IIT Madras courses win Wharton QS Reimagine Education Awards

IIT Madras Researchers Successfully Develop Method to Detect Petroleum Reserves Underground

Researchers from the Indian Institute of Technology (IIT) Madras have discovered a way to locate petroleum reserves that are hidden beneath rocks. Using their method, they were able to detect a zone saturated with hydrocarbons located 2.3 km underground in the Tipam formation of the Upper Assam basin, within a sandstone-based reservoir.

The researchers employed a statistical approach to identify and characterise subsurface rock structure and detect hydrocarbon reserves. They used this method to analyze data obtained from seismic surveys and well logs in the North Assam region, which is known for its petroleum reserves. According to a press release from the institute, the results of this analysis were accurate.

“Since the discovery of the Digboi oilfield in Upper Assam more than 100 years ago, the area has come to be characterized as a category-I basin, denoting that it has significant amounts of hydrocarbon reserves. Petroleum is found in the pore space of hydrocarbon-bearing underground rock formations. The identification of petroleum reservoirs in the oil-rich basins of Assam requires a survey of the rock structure of this region and the detection of hydrocarbon saturation zones in them,” the release informs.

Understanding underground rock structures can be a difficult task. To do so, scientists often use seismic survey methods and well-log data. “In a seismic survey, vibrations are sent through the ground, and when these waves encounter different rock layers, they are reflected in different ways. The reflected waves are recorded and used to create an image of the underground rock structure. Well logs contain information about the various layers of the earth that are encountered when drilling an oil well,” as per the press release.

Professor Rajesh R Nair, a faculty member of the petroleum engineering programme at the Department of Ocean Engineering at IIT Madras, led the team in this research. Their findings were published in the journal NATURE Scientific Reports, and the paper was co-authored by Professor Nair as well as researchers M Nagendra Babu and Dr Venkatesh Ambati, all from IIT Madras.

Elaborating on the need for such research, Profesor Nair said, “The challenge to imaging underground structures arises from the low resolution of the seismic images and the difficulty in correlating the data from well-log and seismic surveys. Our team at IIT Madras has developed a methodology for predicting the hydrocarbon zones from the complex well log and seismic data.”

“The characterisation of subsurface structures for the detection of oil-bearing rocks involves the use of data analytics methods that establish statistical relationships between seismic data and petrophysical data obtained from well logs. These relationships help in estimating the petrophysical properties of the subsurface,” he added.

Explaining the technical aspects of the study, the professor said, “Seismic inversion is a process that is commonly used to transform the seismic reflection data into a quantitative rock-property description of a reservoir. Our team used a type of seismic inversion, called Simultaneous Prestack Seismic Inversion (SPSI). This analysis provided the spatial distribution of petrophysical properties in the seismic image. Our team then combined this with other data analytics tools such as target correlation coefficient analysis (TCCA), Poisson Impedance (PI) inversion, and Bayesian classification to successfully obtain the underground rock and soil structure of the region.”

He added that India’s mega offshore bidding process of 26 blocks for producing oil, and gas is presently ongoing and such new technologies for finding discoveries will boost the oil and gas business enormously. “For example, on a thumb rule, a 0.07 incremental change in successful new technology will boost the oil and gas business by about 10 per cent,” Professor Nair said, as per the press release.

Courtesy : Edex

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