Texas Basin Research Articles

Icehouse mixed carbonate and siliciclastic sequence evolution based on 3D seismic analysis: Insights from the Eastern Shelf of the Permian Basin, Texas

Reciprocal model was introduced for mixed carbonate and siliciclastic sequences within the Virgilian (Upper Pennsylvanian – Gzhelian) and Wolfcampian (Lower Cisuralian) on the Eastern Shelf of the Permian Basin in Texas. This model emphasizes carbonate dominance during transgressive and highstand on the slope, and siliciclastic dominance in the basin during lowstand. Contradictory observations from other mixed basins, such as compositionally mixed lithology in slope cores, accumulation of siliciclastics behind carbonate highs on the outer shelf, off-shelf transport of siliciclastics during highstands, and carbonate deposition on the slope during falling stage, require a re-evaluation of the reciprocal model. This research examines mixed sequences in the Cisco Group and maps lithology distribution by integrating geological and geophysical data, using advanced seismic interpretation techniques, wireline-log crossplot analyses, model-based post-stack inversion, probabilistic neural networks, and supervised Bayesian classification. Observations from the investigation are presented at two scales. In ∼400kyr sequences, relative sea level fall starts with carbonate deposition on the slope while siliciclastics persist near the inner shelf. As the falling stage progresses, siliciclastics reach the shelf edge, forming offlapping fans at the toe of the slope, likely truncating part of the siliciclastic topsets. Subsequently, mixed facies were deposited during the early stages of rising relative sea level, followed by carbonate deposition on the slope and shelf throughout transgression. The mixed facies found inland of transgressive carbonates indicate that prodelta siliciclastics mixed with carbonate mud. Occasionally, transgressive carbonates create shelf-edge build ups, hindering the transport of highstand siliciclastics to the slope. In the composite sequence spanning ∼1200kyr, siliciclastic input decreases significantly with the onset of sea-level fall. The fall truncates topsets with limited siliciclastics, preserving carbonate and mixed facies-dominated foresets with offlapping fans at the toe of the slope. This study advances our understanding of mixed sequences, challenges existing models and lays the groundwork for future investigations in similar geological settings.

Space-based observations of tropospheric ethane map emissions from fossil fuel extraction

Ethane is the most abundant non-methane hydrocarbon in the troposphere, where it impacts ozone and reactive nitrogen and is a key tracer used for partitioning emitted methane between anthropogenic and natural sources. However, quantification has been challenged by sparse observations. Here, we present a satellite-based measurement of tropospheric ethane and demonstrate its utility for fossil-fuel source quantification. An ethane spectral signal is detectable from space in Cross-track Infrared Sounder (CrIS) radiances, revealing ethane signatures associated with fires and fossil fuel production. We use machine-learning to convert these signals to ethane abundances and validate the results against surface observations (R2 = 0.66, mean CrIS/surface ratio: 0.65). The CrIS data show that the Permian Basin in Texas and New Mexico exhibits the largest persistent ethane enhancements on the planet, with regional emissions underestimated by seven-fold. Correcting this underestimate reveals Permian ethane emissions that represent at least 4-7% of the global fossil-fuel ethane source.

Investigation of Oil Well Blowouts Triggered by Wastewater Injection in the Permian Basin, USA

AbstractAged hydrocarbon wells, if proper care is not ensured, can crack, get corroded, and leak subsurface fluids. Permian Basin in Texas, home to thousands of such wells, has seen numerous blowouts and wastewater leaks. Our study employs surface deformation derived from satellite observations, and injection well records to investigate these events. The results reveal an over‐pressurized wastewater aquifer producing a surface uplift of 20 cm/yr, likely due to wastewater being injected tens of kilometers away. Focusing on a January 2022 blowout resulting in 3 cm subsidence in 2 weeks, our geophysical model suggests aquifer over‐pressurization as the cause. With an excess pressure of over 3 MPa in the aquifer, several more such blowouts are possible in the near future. This research highlights the urgent need to better understand the impact of subsurface fluid injection and calls for prompt action to mitigate the environmental effects of oil and gas production.

Potential Poroelastic Triggering of the 2020 M 5.0 Mentone Earthquake in the Delaware Basin, Texas, by Shallow Injection Wells

ABSTRACT The Delaware basin in Texas, one of the largest oil and gas production sites in the United States, has been impacted by widespread seismicity in recent years. The M 5.0 earthquake that occurred in March 2020 near the town of Mentone is one of the largest induced earthquakes recorded in this region. Characterizing the source parameters and triggering mechanism of this major event is imperative to assess and mitigate future hazard risk. A former study showed that this event may be attributed to the deep injection nearby. Interestingly, the earthquake is in proximity to shallow injection wells with much larger total injection volume. In this study, we investigate the role of these shallow injection wells in the triggering of the M 5.0 event despite their farther distance from the mainshock. We perform source-parameter inversion and earthquake relocation to determine the precise orientation of the south-facing normal-fault plane where the mainshock occurred, followed by fully coupled poroelastic stress modeling of the change of Coulomb failure stress (ΔCFS) on the fitted fault plane caused by shallow injection in the region. Results show that shallow wells caused up to 20 kPa of ΔCFS near the mainshock location, dominated by positive poroelastic stress change. Such perturbation surpasses the general triggering threshold of faults that are well aligned with the local stress field and suggests the nonnegligible role of these shallow wells in the triggering of the mainshock. We also discuss the complex effect of poroelastic stress perturbation in the subsurface and highlight the importance of detailed geomechanical evaluation of the reservoir when developing relevant operational and safety policies.

Hydrologic changes in the Brazos River Basin and implications for Great Plains fishes

Alteration of natural flow regimes from surface water and groundwater resource development has adversely impacted aquatic habitats of resident fish throughout the Great Plains. Two endangered cyprinids, Sharpnose Shiner Notropis oxyrhynchus and Smalleye Shiner N.buccula, were historically found throughout the Brazos River Basin in Texas. However, their range has been greatly reduced by construction of impoundments and stream depletion from groundwater pumping. Successful recruitment requires flowing, unobstructed river reaches of sufficient velocity to suspend semi-buoyant fertilized fish ova. The wide, shallow stream habitats the shiners utilize are now limited to the Upper Brazos River Basin upstream of Possum Kingdom Reservoir. This study assesses the relative importance of long-term climate variability, reservoir construction, and groundwater development on Upper Brazos streamflow regimes by (1) calculating flow metrics (2) evaluating groundwater-surface water interactions and long-term groundwater inflows, and (3) using mixed-effects regression models and Poisson regression. Results show that fish habitat has been threatened through several impacted hydrologic processes: (1)groundwater development has resulted in reduced mean daily flows, peak flows, and zero-flow days, (2)upstream impoundments have increased zero-flow days and reduced mean daily flows, and (3)lower mean daily flows and peak flows now occur during droughts, suggesting water resource development—particularly after 1970—has exacerbated drought effects. We illustrate this approach using the Upper Brazos River Basin; however, the methodology applied can inform management actions to maintain spawning flows for streams in similar altered basins.

The Use of Historical Data and Global Climate Models to Assess Historical and Future Surface Water and Groundwater Availability in the Trinity River Basin in Texas

This paper describes the results of a study that was done by the USGS to assess recent (2017) water availability, forecast long-term trends in water availability, assess changes in water availability, and forecast future water availability in the Trinity River Basin in Texas. The Trinity River Basin surface water model and Trinity River alluvium aquifer (TRAA) groundwater model were created to evaluate future conditions under different global climate models (GCM). The results of this study show minimal overall changes in water availability for both surface water and groundwater. Trend analyses using historical data (1900–2017) indicated an increase of annual precipitation on the watersheds that drain into the reservoirs in Regional Water Planning Group C. However, the Trinity River Basin surface water model GCM ensemble mean annual precipitation indicates a downward trend, resulting in a downward trend in surface runoff. Additionally, the GCM ensemble mean for the Trinity River Basin surface water model and the TRAA groundwater model both indicate a downward trend in recharge while the TRAA model GCM ensemble mean indicates an upward trend in the amount of groundwater leaving the aquifer to rivers and streams resulting in an upward trend of cumulative storage change.

Representing Bidirectional Hydraulic Continuum Between the Stream and Hillslope in the National Water Model for Improved Streamflow Prediction

AbstractAlthough hydraulic groundwater (GW) theory has been recognized as a promising tool for understanding the role of the aquifer(s) in the surface‐subsurface hydrologic cycle, the integrated modeling community still lacks a proper hydrologic structure to apply the well‐studied theory to large‐scale hydrologic predictions. This study aims to present a novel hydrologic structure that enables the Boussinesq equation‐based depiction of the bidirectional stream‐hillslope processes for applying hydraulic GW theory to large‐scale model configurations. We integrated the BE3S's (Hong et al., 2020, https://doi.org/10.1029/2020wr027571) representation scheme of the catchment‐scale stream‐hillslope continuum into the National Water Model (NWM) and applied the modified NWM (i.e., the NWM‐BE3S) to three major basins in Texas (i.e., the Trinity, Brazos, and Colorado River basins). Since the NWM currently relies on a single reservoir model for baseflow simulation, we used the Boussinesq aquifer as an alternative subsurface hydrology routine and evaluated its predictive skill and efficacy. We identified that the implemented Boussinesq aquifer(s) in the NWM‐BE3S yielded noticeable improvements in predicting streamflow for aquifers that exhibited higher nonlinearities in the observed recessions. The varying degree of improvements in streamflow predictions per the recession nonlinearities demonstrated not only (a) the algorithmic enhancement of subsurface hydrology (physics) but also (b) the applicability of the Boussinesq theory‐based depiction of the stream‐hillslope two‐way continuum. We diagnosed each stream's state based on the bidirectional stream‐hillslope exchanges and identified the dominant processes (i.e., river infiltration or baseflow) that were represented spatially in the NWM‐BE3S.

Simulated Methane Emission Detection Capabilities of Continuous Monitoring Networks in an Oil and Gas Production Region

Simulations of the atmospheric dispersion of methane emissions were created for a region containing 26 oil and gas production sites in the Permian Basin in Texas. Virtual methane sensors were placed at 24 of the 26 sites, with at most 1 sensor per site. Continuous and intermittent emissions from each of the 26 oil and gas production sites, over 4 week-long meteorological episodes, representative of winter, spring, summer, and fall meteorology, were simulated. The trade-offs between numbers of sensors and precision of sensors required to reliably detect methane emissions of 1 to 10 kg/h were characterized. A total of 15 sensors, able to detect concentration enhancements of 1 ppm, were capable of identifying emissions at all 26 sites in all 4 week-long meteorological episodes, if emissions were continuous at a rate of 10 kg/h. More sensors or sensors with lower detection thresholds were required if emissions were intermittent or if emission rates were lower. The sensitivity of the required number of sensors to site densities in the region, emission dispersion calculation approaches, meteorological conditions, intermittency of the emissions, and emission rates, were examined. The results consistently indicated that, for the conditions in the Permian Basin, a fixed monitoring network with approximately one continuous monitor per site is likely to be capable of consistently detecting site-level methane emissions in the range of 5–10 kg/h.

BLP3-SP: A Bayesian Log-Pearson Type III Model with Spatial Priors for Reducing Uncertainty in Flood Frequency Analyses

Gauge stations have uneven lengths of discharge records owing to the historical hydrologic data collection efforts. For watersheds with limited water data length, the flood frequency model, such as the Log-Pearson Type III, will have large uncertainties. To improve the flood frequency prediction for these watersheds, we propose a Bayesian Log-Pearson Type III model with spatial priors (BLP3-SP), which uses a spatial regression model to estimate the prior distribution of the parameters from nearby stations with longer data records and environmental factors. A Markov chain Monte Carlo (MCMC) algorithm is used to estimate the posterior distribution and associated flood quantiles. The method is validated using a case study watershed with 15 streamflow gauge stations located in the San Jacinto River Basin in Texas, US. The result shows that the BLP3-SP outperforms other choices of the priors for the Bayesian Log-Pearson Type III model by significantly reducing the uncertainty in the flood frequency estimation for the station with short data length. The results have confirmed that the spatial prior knowledge can improve the Bayesian inference of the Log-Pearson Type III flood frequency model for watersheds with short gauge period.

Salinity Contributions from Geothermal Waters to the Rio Grande and Shallow Aquifer System in the Transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin

Freshwater scarcity has raised concerns about the long-term availability of the water supplies within the transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin in Texas, New Mexico, and Chihuahua. Analysis of legacy temperature data and groundwater flux estimates indicates that the region’s known geothermal systems may contribute more than 45,000 tons of dissolved solids per year to the shallow aquifer system, with around 8500 tons of dissolved solids being delivered from localized groundwater upflow zones within those geothermal systems. If this salinity flux is steady and eventually flows into the Rio Grande, it could account for 22% of the typical average annual cumulative Rio Grande salinity that leaves the basin each year—this salinity proportion could be much greater in times of low streamflow. Regional water level mapping indicates upwelling brackish waters flow towards the Rio Grande and the southern part of the Mesilla portion of the basin with some water intercepted by wells in Las Cruces and northern Chihuahua. Upwelling waters ascend from depths greater than 1 km with focused flow along fault zones, uplifted bedrock, and/or fractured igneous intrusions. Overall, this work demonstrates the utility of using heat as a groundwater tracer to identify salinity sources and further informs stakeholders on the presence of several brackish upflow zones that could notably degrade the quality of international water supplies in this developed drought-stricken region.

Improving flood forecasting using conditional bias-aware assimilation of streamflow observations and dynamic assessment of flow-dependent information content

We describe an adaptive extension of the conditional bias-penalized ensemble Kalman filter for conditional bias (CB)-aware data assimilation (DA) and comparatively evaluate with the ensemble Kalman filter (EnKF) for 6 headwater basins in Texas using the operational lumped hydrologic models from the National Weather Service. We then use CB-aware DA and the degrees of freedom for signal to assess the marginal information content of observations. We show that CB arises very frequently in varying magnitudes when assimilating streamflow observations during the catchment’s response to precipitation and subsequent drainage, and that, in general, larger discharges are associated with larger CB. CB-aware DA improves over EnKF by varying margins in times of significant flow, and the improvement is particularly large during sharp rises of the outlet hydrograph with large peak flows. For the 6 study basins, the average relative reduction in root mean square error of the ensemble mean streamflow analysis by CB-aware DA over EnKF is 31.5% for all ranges of observed flow and 32.1% for observed flow exceeding 200 cms. The flow-dependent marginal information content of the observations varies very significantly with the streamflow response of the catchment and the magnitude of CB, and tends to decrease and increase in the rising and falling phases of the hydrograph, respectively. The findings indicate that CB-aware DA with information content analysis offers an objective framework for dynamically balancing the predictive skill of hydrologic models, quality and frequency of hydrologic observation, and scheduling of DA cycles toward improving operational flood forecasting cost-effectively.

Nanoparticles Aid Oil Recovery During Alternating Injection

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 201586, “Effect of Silica Nanoparticles on Oil Recovery During Alternating Injection With Low-Salinity Water and Surfactant Into Carbonate Reservoirs,” by Saheed Olawale Olayiwola, SPE, and Morteza Dejam, SPE, University of Wyoming, prepared for the 2020 SPE Annual Technical Conference and Exhibition, originally scheduled to be held in Denver, Colorado, 5–7 October. The paper has not been peer reviewed. Although the potential of nanoparticles (NPs) to improve oil recovery is promising, their effect during alternating injection is still uncertain. The main objective of the authors’ study is to investigate the best recovery mechanisms during alternating injection of NPs, low-salinity water (LSW), and surfactant and transform the results into field-scale technology. The outcome of these experiments revealed that tertiary injection of NPs results in additional oil recovery beyond the limits of LSW. Introduction A series of coreflooding experiments was conducted using several cores with an effective permeability of approximately 1 md to the brine at a temperature and pressure of 70°C and 3,000 psi. The study performs four different alternating injections of NPs with LSW and surfactant to determine optimal oil recovery. The wettability of the rock and fluid and the interfacial tension (IFT) of oil and water are measured to understand the mechanisms of interactions between the fluids and the reservoir rock. Materials A 12×12×12-in. block taken from an outcrop of Indiana limestone reservoir was purchased for this study. Four core plugs with a diameter of 1.5 in., used for the coreflooding experiments, were selected from this block. A synthetic 100,000-ppm (10 wt%) brine was prepared in the laboratory by dissolving sodium chloride (NaCl) and calcium chloride with a ratio of 4:1 in deionized water. The crude oil used in this study was a volatile oil (properties are described in Table 2 of the complete paper) obtained from the Permian Basin in Texas. Injected Fluids. A 10,000-ppm (1 wt%) LSW was prepared by diluting the synthetic brine 10 times. The surfactant solutions were prepared from an anionic sodium dodecyl sulfate (SDS) surfactant. A 1,000-ppm (0.1 wt%) surfactant solution used throughout the experiments was selected on the basis of the estimated critical micelle concentration of 600 to 2,240 ppm for SDS and nanofluid/NaCl. The concentration of silica NPs used in this study was 500 ppm (0.05 wt%). The nanofluids were pre-pared either as a simple solution or as a mixture with other chemicals to make a concentration of 500-ppm silica NPs. Coreflooding System. The established coreflooding system used for this experimental study was custom-made to determine the oil recovery and the relative permeabilities at steady-state and unsteady-state flows. However, the focus of this study is to investigate the effect of silica NPs on oil recovery. The schematic diagram of the coreflooding system is shown in Fig. 1.

Tectonic controls on the evolution of mixed carbonate‐siliciclastic systems: Insights from the late Palaeozoic Ouachita‐Marathon Foreland, United States

AbstractSea level is thought to be the primary driver of alternating deposition of carbonate and siliciclastic sediment in shelf settings, with carbonates dominating during transgressive/highstands and siliciclastics during lowstands. Although sediment supply is critically important for shelf‐margin growth in siliciclastic systems, few studies demonstrate its impact on mixed carbonate‐siliciclastic systems. The Permian Basin in Texas, United States, provides an opportunity to investigate the basin evolution regarding the source, sediment routing and particularly shelf/slope growth from syn‐ to postorogenic phases during alternating carbonate and siliciclastic sedimentation. Published detrital zircon data show that the proportion of orogen‐related sources decreased significantly from an earliest Permian synorogenic phase (ca. 298 Ma) to a Leonardian (ca. 280–271 Ma) postorogenic phase, in concert with a grain‐size change from fine‐ to medium‐grained sand to silt. Although along‐strike lateral variabilities exist on the shelf margin, the shelf‐margin evolution characteristics show a significant difference among the Northern Shelf, Eastern Shelf and Central Basin Platform. The synorogenic Eastern Shelf exhibits a significant higher progradation rate than does the postorogenic Northern Shelf. The progradation and aggradation ratio of siliciclastic‐rich intervals in the Eastern Shelf is significantly higher than those of carbonate‐rich intervals in the Eastern Shelf and carbonate‐ or siliciclastic‐rich intervals in the Northern Shelf. In contrast, the Central Basin Platform, with no siliciclastic sediment supply, records almost no progradation regardless of orogenic phases. There is an increase in slope gradient with decreasing sediment supply during this second‐order sequence from the Permian Cisuralian Series to the end of the Guadalupian Series. This study demonstrates that tectonically driven siliciclastic sediment supply was the main mechanism controlling the shelf and slope evolution in alternating siliciclastic and carbonate deposition.

Analysis of uncertainty and non-stationarity in probable maximum precipitation in Brazos River basin

Probable Maximum Precipitation (PMP) is used for designing major hydraulic structures, such as dams and reservoirs, nuclear power plants, and flood protection works. However, the estimated PMP values are associated with uncertainties that have received significant attention in recent years, partly because hydrologic extremes are projected to become more frequent, severe, and uncertain with non-stationarity and natural climate variability. This study compared four methods of estimating PMP, ranging from hydrometeorological to statistical, including up-to-date grid based and site-specific in the Brazos River basin (BRB). BRB is the largest river basin in Texas and it contains a range of climates from subtropical arid to subtropical humid. The objective of this study was to quantify the uncertainty associated with PMP estimation in terms of change in the PMP value and emphasize the necessity of including the effect of non-stationarity on PMP. The uncertainty analysis incorporates the effect of three sources of error: (1) PMP estimation method, (2) topography, and (3) non-stationarity. The contribution of each of the uncertainty sources to the 24-hour PMP estimation was quantified and found to be as 53.5% (selection of method), 31.4% (effect of non-stationarity), and 15.1% (effect of topography). The uncertainty of PMP estimation was more sensitive to the existing observation statistics and the selection of method than to the differences between climate zones. Results showed an overall significant increase in 24-hour record precipitation (+19.5 mm) and PMP (+22.3 mm) in BRB between two historical periods 1940–1976 and 1977–2013. Thus, it is concluded that extreme precipitation in BRB showed non-stationarity which affected PMP shift during the historical period.

Dams are coming down, but not always by choice: the geography of Texas dams, dam failures, and dam removals

This study examines spatial and temporal trends in Texas dams, dam failures, and dam removals. Dams were examined from a state-wide perspective and within 10 major river basins that collectively account for over 80% of all dams in the state. The state-scale and basin-scale analysis revealed similar patterns of dam occurrence, however there was greater variation in the patterns observed in both the purpose of dams and the timing for when most of the storage was created in each basin. Climate factors, mainly precipitation, influenced dam location. Population was not directly measured in this study but was an obvious influence on the spatial distribution of dams and their functions. While new dams are being built in Texas to secure future water supplies, documented dam incidents/failures have occurred in 15 of the 23 major river basins in Texas, with 328 total instances occurring since 1900. As the number of newly constructed dams and dam failures continue to grow across the state, so should the number of planned dam removals. Between 1983 and 2016, 50 dams have been removed across the state. The purpose for the majority of removals was to eliminate liability concerns associated with aging dams. Future dam removals will likely continue to occur based on the number of older, smaller dams with potential liability concerns. As Texas’ dam infrastructure continues to age, dam removal is a practical management option for mitigating potential dam-related hazards and improving the connectivity and ecological function of the river systems. Citation: Dascher ED, Meitzen K. 2020. Dams are coming down, but not always by choice: the geograph of Texas dams, dam failures, and dam removals. Texas Water Journal. 11(1):89-129. Available from: https://doi.org/10.21423/twj.v11i1.7092.

Reproduction and Age Structure of the Plains Killifish Fundulus zebrinus from Two Tributaries of the Upper Red River, Texas

Plains Killifish Fundulus zebrinus (subgenus Plancterus) is native to river basins in Oklahoma, New Mexico, and Texas. Original descriptions of Plains Killifish life history information are now applicable to the sister taxon Northern Plains Killifish Fundulus kansae following recognition of the 2 species in 2001. Study objectives were to quantify (1) length of the reproductive season, using the gonadosomatic index and categories of gonadal maturation, (2) batch fecundity, and (3) number of age groups for Plains Killifish taken from 2 rivers within the upper Red River basin of Texas. Reproductive season was from March through September, with the production of multiple batches and a maximum batch of 131 mature oocytes. Plains Killifish were sexually mature at age 1 and had an estimated life span of 2–3 years. Reproductive season, production of multiple batches, and age of Plains Killifish were similar to those reported for Northern Plains Killifish and 2 other closely related subgenera, Wileyichthys and Zygonectes. These similarities suggest strong trait conservatism among a monophyletic group of fundulids that inhabit a diversity of freshwater and saltwater environments in western shallow bays and salt marshes, southwestern arid and prairie streams, and eastern low-gradient streams of North America.

Quantifying the effects of urbanization on floods in a changing environment to promote water security — A case study of two adjacent basins in Texas

The increased occurrence of flood events resulting from urbanization and global climate change is a great threat to water security. To systematically evaluate the impacts of urbanization on floods, we applied a paired catchments approach to two adjacent river basins in south-central Texas — the San Antonio River Basin (SARB), with fast urbanization; and the Guadalupe River Basin (GRB), with little land cover change. A physics-based distributed hydrological model — the Distributed Hydrology Soil Vegetation Model, embedded with a multi-purpose reservoir module (DHSVM-Res) — was used to simulate streamflow and reservoir storage. The simulations were conducted under different land cover scenarios, including a newly developed continuous land cover series (CLCS). Holistic analyses were then conducted for the paired basins using three methods: analyzing the selected flood events, detecting change points (CP) of monthly floods, and testing the elasticity of long-term flood regimes. The results suggest that: (1) urbanization may reduce lag time and elevate flood peaks significantly by 3–30% in our study area; (2) when there is little land cover change, changing climate is the major driver of variations in the monthly maximum streamflow (MMS); (3) fast urbanization can amplify streamflow variability, increase MMS significantly, and thus alter the timing of CP; and (4) the mean MMS of observed streamflow in the SARB has increased by as much as 75.7% from the pre-CP to post-CP periods. This comprehensive study fills in a gap in our current understanding of the isolated impacts of urbanization on flooding and is expected to support future explorations of anthropogenic influences on floods.

A Bayesian Neural Network for an Accurate Representation and Transformation of Runoff Dynamics: A Case Study of the Brazos River Basin in Texas

Conventional physically based models have long yielded promising results, as they have been the main tool to depict the underpinnings of the physics governing the hydrological events. These models, however, suffer from certain issues such as the intense calibration time or the uncertainty in the estimation of hydrological variables. The development of the sophisticated data-driven techniques, and machine learning models in particular, combined with rapid increases in computational abilities (graphics processing units, computer clusters. etc.), has enabled hydrologists to utilize the data driven models in tandem with the well-established hydrological models to simulate miscellaneous environmental processes nimbly, and therefore circumvent the aforementioned conundrums associated with the physically based models. To this end, the present study aims at exploring a sophisticated neural network called variational Bayesian neural network, to improve the accuracy of physically based predictions such as runoff. Our neural network was able to accurately forecast the runoff rates with the mean Pearson correlation coefficient of 86.27%+0.0599 within a randomly selected subset of cells in the Brazos River Basin. As these cells are selected randomly across the basin, we exclude the possibility of biasing our neural network by any specific cell. Moreover, this work for the very first time, to the best of our knowledge, suggests a similarity-based solution to transfer the learning model developed in a basin to be deployed across a different basin. In other words, there would be no need to develop a learning model for each basin from scratch. We, instead, utilize the models learnt from the previously studied basins. We cross-validated our proposed transfer learning solution via leave-one-out strategy within the grid cells of the Brazos River basin achieving a mean Pearson correlation coefficient of 85.83%+0.0592.

E&P Notes (June 2020)

E&P Notes (June 2020)

Daily Satellite Observations of Methane from Oil and Gas Production Regions in the United States

Production of oil and natural gas in North America is at an all-time high due to the development and use of horizontal drilling and hydraulic fracturing. Methane emissions associated with this industrial activity are a concern because of the contribution to climate radiative forcing. We present new measurements from the space-based TROPOspheric Monitoring Instrument (TROPOMI) launched in 2017 that show methane enhancements over production regions in the United States. In the Uintah Basin in Utah, TROPOMI methane columns correlated with in-situ measurements, and the highest columns were observed over the deepest parts of the basin, consistent with the accumulation of emissions underneath inversions. In the Permian Basin in Texas and New Mexico, methane columns showed maxima over regions with the highest natural gas production and were correlated with nitrogen-dioxide columns at a ratio that is consistent with results from in-situ airborne measurements. The improved detail provided by TROPOMI will likely enable the timely monitoring from space of methane emissions associated with oil and natural gas production.