Location of spontaneous combustion in a coal waste pile by self-potential method

2004 ◽  
pp. 249-254
Author(s):  
Bingrui Li ◽  
K. Uchino ◽  
M. Inoue ◽  
T. Tanaka
Keyword(s):  
Spontaneous Combustion ◽  
Potential Method ◽  
Coal Waste ◽  
Coal Waste Pile ◽  
Self Potential

Assessment of Self-Heating Susceptibility of Indian Coal Seams – A Neural Network Approach

2014 ◽  
Vol 59 (4) ◽  
pp. 1061-1076 ◽  
Author(s):  
D.C. Panigrahi ◽  
S.K. Ray
Keyword(s):  
Neural Network ◽  
Spontaneous Combustion ◽  
Potential Method ◽  
Oxidation Potential ◽  
Wet Oxidation ◽  
Experimental Conditions ◽  
Neural Network Approach ◽  
Indian Coal ◽  
Petrographic Analyses ◽  
Artificial Neural Network Ann

Abstract The paper addresses an electro-chemical method called wet oxidation potential technique for determining the susceptibility of coal to spontaneous combustion. Altogether 78 coal samples collected from thirteen different mining companies spreading over most of the Indian Coalfields have been used for this experimental investigation and 936 experiments have been carried out by varying different experimental conditions to standardize this method for wider application. Thus for a particular sample 12 experiments of wet oxidation potential method were carried out. The results of wet oxidation potential (WOP) method have been correlated with the intrinsic properties of coal by carrying out proximate, ultimate and petrographic analyses of the coal samples. Correlation studies have been carried out with Design Expert 7.0.0 software. Further, artificial neural network (ANN) analysis was performed to ensure best combination of experimental conditions to be used for obtaining optimum results in this method. All the above mentioned analysis clearly spelt out that the experimental conditions should be 0.2 N KMnO4 solution with 1 N KOH at 45°C to achieve optimum results for finding out the susceptibility of coal to spontaneous combustion. The results have been validated with Crossing Point Temperature (CPT) data which is widely used in Indian mining scenario.

scholarly journals The electrical self-potential method is a non-intrusive snow-hydrological sensor

2015 ◽  
Vol 9 (4) ◽  
pp. 4437-4457 ◽  
Author(s):  
S. S. Thompson ◽  
B. Kulessa ◽  
R. L. H. Essery ◽  
M. P. Lüthi
Keyword(s):  
Spatial Scales ◽  
Chemical Properties ◽  
Potential Method ◽  
Measurement Procedure ◽  
Theoretical Modelling ◽  
Avalanche Forecasting ◽  
Physical And Chemical ◽  
Self Potential ◽  
Water Contents

Abstract. Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.

Mapping Fracture Flow Anisotropy Using the Self Potential Method: Field and Laboratory Experiments

2021 ◽  
Author(s):  
Y. Kumar ◽  
J. Comte ◽  
J. Vinogradov ◽  
D. Healy ◽  
J. Mezquita Gonzalez ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Potential Method ◽  
The Self ◽  
Fracture Flow ◽  
Self Potential ◽  
Flow Anisotropy

scholarly journals Self-Potential Studies in Volcanic Environments: A Cheap and Efficient Method for Multiscale Fluid-Flow Investigations

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
N. Grobbe ◽  
S. Barde-Cabusson
Keyword(s):  
Electrical Resistivity ◽  
Fluid Flow ◽  
Case Studies ◽  
Potential Method ◽  
Hydrothermal Systems ◽  
Geochemical Data ◽  
Data Types ◽  
Spatial And Temporal Scales ◽  
Cooling Behavior ◽  
Self Potential

We demonstrate the value of using the self-potential method to study volcanic environments, and particularly fluid flow in those environments. We showcase the fact that self-potential measurements are a highly efficient way to map large areas of volcanic systems under challenging terrain conditions, where other geophysical techniques may be challenging or expensive to deploy. Using case studies of a variety of volcano types, including tuff cones, shield volcanoes, stratovolcanoes, and monogenetic fields, we emphasize the fact that self-potential signals enable us to study fluid flow in volcanic settings on multiple spatial and temporal scales. We categorize the examples into the following three multiscale fluid-flow processes: (1) deep hydrothermal systems, (2) shallow hydrothermal systems, and (3) groundwater. These examples highlight the different hydrological, hydrothermal, and structural inferences that can be made from self-potential signals, such as insight into shallow and deep hydrothermal systems, cooling behavior of lava flows, different hydrogeological domains, upwelling, infiltration, and lateral groundwater and hydrothermal fluid flow paths and velocities, elevation of the groundwater level, crater limits, regional faults, rift zones, incipient collapse limits, structural domains, and buried calderas. The case studies presented in this paper clearly demonstrate that the measured SP signals are a result of the coplay between microscale processes (e.g., electrokinetic, thermoelectric) and macroscale structural and environmental features. We discuss potential challenges and their causes when trying to uniquely interpret self-potential signals. Through integration with different geophysical and geochemical data types such as subsurface electrical resistivity distributions obtained from, e.g., electrical resistivity tomography or magnetotellurics, soil CO2 flux, and soil temperature, it is demonstrated that the hydrogeological interpretations obtained from SP measurements can be better constrained and/or validated.

Sign in / Sign up

Export Citation Format

Share Document