Graphical user interface packages in Matlab are getting very popular with the geo-scientific researchers. Matlab GUI (graphical user interface) is a graphical display containing controls which helps in computing and graphically representing the results. In this paper a simple graphical user interface (GUI) viewer is developed in MATLAB that computes the thermal lithospheric structure along with its error bounds. The m-file in the package is integrated through a GUI and the controlling thermal parameters such as crustal thickness, radiogenic heat production, characteristic depth, surface temperature, surface heat flow and thermal conductivity are all given on the screen. The thermal conductivity is considered to be Gaussian random variable with a known coefficient of variability and a correlation length scale. The output is in the form of temperature, depth and its standard deviation. The lithospheric thickness along with the error bounds for the region is then inferred from these graphs. The developed GUI is applied to quantify the lithospheric thickness along with its error structure for any given region where conductive heat transfer is dominant.

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The permeability of sandstone varies significantly from site to site at the field scale. Well-established methods for permeability estimation depend on lab-measured parameters, which are available only at sparse locations. To overcome such dependency, we developed a method to estimate sandstone's site-specific and field scale permeability using well-log and interconnected porosity data, respectively. We considered sandstone as a mono-dispersed porous medium with monofractal pores and simulated them using the fractal theory based acceptance rejection Monte-Carlo algorithm. Stabilization of the algorithm through an error convergence scheme generated repeatable and reliable permeability values. We tested this developed method on cores obtained from various formations representing clean/shaly sandstones and a few sandstone samples contaminated by carbonates. Compared to lab-measured permeability, the estimates are within one-order magnitude error bounds for clean/shaly sandstones and higher for samples that are either contaminated by carbonates or having higher pore volume normalized surface area. We applied the method to infer field scale permeability trend to explain the unexpected movement of hydrocarbons in Kalol reservoir lying in Balol oil field of Cambay basin India, where in-situ combustion Enhanced Oil Recovery process is implemented. The field scale permeability trend could explain the northward movement of the hydrocarbons to the adjacent oil field, Lanwa. It was observed in the production data of the Lanwa field that the in-situ combustion in Balol has benefited oil production in its wells.

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