Artificial Intelligence and Robotics Support Marine Mining
- Chris Carpenter (JPT Technology Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- August 2018
- Document Type
- Journal Paper
- 68 - 70
- 2018. Offshore Technology Conference
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- 96 since 2007
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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 29069, “How AI and Robotics Can Support Marine Mining,” by Peter Kampman, Leif Christensen, Martin Fritsche, Christopher Gaudig, Hendrik Hanff, and Marc Hildrebrandt, German Research Center for Artificial Intelligence (DFKI), and Frank Kirchner, DFKI and University of Bremen, prepared for the 2018 Offshore Technology Conference, Houston, 30 April–4 May. The paper has not been peer reviewed. Copyright 2018 Offshore Technology Conference. Reproduced by permission.
Marine mining initiatives open a new field of subsea operations. Offshore oil and gas sites are still located primarily in areas where divers can support maintenance and repair requirements, but future marine mining will take place in greater depths and with a complexity of machines that requires support from robotic systems equipped with a substantial amount of artificial intelligence (AI). Technologies are being developed that have the potential to support marine mining in all stages from prospection to decommissioning. These developments will likely have substantial influence in the oil and gas industry, itself searching for ways to maximize exploitation of assets.
Under Current Development Increasing Autonomous Underwater Vehicle (AUV) Intelligence. Commercial off-the-shelf AUVs rely mostly on acoustic and inertial sensors for their navigation. Speed measurements from a Doppler velocity log are combined with orientation values from gyroscopes and accelerometers to estimate current position. These updates are sometimes augmented by absolute-position fixes from an ultrashort baseline system. However, during such a mission, the inspection assets might not be located exactly at their expected positions. This might be because of incorrect positioning during installation, objects being dragged off location by fishermen, or sediments hiding a pipeline gradually from the view of standard sensors. Therefore, equipping modern AUVs with sensors and software that can search for, detect, track, and re acquire inspection targets is essential.
In addition, classical sensor suites consisting of cameras and sonars can be augmented with higher-resolution 3D sensing such as laser-line projectors (structured light). This enables an AUV’s onboard software to create a millimeter-precision 3D model of the asset, which can be compared with computer-aided-design models or previous-inspection-run data. By using a fully automated 3D-model cross-check, the AUV could detect asset deformations, defects, or marine growth, even while still submerged during the inspection run.
Seafloor AUV Support Infrastructure. Current AUVs have limited endurance, mostly because of limited battery capacity. Depending on the sensor suite, on-board data-storage space also can be a limiting factor. This causes AUV missions to run no longer than a few days at most, depending on AUV size and shape, propulsion, sensor efficiency, and environmental conditions in the deployment area.
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