8 skills found
toddheitmann / PetroPyA petrophysics python package for geoscience python computing of conventional and unconventional formation evaluation. Reads las files and creates a pandas dataframe of the log data. Includes a basic petrophysical workflow and a simple log viewer based on XML templates.
yohanesnuwara / FormationPyPython utility for formation evaluation and petrophysical analysis support
salmansust / CO2 SequestrationCarbon Capture and Sequestration (CCS) has been proposed as a promising and necessary technology for mitigating CO2 and the effects of anthropogenic climate change. Deep geological formations, like saline aquifers, are pointed out as promising areas for large-scale storage of CO2. If CCS is implemented on large scale to make noticeable reductions in atmospheric CO2, then it will require a solid scientific foundation defining the coupled hydrologic–geochemical–geomechanical processes that govern the long-term fate of CO2 in the subsurface, migration behavior of CO2, trapping mechanisms, proper utilization of methods to characterize and select sequestration sites, workflow and evaluation process, simulation methods, subsurface engineering to optimize performance, well placement, injection rate and cost, approaches to ensure safe operation, monitoring technology, remediation methods, regulatory overview, and an institutional approach for managing long-term liability. To address the above issues, we demonstrated, reviewed and developed the overall workflow of the process of CO2 sequestration in this study.
raushan202000 / Image Dehazing By Artificial Multiple Exposure Image FusionBad weather conditions can reduce visibility on images acquired outdoors, decreasing their visual qual- ity. The image processing task concerned with the mitigation of this effect is known as image dehaz- ing. In this paper we present a new image dehazing technique that can remove the visual degradation due to haze without relying on the inversion of a physical model of haze formation, but respecting its main underlying assumptions. Hence, the proposed technique avoids the need of estimating depth in the scene, as well as costly depth map refinement processes. To achieve this goal, the original hazy image is first artificially under-exposed by means of a sequence of gamma-correction operations. The resulting set of multiply-exposed images is merged into a haze-free result through a multi-scale Laplacian blend- ing scheme. A detailed experimental evaluation is presented in terms of both qualitative and quantitative analysis. The obtained results indicate that the fusion of artificially under-exposed images can effectively remove the effect of haze, even in challenging situations where other current image dehazing techniques fail to produce good-quality results.
samglish / GFGLISH_FORMATION(GF), Lightweight platform in VBA Excel, to manage courses, registrations, re-registrations and learner evaluations.
ndamtruong2k / Statistical Simulation Results Of The Multi UAV Coverage StrategyThe obtained to evaluate the performance of the proposed multi-UAV coverage strategy for the V-shaped formation.
mariafgg-free / Tutorials Formation EvaluationHomework 3 solution in a jupyter notebook accesible way for students
Hjorthmedh / RetinalMapA framework for retinotopic map formation modelling and evaluation.
