Simulation of oil spill infiltration and redistribution in a shallow aquifer

Simulations of oil spill infiltration and redistribution in a shallow aquifer were conducted in this work to quantify their effects on groundwater. Results showed that flow of oil spills can be adequately described by infiltration and redistribution patterns within the domain. Without the influence of rainfall, the contaminant plume pervaded the water table within one year of the spill through the influence of dissolution, diffusive and convective mechanisms. The plume advanced in the domain first by domain wall trailing in a manner suggestive of oil-wetting characteristics followed by bulk plume movement. Simultaneous infiltration with rainfall increased the rate of contaminant penetration and aided the plume front further into the domain. Without influence of rain, uncontaminated water can be found at a depth beyond 30 m from the spill surface at 30 years after the spill, while the possibility of clean water with influence of rainfall, at the same period of time, became remote even up to the bottom of the aquifer as the rainfall drives the plume into the furthest depth though, this is accompanied by cleaner water body at the upper portion of the aquifer. It was found that the impacts of contaminants on aquifer water are influenced by contaminant components, wettability of the aquifer, annual rates of rainfall, boundary conditions of the source and possibly size of the domain. Findings in this report point to the needs for quicker clean up exercises and identification of multi-approach procedures for different spill scenarios.Key words: Simulation, oil spills, infiltration, redistribution, Niger Delta

ANN-derived equation and ITS application in the prediction of dielectric properties of pure and impure CO₂

High-performing equation has been step-wisely extracted from artificial neural network (ANN) simulation and subsequently applied for the prediction of the dielectric properties of pure and impure CO2. Data of relative permittivity (εr) for pure and impure CO2 were used in the ANN to train different ANN structures so that the network can recognise and predict CO2 property under different conditions. Analyses of the results from the training showed that single-layer ANN model [3-6-1] outperformed others. From this best-performing ANN structure, a single mathematical equation was extracted that can be employed in predicting εr for pure CO2 and CO2-ethanol mixture, even without access to ANN software. Using this ANN-based mathematical model, predictions of the relative permittivity (εr) for pure CO2 and CO2-ethanol mixture were performed, under different temperatures and pressures and at different ethanol concentrations. Under similar conditions, the output of the model provides good match with the original experimental εr. With increment in ethanol concentration, the model correctly predicted the rise in εr for the mixture. Also, it was shown that the εr rises with an increase in pressure but decreases with a rise in temperature. The work showed the reliability and applicability of the ANN in characterizing and predicting the dielectric property of pure CO2 as well as its mixture or impurities. The model developed and the techniques demonstrated in this work offers immense benefits and guides for researchers, who may want to explore the behaviours of a pure compound and its mixtures/impurities using ANN, as well as those interested in derived mathematical model from statistical computation tool like ANN

Physico-chemical and dielectric parameters for the monitoring of carbon sequestration in basalt and silica media

Currently, there are concerns about the safety of carbon sequestration in the geological media. To assuage this concern, scientists and engineers have the tasks to demonstrate fool-proof and comprehensive techniques that can monitor the movement, or otherwise, concentration of the injected CO2 in the subsurface. In this work, well-defined laboratory experiments were used to demonstrate the key physico-chemical characteristics and dielectric parameters that are useful in monitoring carbon sequestration sites. The porous materials used were basalt and silica sand samples to demonstrate the possibility of CO2 injection into different media. To simulate the resident fluids, distilled and brine water samples were used in separate experimentations. Also, the pressures and temperatures were chosen to correspond to different geological depths which are relevant for CO2 injection. The pH, bulk electrical conductivity (σୠ) and bulk dielectric permittivity (εୠ) of the system were measured for the two different media. Onne hand, the decrease in pH was clearly observed in both the basalt and silica sand after the exposure to CO2. On the other hand, σୠ and εୠ increased as CO2 was injected. Our results further revealed a higher ion mobilization potential in basalt medium than that in silica sand. This results in lower pH and higher electrical conductivity in the basalt medium than the silica medium. Thus, a simultaneous measurement of pH, σୠ and εୠ are proposed as a multiparameter approach to monitor CO2 leakage from the storage reservoir. As far as we are aware, this is the first work in the open literature that reports simultaneous dielectric and electrical behaviours of CO2-water-porous media system for basalt porous medium in connection with carbon sequestration

Geo-electrical Characterisation for CO2 Sequestration in Porous Media

This is a post-peer-review, pre-copyedit version of an article published in Environmental Processes. The final authenticated version is available online at: http://dx.doi.org/10.1007/s40710-017-0222-2.Developing monitoring strategies for the detection and monitoring of possible CO2 leakage or migration from existing and anticipated storage media are important because they can provide an early warning of unplanned CO2 leakage from a storage site. While previous works have concentrated on silicate and carbonate porous media, this work explores geoelectrical techniques in basalt medium in a series of well-defined laboratory experiments. These were carried out to identify the key factors which affect geoelectrical monitoring technique of CO2 in porous media using low cost and efficient time domain reflectometry (TDR). The system has been set up for simultaneous measurement of the bulk electrical conductivity and bulk dielectric permittivity of CO2-water-porous media system in silica sand, basalt and limestone. Factors investigated include pH, pressure, temperature, salinity, salt type and the materials of the porous media. Results show that the bulk electrical conductivity and dielectric permittivity decrease as water saturation decreases. Noticeably, electrical conductivity and permittivity decrease due to the changes in water saturation and the relationship remains the highest in limestone except at the start of the experiment. Also, an increase in temperature, pressure and salinity tend to increase the bulk electrical conductivity (σb) and permittivity (εb) of the CO2-water-porous media system during the drainage experiment. On the other hand, pH and concentrations of different types of salt do not seem to have significant effect on the geoelectrical characteristics of the system. It was evident that Archie’s equation fit the experimental results well and the parameters obtained were in good agreement with those in the literatures. The regression shows a good reliability in the prediction of electrical properties during the monitoring process of CO2 sequestration

Dynamic Effect in Capillary Pressure – Saturation Relationship Using Lattice Boltzmann Simulation

Soil water retention curve (SWRC) as the constitutive relationship of hydro-mechanical coupling bridge of unsaturated soil has been experimentally investigated decades regarding impacts from dynamic effects in sandy soil and deformation in soft soil. However, due to inaccessibility of observation of microscale dynamic capillary behavior in geotechnical testing scale, most of the experimental methods can only provide the deviation between static SWRC and dynamic SWRC on drainage and imbibition. With the development of Computational Fluid Dynamic (CFD) simulation, several numerical methods so far can be utilized to investigate the soil water retention behavior in both micro- and macro-scale and upscaling between them, such as pore network model, Navier-Stokes integrated with Volume of Fluid and Level Set Method. Nevertheless, none of them provide a vision of interaction between fundamental fluid fractions in order to replicate the physical behavior of fluid tension from their mathematical expression. Compared to those CFD methods, Lattice Boltzmann Methods (LBM) is formulated on microscale for simulation of fluid dynamics. In addition to the interaction forces between fluid-fluid and fluid-solid phases, it fundamentally replicates the physical meaning of immiscible multiphase flow behavior in porous media. Therefore, LBM is selected to investigate the dynamic effect in soil water retention behavior in this study. The aim is to investigate the dynamic capillary pressure (soil suction in soil mechanics) varying with the saturation of each phase in a Representative Elementary Volume (REV) domain