Analytics and machine learning company Earth Science Analytics (ESA) has become the first Core Sponsor for the Rock Imaging Special Interest Group (RISIG). This annual sponsorship package assures ESA of year-long recognition as a prime supporter of RISIG’s efforts to spread knowledge of rock imaging techniques and tools, and to exhibit applications in oil and gas, mining, CCUS and general geoscience areas.
Last year, ESA was an active supporter, participating in two 2021 webinars, "The Challenges and Rewards of Image-Based Cuttings Analysis" in April 2021 and "Machine Learning for Rock Typing" in September 2021. They were also the Registration Sponsor for the International Rock Imaging Summit (iRIS) held in November 2021. This year, they are already lined up to present at the webinar on "Accessing the Value in Cuttings" and, as Core Sponsor, will sponsor other RISIG activities including iRIS-2022.
“We are delighted at the support we have received from Earth Science Analytics”, said Ross Davidson, Managing Director of EXPROBIZ which runs RISIG. “We are seeing increased interest in all kinds of rock imaging, be it physical property logging, XRF for geochemistry analysis, hyperspectral IR spectrometry for mapping mineralogy, thin section imaging, X-ray computed tomography for 3D analysis and scanning electron microscopy for pore-scale understanding. The huge volume of image data needs managing and interpreting. Powerful software tools are being developed to interpret the wealth of fresh data and extract valuable meaning, often using advanced machine learning and artificial intelligence techniques to recognise patterns and characterise the rock material: cores, plugs, thin sections, chips and cuttings. ESA is at the leading edge of this new technology.”
Tatiana Moguchaya, CEO at Earth Science Analytics, said: ‘We are pleased to support RISIG in their work to promote a deeper technical and business understanding of the value of rock image data.
“Over the decades of subsurface exploration and development, vast numbers of samples from drill cuttings and cores have been collected. Even in cases where these samples have been washed and photographed, further analysis and inclusion of data in interpretations has been hampered by the physical volume of data requiring human review. However, with Machine Learning and Cloud-computing, the value of these often-overlooked rock core and cuttings images can be unlocked as Computer Vision and automation make classification of hundreds of thousands of samples a realistic step in an integrated data workflow.
“Inclusion of core and cuttings interpretation in broader subsurface workflows is essential for good business decision making, not only in oil and gas exploration, but also for sub-surface CO2 storage and mining industries.”
About Rock Imaging Special Interest Group: RISIG provides opportunities for sharing, learning and collaborating with peers in industry and academia for the purpose of advancing knowledge and best practices in the field of rock imaging, whatever the purpose. For more information, visit: rockimaging.org.