedreiging voor de veiligheid van de maatschappij en de integriteit van het openbaar bestuur. Hoewel preventieve maatregelen doeltreffend kunnen zijn bij de preventie van bepaalde soorten criminaliteit, is weinig bekend over de daadwerkelijke effectiviteit van de instrumenten die georganiseerde criminaliteit zouden moeten voorkomen. Er is daarom behoefte aan meer inzicht in wat binnen- en buitenlandse wetenschappelijke literatuur rapporteert over de effectiviteit van preventieve instrumenten tegen georganiseerde criminaliteit. Dit onderzoek richt zich op de preventie van georganiseerde criminaliteit en in het bijzonder op de volgende drie aan georganiseerde criminaliteit verbonden activiteiten: 1) drugsproductie en -handel, 2) wapenhandel en -smokkel, en 3) mensenhandel en -smokkel. Bovendien zijn alleen studies meegenomen waarin duidelijk wordt aangegeven dat de daarin beschreven instrumenten een beoogd preventief doel hebben, ook als de maatregelen daarnaast nog een ander doel dienen. Daarnaast willen we met deze studie in de eerste plaats de beschikbare literatuur over de effectiviteit van de toepassing van preventieve instrumenten in kaart brengen. Het onderzoek is dan ook uitsluitend gericht op studies die de effectiviteit van de preventieve instrumenten op dit gebied (en met betrekking tot de belangrijkste criminele activiteiten in kwestie) trachtten te evalueren of te bestuderen. INHOUD Introductie De aanpak van georganiseerde criminaliteit in Nederland Theoretische onderbouwing van de preventie van georganiseerde criminaliteit Methodische aanpak van het onderzoek De geëvalueerde preventieve instrumenten in de strijd tegen de georganiseerde criminaliteit: bevindingen van de literatuurstudie Uitdagingen bij de evaluatie van de preventieve aanpak van georganiseerde criminaliteit Conclusie