Preliminary reservoir model of enhanced coalbed methane (ECBM) in a subbituminous coal seam,Huntly Coalfield,New Zealand

The Huntly coalfield has significant coal deposits that contain biogenically-sourced methane. The coals are subbituminous in rank and Eocene in age and have been previously characterised with relatively low to moderate measured gas (CH₄) contents (2–4 m³/ton). The CO₂ holding capacity is relatively high (18.0 m³/ton) compared with that of CH₄ (2.6 m³/ton) and N₂ (0.7 m³/ton) at the same pressure (4 MPa; all as received basis). The geothermal gradient is also quite high at 55 °C/km.A study has been conducted which simulates enhancement of methane recovery (ECBM) from these deposits using a new version of the TOUGH2 (version 2) reservoir simulator (ECBM-TOUGH2) that can handle non-isothermal, multi-phase flows of mixtures of water, CH₄, CO₂ and N₂. The initial phase of the simulation is CH₄ production for the first 5 years of the field history. The model indicates that methane production can be significantly improved (from less than 80% recovery to nearly 90%) through injection of CO₂. However, although an increase in the rate of CO₂ injection increases the amount of CO₂ sequestered, the methane recovery (because of earlier breakthrough with increasing injection rate) decreases. Modeling of pure N₂ injection produced little enhanced CH₄ production. The injection of a hypothetical flue gas mixture (CO₂ and N₂) also produced little increase in CH₄ production. This is related to the low adsorption capacity of the Huntly coal to N₂ which results in almost instantaneous breakthrough into the production well.     

A review of the community flood risk management literature in the USA: lessons for improving community resilience to floods

Natural Hazards - This study systematically reviews the diverse body of research on community flood risk management in the USA to identify knowledge gaps and develop innovative and practical...     

Evaluation of slurry settling rate using fuzzy rule-based modeling

The pressure acid leach process is the most widely used method of metal extraction from laterite ores. The self-weight settling rate of the ore slurries governs the throughput of the process and is improved by adding synthetic polymers. The charge density, molecular weight, and dosage of the polymers are the key factors influencing the settling rate of the slurries. This interdisciplinary paper uses the geotechnical understanding of hindered sedimentation for a mining engineering application. A conceptual fuzzy rule-based model was developed to evaluate the initial hydraulic conductivity of polymer-modified laterite ore slurries. Identification of control parameters and selection of the model architecture (fuzzy rule-base) were based on expert judgment. The developed model was trained and validated using bench-scale settling test data. The model reasonably predicts the initial hydraulic conductivity of polymer-added laterite ore slurry with a coefficient of determination of 0.75. Rank correlation coefficient-based sensitivity analyses indicated that charge density was the most significant polymer parameter followed by molecular weight and then by dosage. Charge density accounted for more than 97% of variability in the initial hydraulic conductivity estimates for both anionic and cationic polymers.     

High-resolution regional gravity field model of Pakistan based on best residual terrain model (RTM) of topography and interpolation techniques

This study focuses on the development of absolute gravity model for Pakistan based on best possible residual terrain model of gravity using residual terrain modeling technique. The datasets used for the development of model are observed gravity, global gravity models, and Shuttle Radar Topographic Mission (SRTM30) elevation data. The residual terrain modeling technique has been used in the remove-restore procedure for smoothing the observed gravity field. Different topographic elevation models were tested in the model selection and one best possible model with minimum mean and standard deviation was selected for residual terrain effects. Least square collocation technique has been used for quality control and error estimates. The best possible covariance model was established from residual gravity for onward prediction of gravity anomalies at the earth surface for error and prediction analysis. The residual terrain effect of gravity, value of free air anomaly from EGM96, and observed free air anomaly are added to normal gravity to compute the absolute gravity at earth surface. The prediction of these parameters is made by employing Lagrange interpolation with least square adjustment. The results are compared with ～5% randomly selected data points not utilized for the development of covariance function and/or model development. Spline interpolation technique has also been used for the prediction of gravity field-related parameters. Lagrange interpolation exhibits relatively superior results over spline-based interpolation. This is as per expectation due to the reason that additional gridding for spline interpolation filters the signal part as well. This fact is evident from the results of spline interpolation of Grid-I and Grid-II with relatively better prediction results in Grid-I. This version of the model is capable of prediction having limiting error of 30 mGal. The predicted results show that 96.16% of prediction data falls within above-mentioned limit with Lagrange interpolation technique with least square adjustment for whole Pakistan area. The adverse effect of gridding is absent in case of Grid-I due to relatively flat areas and predicted data matches totally with control values for both spline as well as Lagrange interpolations. However, in case of Grid-II which includes high mountains of Himalaya, gridding effect is present and the accuracy of the predicted results falls to ～92%. The computed results have been compared with absolute values predicted using EGM96 and EGM2008 models as well. The gravity field recovered with PAKGM model is much better, i.e., ～ 96.16%, than both with EGM96 and EGM2008 which is about 85% only.     

Optimization of Blasting-Associated Costs in Surface Mines Using Risk-based Probabilistic Integer Programming and Firefly Algorithm

Natural Resources Research - Blasting outcomes have significant impacts on downstream mining operations such as loading, hauling, crushing, milling, and mineral processing. An ideal blasting plan...     

Probabilistic risk analysis using ordered weighted averaging (OWA) operators

The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complexities increase further when the empirical relationships are not strong enough to derive physical-based models. In this paper, ordered weighted averaging (OWA) operators are proposed to estimate the system load. The risk of failure is estimated by assuming normally distributed reliability index. The proposed methodology for risk analysis is illustrated using an example of nine-input parameters. Sensitivity analyses identified that the risk of failure is dominated by the attitude of a decision-maker to generate OWA weights, missing input parameters and system capacity.

Heterogeneous data management and modeling for the gravimetric geoid model: a review study in Pakistan

Arabian Journal of Geosciences - The gravimetric geoid model can be used as vertical reference in surveying and other related technologies. It is being developed by NESCOM in collaboration with the...     

Evaluating water reuse applications under uncertainty: generalized intuitionistic fuzzy-based approach

Water reuse is a viable option to increase urban water supply, especially under new realities of climate change and increasing anthropogenic activities. A sustainable water reuse application should be cost-effective and have acceptable health risk to consumers. Water reuse application evaluation is complex because data acquisitions are usually associated with the problems of uncertainty, hesitancy, and parameterization. In this paper, a generalized intuitionistic fuzzy soft set (GIFSS)-based decision support framework is proposed to provide an effective approach to describe uncertainty and hesitancy in an intuitionistic fuzzy number. In addition, the modified measures of comparison and similarity are proposed to compare water reuse applications. Then, the proposed framework is applied to the City of Penticton (British Columbia, Canada) to evaluate seven water reuse applications. The evaluation results show that the applications of garden flower watering and public parks watering are the most preferred alternatives, which are consistent with the existing practice in the city. Furthermore, the results are highly affected by the generalized parameter and the weights of evaluation criteria. Both the comparison measure-based and similarity measure-based evaluations within the same GIFSS-based framework produce consistent results, indicating an applicable and efficient methodology.