ROCKPHYSICS AS A TOOL FOR INTEGRATING MULTISCALE DATA IN GEOSCIENCES

Abstract

Geophysical Tools offers a comprehensive portfolio of advanced Geoscience solutions to deliver new insights that reduce risk and uncertainty across the spectrum of exploration, development, and production projects. The developers develop advanced technology tools and continue to build its portfolio to address the most difficult subsurface challenges in all reservoir systems be they carbonate, clastic or other lithology. With the advancement and understanding of the subsurface variation in rock and fluid properties and the availability of high performance computing, the use of software’s to solve complex earth problem has become a routine. PRIME is an Integrated platform for solving Petrophysical and Rock Physical challenges for today’s exploration and development activities. More than the conventional solutions, PRIME aims to integrate machine learning in the most natural way for predicting the hydrocarbon that is; yet to be found. With the majority of the easy mineral resource targets having already been found, the industry is being forced to re-evaluate methodologies for conducting exploration programs. Future targets are likely to be deeper, with little or no surface expression, and may be concealed from conventional exploration techniques by overburden, permafrost or other geologically complex environments. In order to locate such targets, a holistic multidisciplinary approach is required to identify trends across multiple characteristic features, including geology, geophysics and geochemistry. PRIME has been developed in collaboration with students and professor from Earth science and Computer science department since February 2017. It is then used to analyze the seismic and well data. This determines the value and accordingly apply quantitative methods to predict fluid, rock, and pressure properties. With PRIME, seismic related data can be integrated with pressure and log data. PRIME can be used to identify many other types of geological variations, and porosity, based on the well data and seismic data.