Image Credits: Twitter/IIT Madras
Tamil Nadu
IIT Madras Researchers Successfully Devise A Method To Detect Petroleum Underground
|The method analyses data from seismic surveys and well-logs from the North Assam region. At such depth zones, it could obtain precise information on the distribution of rock types and the hydrocarbon saturation zones.
A team of researchers from IIT Madras have devised a statistical method to assess underlying rock structure and find petroleum and hydrocarbon reserves. The approach successfully revealed useful information regarding the rock type distribution and hydrocarbon saturation zones found in the Tipam formation in the upper Assam basin.
Researchers at @iitmadras have developed an effective data analytics approach to detect petroleum underground. Prof. Rajesh R. Nair, IIT Madras, led the research. The findings were published in the prestigious journal @NaturePortfolio Scientific Reports (https://t.co/OMcXTTozBc). pic.twitter.com/i4pt9nY4mv
— IIT Madras (@iitmadras) December 30, 2022
Professor Rajesh R. Nair, Faculty, Petroleum Engineering Program, Department of Ocean Engineering, IIT Madras, served as the study's lead researcher. IIT Madras academics M. Nagendra Babu and Dr. Venkatesh Ambati co-authored the study.
The researchers utilised this method to analyse data from seismic surveys and well logs from the North Assam region, which is famous for its oil reserves. At such depth zones, it could obtain precise information on the distribution of rock types and the hydrocarbon saturation zones.
Need For The Research
Since the Digboi oilfield in Upper Assam was discovered more than a century ago, the Assam-Arakan region has come to be known as a 'category-I' basin to indicate the presence of sizable hydrocarbon reserves. Petroleum is discovered in the pore space of subsurface rock formations that contain hydrocarbons.
Highlighting the need for the research, Professor Nair said that the challenge of imaging underground structures arises from the low resolution of the seismic images and the challenge of relating the data from well-log and seismic surveys. He claims that the method developed by his team can effectively predict the hydrocarbon zones from the intricate well log and seismic data, as per NDTV.
These correlations between seismic data and petrophysical data received from well-logs aid in calculating the subsurface's petrophysical parameters, he added.
Team Effort To Get Accurate Analysis
Professor Rajesh Nair described the technical details of the work by stating that seismic inversion is a method that is frequently used to convert seismic reflection data into a quantitative rock-property description of a reservoir. Simultaneous Prestack Seismic Inversion (SPSI) is a seismic inversion that the team employed to provide the spatial distribution of petrophysical parameters in the seismic image.
He said that to successfully get the region's underground rock and soil structure, the team then integrated this with other data analytics tools like target correlation coefficient analysis (TCCA), Poisson impedance inversion, and Bayesian classification.
The researchers also included a unique property known as Poisson impedance (PI) in their analysis during the course of this work. The fluid capacity of the sandstone reservoir was determined using PI. Additionally, their research demonstrated that PI performed better in estimating the hydrocarbon zone than traditional features.