Nearby Wells Research Articles

Experimental Study on Physico-Chemical Parameters of Ground Water at Peth Seer Sopore J&K

Human activities, use of fertilizers and chemicals in agricultural fields are the main causes of ground water contamination. Therefore to protect and improve the natural eco system, water quality analysis is essential. The main goal of this work is to study the criteria governing the groundwater quality in the nearby wells of Peth Seer, Sopore J&K. Total 12 groundwater samples and 15 water quality parameters for each sample are considered in this study. The ground water samples of all the selected stations were collected for a physiochemical analysis. For calculating present water quality status, following 16 parameters have been considered Viz. pH, TDS, EC, Chloride concentration, Nitrate concentration, Sulphate concentration, Alkalinity, Fluoride concentration, Total hardness, Magnesium, Calcium, Sodium, Potassium, Temperature, Turbidity, Residual chlorine. The obtained results are compared with WHO (2017). The study reveals that the concentrations of all the constituents are well within the permissible limits of WHO (2017). Groundwater in the study area is suitable for drinking purpose as prescribed by WHO (2017) and irrigation purposes as prescribed by IS-11624(1986).

Geological Reservoir Characterization of a Gas Hydrate Prospect Associated with the Hydrate-01 Stratigraphic Test Well, Alaska North Slope

Geological reservoir characterization is essential for accurate evaluation of gas production performance from gas hydrate reservoirs. Particularly, the understanding of reservoir architecture and heterogeneity is of great importance since these are considered as major controls on fluid hydrodynamic and thermodynamic conditions. This study deals with well log and three-dimensional (3-D) vertical seismic profile (VSP) data acquired from the Hydrate-01 Stratigraphic Test Well within the 7-11-12 prospect, Prudhoe Bay Unit, Alaska North Slope and reports on the results of geological/geophysical evaluation related to the geological structure and reservoir properties of the 7-11-12 prospect. The structural trends of the target reservoirs, based on well correlations, are mostly consistent with the predrill prediction using the surface seismic data, and infer the existence of subseismic faults cutting through the Hydrate-01 well. The 3-D VSP data confirm a down-to-the-east normal fault that offsets the reservoir units across the Hydrate-01 well, which is concordant with the well identification of the same fault, and indicate a northeast-dipping relay structure associated with the overstepping normal faults. The edge enhancement attribute associated with discontinuity generated from the 3-D VSP data shows small faults/fractures, possibly as part of a complex fault network within the imaged normal fault system. These results reveal that the 3-D VSP data provide detailed structural information that is not present from the surface seismic data. The Hydrate-01 well log data confirm the occurrence of gas hydrate at high saturation in the two targeted sand units (B1 and D1 sands), and the comparison to a nearby pre-existing well (7-11-12 well) shows the same general trend in gas hydrate saturation as a map of seismic impedance generated from surface seismic data. The well log data also suggest that the base of gas hydrate occurrence in the Hydrate-01 and 7-11-12 wells is almost aligned at the same depth in both of the targeted B1 and D1 sand reservoirs. Especially for the D1 sand in the Hydrate-01 well, the resistivity logs show a sharp transition from high gas hydrate saturation to fully water-saturated within the D1 sand, suggesting a common gas hydrate/water contact. The results of this study will be used to construct the geological models needed for reservoir simulation studies and they can provide important insights into the geological factors that control the occurrence of gas hydrate on the Alaska North Slope.

Use of structure-guided 3D controlled-source electromagnetic inversion to map karst features in carbonates in offshore northwest Borneo

Fractured and/or karstic carbonates (FKCs) in the subsurface are commonly associated with significant drilling risk or reservoir effectiveness issues. Understanding the distribution of karsts will help avoid drilling into possible voids and also reassess risks associated with reservoir effectiveness. A 2020 3D seismic acquisition in offshore northwest Borneo provided data for identifying new carbonate prospects and an opportunity to revisit a 2010 marine controlled-source electromagnetic (CSEM) survey that was not designed specifically for FKC mapping but can serve to test new inversion capability for imaging karsted carbonate bodies. A 3D CSEM data were used to detect and characterize the nature (i.e., fractured and/or karsted) of carbonate prospects mapped using 3D seismic data. In one approach, structure tensors computed from these seismic data were used to constrain the 3D CSEM inversion on the Azure cloud platform. In another approach, cross gradients between vertical and horizontal resistivities were used as a structural guide obviating the need for seismic data. The resulting anisotropic resistivity models were validated using resistivity logs from a nearby well; the resistivity results matched the well-logs satisfactorily, providing geologic justification to interpret the presence of karst features in the resistivity volumes. Lateral boundary of the carbonate prospects was mapped based on the resistivity characteristic, in seismic- and nonseismic-guided structure-coupled inversion. Resistivity-depth cross section of the area revealed the presence of resistivity discontinuity at the seismic-inferred boundary of the main carbonate prospect. Also, resistivity depth slices of the models clearly demonstrated that the areal distribution of low and high resistive zones can be mapped and useful deductions such as the presence of FKC and basement characteristics can be made using the 3D inversion of the CSEM data.

Application of Time Series Analysis to Estimate Drawdown From Multiple Well Fields

In 2018–2020, meteorological droughts over Northwestern Europe caused severe declines in groundwater heads with significant damage to groundwater-dependent ecosystems and agriculture. The response of the groundwater system to different hydrological stresses is valuable information for decision-makers. In this paper, a reproducible, data-driven approach using open-source software is proposed to quantify the effects of different hydrological stresses on heads. A scripted workflow was developed using the open-source Pastas software for time series modeling of heads. For each head time series, the best model structure and relevant hydrological stresses (rainfall, evaporation, river stages, and pumping at one or more well fields) were selected iteratively. A new method was applied to model multiple well fields with a single response function, where the response was scaled by the distances between the pumping and observation wells. Selection of the best model structure was performed through reliability checking based on four criteria. The time series model of each observation well represents an independent estimate of the contribution of different hydrological stresses to the head and is based exclusively on observed data. The approach was applied to estimate the drawdown caused by nearby well fields to 250 observed head time series measured at 122 locations in the eastern part of the Netherlands, a country where summer droughts can cause problems, even though the country is better known for problems with too much water. Reliable models were obtained for 126 head time series of which 78 contain one or more well fields as a contributing stress. The spatial variation of the modeled responses to pumping at the well fields show the expected decline with distance from the well field, even though all responses were modeled independently. An example application at one well field showed how the head response to pumping varies per aquifer. Time series analysis was used to determine the feasibility of reducing pumping rates to mitigate large drawdowns during droughts, which depends on the magnitude and response time of the groundwater system to changes in pumping. This is salient information for decision-makers. This article is part of the special issue “Rapid, Reproducible, and Robust Environmental Modeling for Decision Support: Worked Examples and Open-Source Software Tools”.

A Neural Network Model with Connectivity-Based Topology for Production Prediction in Complex Subsurface Flow Systems

Summary This paper presents a neural network architecture for prediction of production performance under different operating conditions by integration of domain insight and simulated production response data. The neural network topology in the developed approach is derived from interwell communication and connectivity between a producer and its surrounding supporting injection wells. Instead of a fully connected neural network that represents a global (field-scale) model that allows any injector to be connected to a given producer, and hence too many unrealistic and irrelevant connections, a local view is taken in building the proxy model. In this case, each producer is assumed to be supported by very few surrounding injection wells and is likely to have weak or no communication with distant wells. However, interwell connectivity in complex large-scale reservoirs is not just a function of distance and rather difficult to determine. Therefore, multiple randomly sized regions around each producer are considered to include different numbers of injectors in each local network for any given producer. The variability in the neighborhood size reflects the prior uncertainty about the potential connectivity between a producer and its nearby injection wells at different distances. This approach results in many local neural networks (several local networks per each producer) that can be aggregated into a single large neural network model with a predefined topological structure to represent possible connections. Training with simulated data is then used to estimate the weights in the resulting neural network architecture. Once the training process is completed, for each producer, the local model with the best prediction performance on the test data is selected and used to construct the final topology of the neural network model for the entire field. The method is applied to predict interwell connectivity and oil production in a large-scale mature field that undergoes waterflooding. The results demonstrate that even a simple domain insight, such as distance-based elimination of wells in a large field, can significantly reduce the amount of training data need and lead to noticeable improvement in the prediction performance of the resulting neural network model.

Episodic venting of extreme subsalt overpressure through a thick evaporitic seal

Episodic venting from deep overpressured layers has rarely been documented in sedimentary basins, so the pressure evolution leading to these cyclical phenomena is poorly understood at present. Using three-dimensional (3D) seismic data from the West Nile Deep Sea Fan, we interpret >480 fluid escape pipes within a region of prolific leakage across a > 2 km thick sealing sequence of salt and claystones. Within this region, we map five linear trails of pipes with pockmarks or small mud volcanoes at their outlets and interpret them to have formed by episodic venting of overpressured fluids from beneath the salt, over a ∼2–3 Myr period, coeval with basinward displacement of the pipes by flow of the salt. Importantly, the pipe trails root to the crests of stratigraphic traps at the base of the salt seal. Direct measurements from nearby exploration wells are used to construct pressure-depth and pressure-time plots over the lifetime of the pipe trails and demonstrate that overpressure near to or in excess of the lithostatic pressure must be repeatedly achieved in the stratigraphic traps to breach the salt seal every 50–150 kyrs. This pressure evolution is best described by a sawtooth pattern with overpressure relieved by venting, followed by re-seal of the trap, and pressure recharge. The pressure recharge for this episodic venting can most easily be explained here by biogenic gas generation and aquifer pressure transfer in the traps, with some minor contribution from sustained disequilibrium compaction during the Pliocene to Recent. The conditions necessary for this type of episodic venting should occur more widely, particularly in basins with thick evaporite deposits. The recognition of episodic venting has important implications for prospect de-risking, drilling safety and CO2 and hydrogen storage.

On the discharge variation of a qanat in an alluvial fan aquifer

Qanat is a passive (unpumped) horizontal well (or a slant well with a very mild inclined angle) that is capable of extracting water from aquifers by gravity. Many qanats are constructed along the radius of the alluvial fan wedge-shaped aquifers. Analytical modeling of such a qanat-aquifer system provides great benefit for quickly screening different designs of qanats and accessing the performance of qanat discharge in the field. The previous analytical modeling of discharge of qanats, however, did not consider the wedge-shaped aquifers. Thus, the goal of this research is to obtain semi-analytical solutions of discharge variations of qanats in alluvial fan aquifers with nearby pumping wells, subjected to areal recharges due to rainfall. The uniform head boundary is considered inside the qanat (because of its enormous permeability in respect to the background aquifer). The influences of the aquifer lateral boundaries on discharge of qanat and its sensitivity to hydraulic and geometric parameters are explored. The influences of the lateral boundaries on the discharge of qanat due to areal recharge and nearby pumping wells discharge are also explored. The results of this study can be utilized for multiple purposes: 1) to predict the discharge of qanat in an alluvial fan aquifer and explore the influences of the areal recharge and nearby pumping well discharge; 2) to estimate the hydraulic parameters of the alluvial fan aquifer depleted by a qanat; 3) to determine the location of the nearby pumping well to minimize its influences on the discharge of a qanat; 4) to calculate the water budgets of aquifers depleted by qanats and pumping wells and replenished by areal recharge among other applications. This paper is an extension to the work presented by Sedghi and Zhan (2020) (which concerns an infinite unconfined aquifer) for an unconfined alluvial fan aquifer setting.

Analisa Perancanaan Lumpur Pemboran Menggunakan HPEBM pada Sumur "E" Lapangan "P"

The “E” well to be drilled is a development well in the “P” field located in the North Sumatra Basin. During the drilling operation in well “E” using HPWBM, HPWBM is used to overcome shale instability. This water-based mud is used because it is cheaper and more economical than using oil-based mud. However, this mud needs to be added with other chemicals because HPWBM has a weakness in controlling shale formation. The mud system design for the “E” well uses the offset well method, which uses data from nearby wells for comparison. Well “E” is divided into two intervals. Hole interval 12 1/4" with 9 5/8" casing from 24 m to 290 m depth using HPWBM. Then proceed with 8 1/2" hole intervals with 7" casing from 290 m to 530 m depth using the same mud. The problem this well will face is pressure at a depth of 500 m, thus increasing the mud density from 12 ppg to 14 ppg to prevent kick.

Degradation potential of MCPA, metolachlor and propiconazole in the hyporheic sediments of an agriculturally impacted river

Hyporheic sediments are influenced by physical, biological, and chemical processes due to the interactions with river water and has been shown to play an important role in the environmental fate of pesticides.Therefore, this study evaluated the bacterial degradation potential of MCPA, metolachlor and propiconazole in hyporheic sediments sampled along a 20 km long stretch of an agriculturally impacted river dominated primarily by water losing conditions. Water physicochemical parameters in the river and nearby groundwater wells were assessed along with pesticide sorption to sediments and bacterial community composition. Degradation and mineralisation batch experiments were set up from six locations (five water losing, one water gaining) using environmentally relevant concentrations of pesticides (10 μg kg−1). Highly variable DT50 values from 11 to 44 days for MCPA, 11–27 days for metolachlor (MTC) and 60–147 days for propiconazole were calculated based on ~140 day studies. Degradation of MTC led to accumulation of the transformation products MOA and MESA in batch experiments. Noteworthy, MESA was detected in the groundwater wells adjacent to the part of the river impacted by losing conditions suggesting that degradation processes in hyporheic sediments may lead to the formation of transformation products (TP) leaching towards groundwater. Further, from propiconazole was identified a persistent transformation product being different from 1,2,4-triazole.Specific calculated DT50 values could not the linked to bacterial diversity. However, generally all sediment samples were characterised by high bacterial diversity, where approximately 80% of the relative sequence abundances were < 1%, which may increase the likelihood of finding contaminant-degrading genes, thereby explaining the general high contaminant-degrading activity. The studied sediments revealed a high potential to degrade pesticides despite only being exposed to low diffuse pollutant concentrations that is similar to calculated DT50 values in agricultural soils.

TECTONOSTRATIGRAPHIC EVOLUTION AND HYDROCARBON PROSPECTIVITY SOUTH OF GWADAR BAY, MAKRAN ACCRETIONARY WEDGE, OFFSHORE SW PAKISTAN

The Makran accretionary wedge developed as a result of subduction of the Arabian Plate beneath the southern margin of Eurasia since the Eocene. Interpretation of 2D seismic profiles calibrated to offshore well data in a study area to the south of Gwadar Bay (SW Pakistan) indicates a major period of accretion from the mid‐Miocene, as evidenced by the occurrence of thick growth strata associated with large‐scale imbricate thrusts. The thrust faults originate from a deep detachment within the mud‐rich Oligocene interval, and well‐developed piggy‐back basin successions occur in thrust hanging walls. In the study area, the thrust structures are sealed by a thick, progradational Pliocene to Recent interval in which the presence of submarine canyons, up to 2.5 km across, indicate that sedimentary transport was from the north.Fluid escape pipes and associated amplitude anomalies are observed in the seismic profiles studied and may be related to upward migration of thermogenic hydrocarbons from depth, as heavy hydrocarbon fractions &lt;C3 have been reported from nearby wells. The hydrocarbons are believed to have been sourced from the Oligocene Hoshab Shale and to have then migrated up through a sedimentary succession in which permeability barriers are largely absent. Hanging wall anticlines mapped in the study area could provide structural traps, and turbidites in the Lower Miocene Panjgur Formation may represent a potential reservoir. Amplitude anomalies are also observed adjacent to shallow fluid escape pipes within the topsets of clinoforms in the Pleistocene Chatti and Omara Formations, and probably indicate the presence of biogenic hydrocarbons sourced from distal mudstones in bottomset strata.

Seismic geomorphology of submarine landslides in the Chalk Group of the Danish Central Graben: implications for reservoir potential

Abstract This study documents a variety of deposits created by submarine landslides within the Upper Cretaceous to lowermost Paleocene Chalk Group in the Danish Central Graben and investigates the impact of remobilization on porosity. Improved visualization of the landslides in 3D seismic data compared with previous studies was facilitated by better seismic data quality for the Chalk Group, the availability of a large stack of stratigraphy-consistent horizons and the use of spectral decomposition data. The illustrated examples are chosen to reflect the spectrum of deformation styles seen in the chalk and all have a well penetrating the affected succession. They include a large collapse (375 km 2 ) of an inversion ridge within the Kraka and Gorm formations, a field of large slide blocks (100–1000 m, 10–26 m) of likely lowermost Danian age embedded in the uppermost Ekofisk Formation, a debris flow system within the uppermost Tor Formation probably originating from the Ringkøbing–Fyn High and fine-grained bottom current sediment waves within the lowermost Danian Ekofisk Formation. In general, porosities are higher (10–25 porosity units) in the remobilized chalk compared with time-equivalent pelagic chalk in nearby reference wells. In earlier studies this has been linked to lack of bioturbation (resulting in limited grain repacking) in the remobilized chalks owing to high sedimentation rates, resulting in a relatively open fabric during initial burial. In contrast, surrounding and covering pelagic deposits could be much more effectively bioturbated, leading to tighter grain packing during burial. The insights of this study help in the seismic characterization of mud-grade carbonate oozes and have important applications in the reservoir modelling of mud-grade carbonate reservoirs (also in light of carbon capture and storage), and in palaeo-reconstructions of pelagic seafloors since submarine landslides provide kinematic indicators.

The development of the eastern Orpheus rift basin, offshore eastern Canada: A case study of the interplay between rift-related faulting and salt deposition and flow

The salt-rich Orpheus rift basin, part of the eastern North American (ENAM) rift system, formed during the Late Triassic to Early Jurassic prior to opening of the Atlantic Ocean. Using a dense grid of 2D seismic-reflection lines, data from nearby wells, and information from adjacent ENAM rift basins, we have established a tectonostratigraphic framework, identified key structural elements, and reconstructed the deformation history for the eastern part of the basin. Our work shows that a series of E-striking, S-dipping faults with normal separation bound the basin on the north. Deformation within the basin is complex with forced folds above deep-seated intrabasin faults, detachment folds, detached thrust faults, and salt diapirs. The synrift evaporite sequence consists of an older massive salt unit that underlies a younger unit with two distinct interfingering facies. Facies A, consisting of salt and interbedded sedimentary rocks (likely shales), developed near the border-fault system and its relay ramps. Facies B, consisting of massive salt with few interbedded sedimentary rocks, developed toward the basin center. The youngest synrift unit accumulated exclusively within minibasins near the northern border-fault system. Based on location, this youngest synrift unit likely consists of coarse-grained and poorly sorted alluvial-fan or talus-slope deposits shed from the footwall. All synrift units are intruded by igneous sheets likely associated with the Central Atlantic Magmatic Province and, thus, are mostly Late Triassic in age (or possibly older). The border-fault system profoundly affected deposition within the eastern Orpheus rift basin by providing pathways for clastic sediment input into the salt-rich basin. These depositional patterns subsequently influenced deformation associated with lateral salt flow during minibasin formation. In regions with interbedded salt, detachment folds and thrust faults developed, whereas salt walls and stocks developed in regions with more massive salt.

Enhancing performance of GaN-based LDs by using GaN/InGaN asymmetric lower waveguide layers

The effects of GaN/InGaN asymmetric lower waveguide (LWG) layers on photoelectrical properties of InGaN multiple quantum well laser diodes (LDs) with an emission wavelength of around 416 nm are theoretically investigated by tuning the thickness and the indium content of InGaN insertion layer (InGaN-IL) between the GaN lower waveguide layer and the quantum wells, which is achieved with the Crosslight Device Simulation Software (PIC3D, Crosslight Software Inc.). The optimal thickness and the indium content of the InGaN-IL in lower waveguide layers are found to be 300 nm and 4%, respectively. The thickness of InGaN-IL predominantly affects the output power and the optical field distribution in comparison with the indium content, and the highest output power is achieved to be 1.25 times that of the reference structure (symmetric GaN waveguide), which is attributed to the reduced optical absorption loss as well as the concentrated optical field nearby quantum wells. Furthermore, when the thickness and indium content of InGaN-IL both reach a higher level, the performance of asymmetric quantum wells LDs will be weakened rapidly due to the obvious decrease of optical confinement factor (OCF) related to the concentrated optical field in the lower waveguide.

Deep learning for predicting permeability logs in offset wells using an artificial neural network at a Waggoner Ranch reservoir, Texas

Permeability logs are critical data used to assess reservoir quality, which can impede the confidence of reservoir productivity without proper characterization. In particular, this can be significant in shale-sand sequence reservoirs that have heterogeneous lithology. Fortunately, permeability logs can be derived from Stoneley waves that are extracted from conventional full-waveform sonic logs. Because sonic logs are not always available in old wells, exploring alternatives to predict permeability is essential. The artificial neural network method is one option that provides elements to develop a model to predict permeability logs in offset wells. Consequently, a model is constructed using standard logs as input data and a Stoneley-wave permeability log as the desired output. These logs are obtained from a new well containing a complete suite of logs including full-waveform sonic data and a permeability log. The open-source Python library Keras provides the environment to generate the model. The model is applied to two nearby wells in which permeability logs do not exist. The borehole separation from the new well to the far well is 2055 ft, and the separation distance to the near well is 1370 ft. The logging data were acquired from wells located in an oil reservoir at Waggoner Ranch in northeast Texas. The reservoir geology is a sand-shale sequence intercepted by thin limestone markers at several depths. Permeability logs are predicted and correlated with other logs and their corresponding lithology. Sands partially saturated with hydrocarbons are identified by their permeability properties at the wells. The sands were previously characterized and mapped from impedance data using a nonlinear inversion of reflection seismic image constrained with well logs. The data analysis demonstrates the usefulness of the neural network approach to predict permeability in reservoirs where offset wells are available and only one well contains a permeability log.

Testing alternative conceptual models of river‐aquifer connectivity and their impacts on baseflow and river recharge processes

AbstractThis study simulates the dynamics of exchange fluxes between Brazos River Alluvium Aquifer and the Brazos River, TX. Seven conceptual models for the connection between the river and the aquifer were simulated in HYDRUS 2D using small‐scale, high‐resolution transects across the river. These models assumed varying aquifer lithology and river incision depths and considered processes such as riverbed clogging and seepage face flows. Observed river stage values were used to specify a time‐variable head boundary, and the simulations were tested against observed hydraulic heads in two nearby monitoring wells. The nearly 1.5 years of sub‐hourly measurements spanned both flood and drought periods. The best‐fit conceptual model supported a hypothesized hydraulic disconnection between the subsurface near the river and the wider alluvial aquifer. In contrast to the assumptions of previous studies, these data were more consistent with the presence of a thin, low‐K structure (such as an abandoned paleochannel) rather than riverbed clogging. Across the range of models evaluated, the average net exchange between the river and the aquifer ranged from 0.016 to 12.4 m3/d/m. Most of the variability was attributed to baseflow across the riverbed, which ranged from 0.18 to 13.1 m3/d/m depending on the model. The ranges of exchange fluxes across the seepage face (0.004 to 2.37 m3/d/m) and recharge from the river to the aquifer (0.1 to 5.63 m3/d/m) were significant, but not as influential. Based on these values, the choice of conceptual model could have a profound impact on the accuracy of numerical models used for river management. Extrapolated across the entire reach, this uncertainty would amount to ±83 m3/s of discharge, equivalent to 34% of the river's discharge near its outlet.

Advancement of power generation system by instalment of solar photovoltaic system for multiple wells: A Case Study

This paper proposes the solution for electricity issues in agriculture sector of particular location in Rajasthan. The issues reported about the availability of ground water and availability of Electricity from electric Grid. The study proposes a centralized solar photovoltaic system for available nearby open wells, which are being operated by diesel engine pump-sets, which emits greenhouse gases and pollute the environment. The proposed centralized photovoltaic system will provide power for submersible pump sets. The additional available power can be stored in batteries, utilized for charging the batteries of electrical vehicles or sell back to electric grid. This paper shows the cost analysis for proposed systems that can be applied and effective centralized solar photovoltaic system in the area considered for study. Centralized solar photovoltaic generation supply to different consumers in different slots and may increase the conflict between consumers, demand side management provide suitable solution to consumers is proposed and analyse in future work.

Machine learning based rate decline prediction in unconventional reservoirs

The main objective of this paper is to develop a novel machine learning based model that can accurately predict the decline curves and EUR (Estimated Ultimate Recovery) for new wells based on the data collected from nearby wells. This is because decline curves are easier and faster alternative to complex reservoir simulators which perform computationally expensive operations. In contrast to this, decline curves require only a few parameters in the equation which can be easily collected from the existing data of the wells. In this study, first we collected the well data corresponding to well parameters such as initial monthly oil flow rate ( q i ), well completion parameters (i.e., no. of fracturing stages, completed length, amount of proppant used, amount of fracturing fluid used), well location parameters (TVD Heel-Toe Difference), reservoir fluid properties (Oil API Gravity, initial 24 h period Gas-Oil Ratio (GOR), initial 24 h period Gas Produced, initial 24 h period Oil Produced), flowing tubing pressure, casing pressure tubing size,choke size from publicly available databases of the Eagle Ford Shale formation Texas RRC (Railroad Commission of Texas). Wells were selected randomly and only those wells were finally included for the study whose data of the all the required parameters were available. The model parameters were estimated by fitting the production data to the decline curve models. Artificial Neural Network (ANN) was employed to build Machine learning models as a function of the above well parameters for the corresponding model parameters. The decline curves for new or existing wells were rapidly predicted using these models. In order to estimate the predictive accuracy of these models when applied to new or test wells cross validation technique such as k-fold cross validation was employed. These models were also used to predict EUR for the test wells. Additionally, feature selection was also done using algorithms such as Chi Square Test (χ2) and Minimum Redundancy Maximum Relevance (MRMR) Algorithm to determine the relative importance of predictor variables in predicting EUR. The predictor variables were successfully linked to SEDM (Stretched Exponential Decline Model) decline curve parameters (n and τ) in a random set of oil field well data. The relative influences of various well parameters were also examined to determine the hidden relationship between them. The novelty in this study lies in the algorithm and dataset that we used for the rate decline prediction in Eagle Ford data set. Although, this paper has referenced some previous papers where machine learning has been used to make prediction, but this paper presents use of new algorithm as well as a new dataset. As more data gets available, there is definitely extra room for further data analysis and improved results using machine learning methods. In future, the number of wells can be increased and the updated results can again be submitted after investing more time. It should be noted here that data downloading and preparing takes most of the time for such study especially when dealing with oil and gas data.

Groundwater‐stream connectivity from minutes to months across United States basins as revealed by spectral analysis

AbstractStream corridors are dynamic places where streams and aquifers are connected and interact to various degrees, depending on geology, climate, stream morphology, and water use. Water table fluctuations propagate through the unconfined aquifer and are linked with changes in solute export to streams and biogeochemical transformations in floodplain soils. Through publicly available USGS data, this study aims to better understand the behaviour of stream‐groundwater connectivity and water table fluctuations by analysing continuous time series of water levels from 17 pairs of stream gauges and nearby (&lt;100 m) groundwater monitoring wells. Sites are located within 8 of 18 major hydrologic units (HUC‐2) across the contiguous United States and span a variety of stream sizes, climates, and land use practises. More than 50% of sites have a water table that remains within 3 m of the land surface year‐round. Energy spectral densities and cross‐wavelet transformations generally reveal strong coherence between the water table and stream stage over daily to monthly periods. The transfer function, which describes relative variations between the water table and stream stage, shows that 10 of 17 sites are more stream‐dominated at daily and monthly frequencies, meaning that water level fluctuations are greater in the stream and propagate into the aquifer. Only 1 of 17 sites is more groundwater‐dominated at daily and monthly frequencies, meaning that water level fluctuations are greater in the aquifer. This study shows the utility of frequency‐domain analysis for revealing specific timescales of stream‐aquifer interaction.

Validation of in situ and remote sensing-derived methane refinery emissions in a complex wind environment and chemical implications

Air pollution emissions from ports are major sources of contaminant exposures to downwind communities. Elevated pollutant concentrations relate to emissions from port activities and nearby heavy industries including refining. Methane (CH4) in the 66 Refinery plume, located west of the Los Angeles Port, provided a real-world validation opportunity for in situ-derived emissions in comparison with imaging spectroscopy-derived emissions.Airborne remote sensing data were acquired by the airborne thermal infrared Mako imaging spectrometer, while contemporaneous in situ meteorology and trace gas measurements and air samples were collected using a ground based mobile system, SISTER™ (Standard Instrumentation Suite: Truck Enabled for Response). SISTER measures 13 trace gases, meteorology, aerosol size distributions, and vertical aerosol profiles at up to highway speeds. Real-time data visualization is used to target sample collection. SISTER & Mako data were collected 19 June 2020 with additional SISTER data including air samples collected 16 July 2020.In situ CH4 emissions were derived from two series of inversion plume models with different numbers of plumes for comparison with Mako reference emissions. The informed series used Mako spatial data, whereas the uninformed series did not. In situ survey data and air samples also were collected for two nearby oil wells and found significantly elevated alkanes through undecane and aromatics in the refinery and oil well plumes compared to nearby reference air.Remote sensing CH4 emissions were 69 g s−1 (2.18 Gg yr−1), within 20% of the informed in situ emissions of 87 g s−1 (2.73 Gg yr−1) and within 10% of four-plume uninformed emissions of 80 g s−1 (2.51 Gg yr−1). On an annualized basis, this is 10% of estimated US refining CH4 emissions. Derived emissions were robust – agreeing within 10–20% for the various models; however, partitioning between plumes was very poor for the uninformed plumes because neglecting wind veering caused emissions mis-assignment. Monte Carlo simulation emission uncertainties were 12–13% for 19 June and 24–25% for 16 July when emissions were much lower, 0.25 Gg CH4 yr−1.This study emphasized the importance of fine-scale structure in winds with respect to characterizing emissions at the sub-facility (kilometer) scale, while also showing robust estimation of emissions at the facility scale by in situ survey for a wide range of models. Wind structure on kilometer and smaller scales plays a key role in understanding the fate of emissions.

Spatial and temporal dynamics and potential pathogenicity of fecal coliforms in coastal shallow groundwater wells.

Access to water through shallow groundwater wells is a common practice in coastal settlements. This, coupled with a lack of planning for wastewater disposal promotes fecal contamination of groundwater and poses a threat to human health. Here, the spatial and temporal dynamics of groundwater fecal contamination was evaluated during summer and winter (2013 and 2014) in a coastal protected area having a high touristic relevance (Cabo Polonio, Uruguay). Fecal coliforms (FC) abundance in groundwater was significantly higher during summer, related to an influx of ~ 1000 tourists per day. A significant spatial autocorrelation was found in 2014, when the abundance of FC in a well was influenced by its three nearest wells (Moran and Geary tests). The applied statistical models (mixed models) indicated that total phosphorus and organic matter were the variables significantly explaining FC abundance. The risk for human health was estimated using groundwater-extracted DNA and qPCR of genes encoding for E. coli virulence factors (stx1, stx2, and eae). Potential Shiga toxin-producing enteropathogenic and enterohemorrhagic pathotypes were detected, even at FC abundances ≤ 1CFU (100mL-1). Moreover, we found that contaminated groundwater reached the beach, being the presence of FC in sand detected even in winter and showing its highest frequency nearby groundwater wells consistently having high FC abundance (hot spots). Altogether, the results show that fecal contamination of shallow groundwater in Cabo Polonio involves a risk for human health that intensifies during summer (associated to a significant increase of tourists). This contamination also impacts the beach, where FC can remain through the whole year.