Groundwater flow modeling in the basaltic hard rock area of Maharashtra, India

The ecological sustainable development and planning of groundwater resources is an excessive challenge for many countries currently facing water insufficiency. The main focus of this work was to determine the direction of groundwater flow, head value, and water level using the steady-state finite difference model (MODFLOW software) in basaltic formations in Maharashtra, India. The MODFLOW model was integrated with ground data using Geographic Information System (GIS) for sustainable groundwater resource management in the hard rock terrain. The MODFLOW-2005 model simulated the interaction between heads and time in 2014–18 by steady-state conditions. In this present study, four observation wells were selected. During the field survey, four observation wells have been monitored regularly as per the Central Groundwater Board guidelines. MODFLOW software has been conceptualized as a double-layered rigid and fractured aquifer area feast over 18,312 m × 11,265 m area. This research demonstrates that the integration of GIS, conventional fieldwork, and mathematical model can support to understand groundwater demand and supply in a better way.

Converting Development Wells to Observations Wells to Aid Reservoir and Overburden Monitoring for CO2 Sequestration in a Depleted Carbonate Field

Measurement, Monitoring & Verification (MMV) is crucial to ascertain both containment and conformance in Carbon Capture & Storage (CCS) projects. The magnitude of parameters to be monitored along with the technologies to be adopted could be very cost intensive and impact overall project Net Present value (NPV). To rationalize the associated costs and maximize the value propositions of existing infrastructure, the development wells in depleted field provide the opportunity to reduce the MMV cost by converting them into observation wells. However, the wells are to be analyzed for their strategic location in the reservoir, fit for purpose plug & abandonment plan and the apt technologies that can be implemented for both reservoir & overburden monitoring. Development wells in the identified depleted field are 30-40 years old and were not designed considering high CO2 concentration. In consequence, the possibility of well leakage due to accelerated corrosion channeling, cracks, along the wellbore cannot be ignored and requires careful evaluation. Rigorous process has been adopted in assessing the feasibility for converting existing producers into observation wells. Wells basis of designs disparity between the producer and the required observation well governs the selection for conversion to observation wells or plugging and abandonment. The reservoir simulation and coupled modelling predict that CO2 plume will reach all wells penetrating the storage reservoir during the initial injection phase. Out of 9 available producers, 2 strategically located wells have been evaluated for conversion based on end injection reservoir pressure of ∼3450psi. Quantitative CO2 leakage through the observation wells has been numerically computed based on all possible pathways for risk characterization. The permeable/perforated zones in these two wells are to be isolated along with the cap-rock restoration technique at deepest depth of ∼4000ft TVDSS. This will ensure the wells are safe & accessible for monitoring CO2 plume migration, CO2 leakage and well integrity by analyzing acquired DAS-VSP, DTS, DPS data and well logs. This paper elaborates unique challenges associated with identifying strategic wells for conversion to observation wells. Minimum plug setting depths, ranging from 3720-3880ft TVDSS, for abandonment of 9 development wells are derived based on fracture gradient and maximum horizontal stress. 2 observation wells require deeper plug setting depth to make caprock accessible at ∼4000ft TVDSS to be restored by utilizing either perforate-wash-cement (PWC) or section milling. Based on the subsurface illumination modelling, deployment of fiber-optics sensors in observation wells promises a cost-effective solution for monitoring CO2 plume migration and leakage by acquiring 4D DAS-VSP survey. Conversion of producers to observation wells promises cost effective MMV application for CO2 plume migration and leakage monitoring along with periodic temperature, pressure, and CO2 concentration measurement in overburden.

Evaluation of transmissivity in a fractured aquifer—the Nyanzari wellfield, Burundi

Due to population growth, the city of Gitega in the central part of Burundi is lacking drinking water. Therefore, the national urban water supply company decided to expand the Nyanzari wellfield by drilling additional wells.Two additional wells were drilled to 80 m (F7.2) and 85 m (F8bis) depths. Step tests followed by 72-hours aquifer tests were performed in each well. Results indicate bilinear flow followed by linear flow and radial flow in F7.2. No reaction was observed in observation wells. Fracture-matrix transmissivity was estimated at 3 · 10−4 m2/s. In the case of F8bis, linear flow in an infinite flow fracture followed by radial flow was visible. Reaction was measured in observation wells. Transmissivity was estimated at 3.3 · 10−3 m2/s.Both wells lie no more than 300 m apart, but no evidence of interference between them was depicted during the tests. It appears that two independent fracture systems prevail in the wellfield.

Using Freshwater Heads to Analyze Flow Directions in Saline Aquifers of the Pingtung Plain, Taiwan

The hydraulic head is the most important parameter for the study of groundwater. However, a head measured from observation wells containing groundwater of variable density should be corrected to a reference density (e.g., a freshwater head). Some previous case studies have used unknown density hydraulic heads for calibrating flow models. Errors arising from the use of observed hydraulic head data of unknown density are, therefore, likely one of the most overlooked issues in flow simulations of seawater intrusion. Here, we present a case study that uses the freshwater head, instead of the observed hydraulic head, to analyze the flow paths of saline groundwater in the coastal region of the Pingtung Plain, Taiwan. Out of a total of 134 observation wells within the Pingtung Plain, 19 wells have been determined to be saline, with Electric Conductivity (EC) values higher than 1500 μS/cm during 2012. The misuse of observed hydraulic heads causes misinterpretation of the flow direction of saline groundwater. For such saline aquifers, the determination of a freshwater head requires density information obtained from an observation well. Instead of the purging and sampling method, we recommend EC logging using a month interval. Our research indicates that EC values within an observation well within saline aquifers vary not only vertically but also by season.

Decision Support for Local Water Authorities in Guantao

Policy selection and implementation rely on monitoring data and technical decision support tools. Monitoring data of Guantao County include groundwater levels at 55 observation wells, pumping rates of 7600 wells, surface water flows, precipitation, and land use in monthly time steps.

Groundwater Level Prediction Using a Multiple ObjectiveGenetic Algorithm-Grey Relational Analysis Based Weighted Ensemble of ANFIS Models

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited groundwater reserves and developing a useful groundwater abstraction management strategy. The purpose of this study was to assess the predictive accuracy and estimation capability of various models based on the Adaptive Neuro Fuzzy Inference System (ANFIS). These models included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimization-ANFIS (PSO-ANFIS), and traditional Hybrid Algorithm tuned ANFIS (HA-ANFIS) for the one- and multi-week forward forecast of groundwater levels at three observation wells. Model-independent partial autocorrelation functions followed by frequentist lasso regression-based feature selection approaches were used to recognize appropriate input variables for the prediction models. The performances of the ANFIS models were evaluated using various statistical performance evaluation indexes. The results revealed that the optimized ANFIS models performed equally well in predicting one-week-ahead groundwater levels at the observation wells when a set of various performance evaluation indexes were used. For improving prediction accuracy, a weighted-average ensemble of ANFIS models was proposed, in which weights for the individual ANFIS models were calculated using a Multiple Objective Genetic Algorithm (MOGA). The MOGA accounts for a set of benefits (higher values indicate better model performance) and cost (smaller values indicate better model performance) performance indexes calculated on the test dataset. Grey relational analysis was used to select the best solution from a set of feasible solutions produced by a MOGA. A MOGA-based individual model ranking revealed the superiority of DE-ANFIS (weight = 0.827), HA-ANFIS (weight = 0.524), and HA-ANFIS (weight = 0.697) at observation wells GT8194046, GT8194048, and GT8194049, respectively. Shannon’s entropy-based decision theory was utilized to rank the ensemble and individual ANFIS models using a set of performance indexes. The ranking result indicated that the ensemble model outperformed all individual models at all observation wells (ranking value = 0.987, 0.985, and 0.995 at observation wells GT8194046, GT8194048, and GT8194049, respectively). The worst performers were PSO-ANFIS (ranking value = 0.845), PSO-ANFIS (ranking value = 0.819), and DE-ANFIS (ranking value = 0.900) at observation wells GT8194046, GT8194048, and GT8194049, respectively. The generalization capability of the proposed ensemble modelling approach was evaluated for forecasting 2-, 4-, 6-, and 8-weeks ahead groundwater levels using data from GT8194046. The evaluation results confirmed the useability of the ensemble modelling for forecasting groundwater levels at higher forecasting horizons. The study demonstrated that the ensemble approach may be successfully used to predict multi-week-ahead groundwater levels, utilizing previous lagged groundwater levels as inputs.

Assessment of Groundwater Resources in Water Spring Areas Using Geophysical Methods, Northern UAE

The Khatt, Madab, and Al Ghmour Springs are important springs in UAE. They are located in the foothills of the Oman Mountains. The water temperature of these springs is relatively high (approximately 39 °C). Overexploitation of fractured aquifers negatively affected the waterflows from these springs. The outflows from these springs are time-dependent and range from 10 to 50 L/s (until 1998) to 1–10 L/s (until 2010). To assess the current conditions of the spring areas, relevant data were carefully reviewed, analyzed, and stored in a GIS database. A 3D-geological model was developed for the Khatt Springs area, which allowed different types of visualizations, calculations, and predictions. In addition, a 2D earth resistivity imaging survey was performed to evaluate the available groundwater resources, characterize the major faults/fractures feeding these springs, and to determine the locations of saturated fractures and karsts and the thicknesses of the unconsolidated materials in the wadis. Borehole and drilling information from observation wells were utilized to enhance the analysis of the earth resistivity imaging data. The described procedures and acquired results indicated that it was possible to determine the locations of two production wells for feeding Al Ghmour Springs with water during drought periods to keep it alive.

Groundwater Drought and Cycles in Xuchang City, China

The urban groundwater system is complex and affected by the interaction of natural and human factors. Groundwater scarcity can no longer reflect this complex situation, and the concept of groundwater drought can better interpret this situation. The groundwater drought cycle is the time interval in which groundwater droughts occur repeatedly and twice in a row. The study of the groundwater drought cycle can more comprehensively grasp the development characteristics of the groundwater drought, which is of great importance for the development, utilization, and protection of groundwater. This study used monthly observation data from seven groundwater wells in Xuchang, China, in the period 1980–2018. We applied the Kolmogorov–Smirnov test to select the best fitting distribution function and constructed a Standardized Groundwater Index (SGI). We analyzed groundwater drought at different time scales and used Morlet’s continuous complex wavelet transform to analyze the groundwater drought cycles. The following results were obtained: 1) the maximum intensity of groundwater drought in the seven observation wells ranged from 104.40 to 187.10. Well-3# has the most severe groundwater drought; 2) the drought years of well-5# were concentrated in 1984–1987 and 2003–2012 and those in the other wells in 1994–1999 and 2014–2018; and 3) the groundwater drought cycles in the seven observation wells were 97–120 months, and the average period is about 110 months. The cycle length had the following order: well-7# > well-4# > well-5# > well-2# > well-1# > well-3# > well-6. Therefore, Morlet wavelet transform analysis can be used to study the groundwater drought cycles and can be more intuitive in understanding the development of regional groundwater droughts. In addition, through the study of the Xuchang groundwater drought and its cycle, the groundwater drought in Xuchang city has been revealed, which can help local relevant departments to provide technical support and a scientific basis for the development, utilization, and protection of groundwater in the region.

Toward Controllable Infill Completions Using Frac-Driven Interactions FDI Data

Infill completions have been explored by many operators in the last few years as a strategy to increase ultimate recovery from unconventional shale oil reservoirs. The stimulation of infill wells often causes pressure increases, known as fracture-driven interactions (FDIs), in nearby wells. Studies have generally focused on the propagation of fractures from infill wells and pressure changes in treatment wells rather than observation wells. Meanwhile, studies regarding the pressure response in the observation (parent) wells are mainly limited to field observations and conjecture. In this study, we provide a partialcorrective to this gap in the research.We model the pressure fluctuations in parent wells induced by fracking infill wells and provide insight into how field operators can use the pressure data from nearby wells to identify different forms of FDI, including fracture hit (frac-hit) and fracture shadowing. First,we model the trajectory of a fracture propagating from an infill well using the extended finite element methods (XFEM). This method allows us to incorporatethe possible intersection of fractures independent of the mesh gridding. Subsequently, we calculate the pressure response from the frac-hit and stress shadowing using a coupled geomechanics and multi-phase fluid flow model. Through numerical examples, we assess different scenarios that might arise because of the interactions between new fractures and old depleted fractures based on the corresponding pressure behavior in the parent wells. Typically, a large increase in bottomhole pressure over a short period is interpreted as a potential indication of a fracture hit. However, we show that a slower increase in bottomhole pressure may also imply a fracture hit, especially if gas repressurization was performed before the infill well was fracked. Ultimately, we find that well storage may buffer the sudden increase in pressure due to the frac-hit. We conclude by summarizing the different FDIs through their pressure footprints.