Artificial neural networks for removal of couplings in airborne transient electromagnetic data

Modern airborne transient electromagnetic surveys typically produce datasets of thousands of line kilometres, requiring careful data processing in order to extract as much and as reliable information as possible. When surveys are flown in populated areas, data processing becomes particularly time consuming since the acquired data are contaminated by couplings to man‐made conductors (power lines, fences, pipes, etc.). Coupled soundings must be removed from the dataset prior to inversion, and this is a process that is difficult to automate. The signature of couplings can be both subtle and difficult to describe in mathematical terms, rendering removal of couplings mostly an expensive manual task for an experienced geophysicist. Here, we try to automate the process of removing couplings by means of an artificial neural network. We train an artificial neural network to recognize coupled soundings in manually processed reference data, and we use this network to identify couplings in other data. The approach provides a significant reduction in the time required for data processing since one can directly apply the network to the raw data. We describe the neural network put to use and present the inputs and normalizations required for maximizing its effectiveness. We further demonstrate and assess the training state and performance of the network before finally comparing inversions based on unprocessed data, manually processed data, and artificial neural network automatically processed data. The results show that a well‐trained network can produce high‐quality processing of airborne transient electromagnetic data, which is either ready for inversion or in need of minimal manual processing. We conclude that the use of artificial neural network scan significantly reduce the processing time and its costs by as much as 50%.     

Environmental Factors Associated With Natural Methane Occurrence in the Appalachian Basin

The recent boom in shale gas development in the Marcellus Shale has increased interest in the methods to distinguish between naturally occurring methane in groundwater and stray methane associated with drilling and production operations. This study evaluates the relationship between natural methane occurrence and three principal environmental factors (groundwater redox state, water type, and topography) using two pre‐drill datasets of 132 samples from western Pennsylvania, Ohio, and West Virginia and 1417 samples from northeastern Pennsylvania. Higher natural methane concentrations in residential wells are strongly associated with reducing conditions characterized by low nitrate and low sulfate ([NO₃^?] < 0.5 mg/L; [SO₄^2?] < 2.5 mg/L). However, no significant relationship exists between methane and iron [Fe(II)], which is traditionally considered an indicator of conditions that have progressed through iron reduction. As shown in previous studies, water type is significantly correlated with natural methane concentrations, where sodium (Na) ‐rich waters exhibit significantly higher (p<0.001) natural methane concentrations than calcium (Ca)‐rich waters. For water wells exhibiting Na‐rich waters and/or low nitrate and low sulfate conditions, valley locations are associated with higher methane concentrations than upland topography. Consequently, we identify three factors (“Low NO₃^? & SO₄^2?” redox condition, Na‐rich water type, and valley location), which, in combination, offer strong predictive power regarding the natural occurrence of high methane concentrations. Samples exhibiting these three factors have a median methane concentration of 10,000 µg/L. These heuristic relationships may facilitate the design of pre‐drill monitoring programs and the subsequent evaluation of post‐drill monitoring results to help distinguish between naturally occurring methane and methane originating from anthropogenic sources or migration pathways.     

Effects of pelagic food web structure and nutrient concentration on anaerobic methane metabolism in lake sediments

Although anaerobic metabolism in lake sediments is strongly related to organic material from the trophogenic layer, little is known about the role of food web structure in this respect. We tested the influence of planktivorous fish (treatments with or without fish, ±F) and nutrients (treatments with or without fertilization, ±N) on chlorophyll a, zooplankton, sedimentation of particulate organic carbon (POC), and methane accumulation in large enclosures with anoxic hypolimnia (10 m diameter, 8 m deep, 2 × 2 factorial design). Additionally, methane production potential from settled material was estimated in laboratory experiments. In the enclosures, methane accumulation rate increased in the order +F/−N, −F/+N, −F/−N, and +F/+N, while POC sedimentation was similar in all treatments. Settled POC was more efficiently transformed into methane in −F/−N than in +F/−N treatments. However, an opposite effect was observed between −F/+N and +F/+N treatments. In the laboratory, methane production potential was higher when (1) POC content in settled matter increased, and (2) no fish were present. This corresponded well only to field results obtained in −F/−N and +F/−N treatments. The unexpectedly high methane accumulation in the +F/+N treatment was very likely related to abrupt depletion of other electron acceptors in the hypolimnion, which attenuated effects of food web structure. In conclusion, our results indicate that food web structure indirectly affects anaerobic microbial activity primarily due to changes in the decomposition potential of settled organic matter.     

P-immobilisation and phosphatase activities in lake sediment following treatment with nitrate and iron

The influence of a further developed inlake restoration method on the P-immobilisation and microbial activities, especially under anoxic conditions was investigated. The impact of nitrate and iron dosing with a newly developed nitrate storage compound (Depox^®Fe) was tested in enclosures in the eutrophic dimictic Lake Dagowsee, Germany. Additions of 50 g m⁻² of NO₃⁻–N and 66 g m⁻² of Fe³⁺ ensured availability of nitrate at the sediment surface during a 2-months period.As a result the phosphate release from the anoxic sediments was completely suppressed even 1 year after the application. The hypolimnetic deoxygenation was unaffected by the Depox^®Fe addition. However, sulfur reduction and methanogenesis were inhibited and the phosphatase activity increased.