The Influence of Mineralogy and Cation Exchange Capacity toward Electrical Resistivity Value

Electrical Resistivity Tomography (ERT) is a method used for subsurface profiling in soil to characterize soil thickness, fracture zones, soil saturation, salinity and groundwater based on the electrical resistivity value (ERV). There are multiple factors that influence the electrical resistivity value, such as the porosity, degree of saturation, mineralogy, density, cation exchange capacity (CEC), and water resistivity. For this study, the effect of CEC towards resistivity value is studied via controlling the mineralogy factor, saturation, porosity and water resistivity. Thus, via understanding the CEC factor able to relate the resistivity and mineralogy of soil. This study is using a few common minerals in soil and rock, such as kaolinite, montmorillonite, illite, quartz, mica, and feldspar. The particle sizes of all tested minerals were passing 0.063mm sieve. The basic index properties of minerals such as particle size distribution, specific gravity, and Atterberg limit were tested. The instruments of Terrameter LS2 and resistivity box were used to determine the resistivity value of minerals. The Atomic Absorption Spectroscopy (AAS) machine was used to analyze the CEC of minerals via dilute with the ammonium acetate solution. The porosity and degree of saturation of minerals mixed with distill water were controlled between the range of 0.5 to 0.6 and 20% to 100%. The CEC of each mineral has different value, where the lowest and the highest minerals CEC in this study were Kaolinite and Montmorillonite at 1 and 70, respectively. The electrical resistivity values decrease with the increasing of CEC value and degree of saturation. The mineral that has higher CEC indicates lower resistivity value. Meanwhile, via increasing the degree of saturation of minerals were decrease its resistivity values.

Inversion-based Interpretation of Borehole Spontaneous Potential Measurements for Accurate Estimation of Water Resistivity in the Presence of Shoulder-Bed and Mud-Filtrate Invasion Effects

Electrical resistivity of formation water is a fundamental property used to quantify in situ water quality for human consumption or for assessment of hydrocarbon pore volume. Resistivity interpretation methods commonly used to quantify the electrical resistivity of formation water invoke rock porosity and fitting parameters that require additional and independent core measurements. Alternatively, the spontaneous potential (SP) log can be used to calculate water resistivity without knowledge of rock porosity in wells drilled with water-based mud. In combination with resistivity and gamma-ray logs, SP logs can be used to estimate water quality, apparent volumetric concentration of shale, and for qualitative assessments of permeability. However, SP logs often exhibit both shoulder-bed and mud-filtration effects; these effects need to be mitigated before using SP logs for calculation of water resistivity. We develop a new inversion-based method to simultaneously mitigate shoulder-bed and mud-filtrate invasion effects present in SP logs via fast numerical simulations based on Green functions. The interpretation method is implemented on SP logs acquired across aquifers with various degrees of complexity using noisy synthetic and field measurements to estimate equivalent NaCl concentration, radius of mud-filtrate invasion, and sodium macroscopic transport number. Interpretation results compare well to those obtained from resistivity and nuclear logs, provide estimates of uncertainty, and can incorporate a priori knowledge of aquifer petrophysical properties in the estimation.

Compatibilization of Starch/Synthetic Biodegradable Polymer Blends for Packaging Applications: A Review

The health and environmental concerns of the usage of non-biodegradable plastics have driven efforts to explore replacing them with renewable polymers. Although starch is a vital renewable polymer, poor water resistivity and thermo-mechanical properties have limited its applications. Recently, starch/synthetic biodegradable polymer blends have captured greater attention to replace inert plastic materials; the question of ‘immiscibility’ arises during the blend preparation due to the mixing of hydrophilic starch with hydrophobic polymers. The immiscibility issue between starch and synthetic polymers impacts the water absorption, thermo-mechanical properties, and chemical stability demanded by various engineering applications. Numerous studies have been carried out to eliminate the immiscibility issues of the different components in the polymer blends while enhancing the thermo-mechanical properties. Incorporating compatibilizers into the blend mixtures has significantly reduced the particle sizes of the dispersed phase while improving the interfacial adhesion between the starch and synthetic biodegradable polymer, leading to fine and homogeneous structures. Thus, Significant improvements in thermo-mechanical and barrier properties and water resistance can be observed in the compatibilized blends. This review provides an extensive discussion on the compatibilization processes of starch and petroleum-based polymer blends.

Quantitative Evaluation of Water Flooding in a Low Resistivity Heavy Oil Reservoir with NMR and Conventional Logs

The classification of water flooding severity is crucial for planning reservoir production and improving the recovery ratio. In this paper, we study a siliciclastic heavy oil reservoir in Bohai Bay, with resistivity reading close to, or even lower than the wet zone (3~5Ω.m). In this environment, computing original reservoir Sw using Traditional hydrocarbon saturation equation is challenging. As a result, the displacement efficiency of a water drive cannot be accurately determined. In order to properly evaluate displacement efficiency, we must estimate initial reservoir Sw (Swirr) and the modern day Sw. Sw can typically be estimated from NMR data with a proper T2 time cutoff. However, in heavy oil reservoirs, the relaxation times of oil and capillary bound water overlap, leading to an over-estimation of Sw. We propose to compensate for the heavy oil effect by adjusting the cutoff until NMR Sw matches the Sw from core Mercury Injection for Capillary Pressure (MICP). As oilfield development proceeds, water displaces some oil in the pore space. Since the injected water has higher salinity than reservoir water, formation resistivity (Rw) becomes lower. Based on the material balance theory, the variable multiple water injection material balance equation is established, and the equation set is established by combining the material balance equation with the Simandoux equation and the calculation formula of mixed water resistivity (Rwz). According to the rock electricity experiment under different salinity, the dynamic rock electricity parameters are used in the Simandoux equation, and the mixed water resistivity and modern day Sw after water flooding are solved iteratively under the original SW constraint. The displacement efficiency is calculated as the difference between Sw and modern day Sw. The proposed method was applied to 10 wells and improved the Sw accuracy by 5%-15%. The continuous solution Rw from our method matches Rw measured in the lab. The calculated displacement efficiency is compared with actual production history and the accuracy improved from 68% to 80%.

Soil-water resistivity curve of a tropical soil

The evaluation of soil-water characteristic curve is one of the most important procedures in the matter of understanding the soil behaviour during wetting and drying processes. Even though it might be carried out by established methods, this practice is considered a time-consuming technique, and because of this it is still under-used in comparison with its potential applications. In this way, this paper aims to analyse the correlation of soil suction and soil resistivity to produce a time-reduced soil-water characteristic curve (SWCC), based on resistivity measured values. To perform this research, it was used a set of soil samples collected from Nova Friburgo, Rio de Janeiro – Brazil. The material was geotechnically characterized by standard methods. To determine the (SWCC), it was used the filter paper method and the volumetric water content/suctions were obtained by wetting and drying stages for two paths that emerged from the field moisture content. The results revealed a remarkable relationship between suction and the resistivity measured data, emphasizing the feasibility of determining the Soil-Water Characteristic Curve by resistivity measurements, here named Soil-Water Resistivity Curve (SWResC).

Electrical Resistivity Imaging near Abandoned Steel Oil Wells: Five Case Studies, USA

Abandoned wells may act as conduits for the contamination of groundwater by oil field brines and other pollutants. The steel casings of abandoned wells eventually develop leaks, which if not properly plugged, can allow pollutants to reach freshwater aquifers that supply drinking water. Resistivity surveys were conducted in the vicinity of five abandoned oil wells in order to characterize the near-surface geology and to determine the effects of the steel casings and potential leakage. The arrays consisted of dipole-dipole (DD) and inverse Schlumberger (SLB) arrays. The effects from steel cased wells can manifest as low resistivity anomalies in the vicinity of the casings, depending on proximity of the line to the well, well location along the line, and the specific array used. These features appear as vertical, circular, elliptical, and bell-like anomalies. However, in some instances with the SLB array, the data appear not to be affected by the presence of steel casings. This observation is significant because resistivity surveys utilizing the SLB array can provide reliable information on near-surface geology next to abandoned wells, and horizontal and vertical extension of brine impacted areas due to leaking abandoned oil wells. The DD array, on the other hand, is better at locating potentially hidden abandoned wells but interpreting subsurface structure or contamination with the array is more difficult.