The team used their method to locate a hydrocarbon-saturated zone in a sandstone-based reservoir on the Tipam Formation in the Upper Assam Basin.
The method provided important information about rock type and hydrocarbon saturation zones located 2.3 km underground
Indian Institute technology Researchers at Madras (IIT Madras) have developed a statistical approach that can characterize subsurface rock composition and locate petroleum and hydrocarbon reserves. The proposed method was successful in providing important information on rock type distribution and hydrocarbon saturation zones in the ‘Tipam Formation’ located in the Upper Assam Basin.
The researchers used this approach to analyze data obtained from seismic surveys and logs of wells known to have petroleum reserves from the north Assam region. The institute says they were able to obtain precise information on rock type distribution and hydrocarbon saturation zones in areas with a depth of 2.3 km.
This research is headed by Prof. Rajesh R. Nair, Faculty, Petroleum Engineering Program, Department of Ocean Engineering, IIT Madras. The findings were published in the prestigious journal Nature Scientific Reports. The paper was co-authored by Prof. M. Nagendra Babu and Dr. Venkatesh Ambati of IIT Madras along with researchers. Rajesh R. Nair did.
Since the discovery of the Digboi oil field in Upper Assam more than 100 years ago, the Assam-Arakan basins have been characterized as ‘Class-I’ basins, indicating that they possess significant amount of hydrocarbon reserves. Petroleum is a hydrocarbon found in the pores of underground rock formations. Identification of petroleum reservoirs in the oil rich basins of Assam requires survey of the rock structure of the region and locating hydrocarbon saturation zones in them.
Pro. Rajesh R. Nair said, “The challenge for imaging underground structures stems from the low resolution of seismic images and the difficulty in correlating data from well-logs and seismic surveys. Our team at IIT Madras has developed a methodology to predict hydrocarbon zones from complex well log and seismic data.
He further added, “The characterization of subsurface structures to locate oil-bearing rocks involves the use of data analytics methods that establish statistical relationships between seismic data and petrophysical data obtained from well logs. They help in estimating the petrophysical properties.
The team used their method to locate a hydrocarbon-saturated zone in a sandstone-based reservoir on the Tipam Formation in the Upper Assam Basin. The researchers combined various statistical approaches to derive subsurface rock composition using data from seismic surveys and well logs.
Prof Rajesh Nair said, “Seismic inversion is a process commonly used to convert 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 Inverse and Bayesian Classification to successfully derive the underground rock and soil composition of the area.
In the course of this work, the researchers also introduced a remarkable feature called ‘Poisson Impedance’ (PI) into their analysis. PI was used to identify the fluid content in the sandstone reservoir. Their findings also proved that ‘Poisson’s impedance’ (PI) was more effective in estimating the hydrocarbon field than conventional properties.
Prof. Rajesh Nair said that India’s mega offshore bidding process of 26 blocks for oil and gas production is currently underway and such new technologies to find new discoveries will give a great boost to the oil and gas business. For example, as a rule of thumb, a 0.07 incremental change in a successful new technology would increase the oil and gas business by about 10 percent.
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