Exploration method and system for detection of hydrocarbons from the water column
US-10145974-B2 · Dec 4, 2018 · US
US12078726B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12078726-B2 |
| Application number | US-202016948707-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 29, 2020 |
| Priority date | Oct 22, 2019 |
| Publication date | Sep 3, 2024 |
| Grant date | Sep 3, 2024 |
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Detection of hydrocarbon bubbles in water using Light Detection and Ranging (LIDAR) to survey shallow water environments for the detection of surface hydrocarbon bubbles therein using LIDAR for the purposes of hydrocarbon exploration and/or brownfield remediation. Embodiments include a method of deploying an airborne LIDAR system configured to detect surface hydrocarbon bubbles in a shallow water environment, the LIDAR system accounting for a bubble volume scattering coefficient; and surveying, using the LIDAR system, the shallow water environment to detect surface hydrocarbon bubbles therein.
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The invention claimed is: 1. A method comprising: deploying an airborne Light Detection and Ranging (LIDAR) system configured to detect surface hydrocarbon bubbles from natural hydrocarbon seeps from beneath a seafloor in a shallow water environment, the LIDAR system accounting for a bubble volume scattering coefficient; differentiating surface hydrocarbon bubbles from the natural hydrocarbon seeps from other bubbles by surveying, using the LIDAR system, the shallow water environment; and performing, based at least in part upon the surveying of the shallow water environment to detect the surface hydrocarbon bubbles from the natural hydrocarbon seeps from beneath the seafloor, well placement for hydrocarbon extraction from beneath the seafloor. 2. The method of claim 1 , wherein the bubble volume scattering coefficient is calculated according to the equation: β bubble =KF void , where B bubble is the bubble volume scattering coefficient, K a bubble constant of proportionality, and F void is a void fraction of bubbles beneath LIDAR footprint. 3. The method of claim 2 , wherein K is in the range of about 233 m −1 sr −1 to about 1500 m −1 sr −1 . 4. The method of claim 3 , wherein K is 233 m −1 sr −1 , 671 m −1 sr −1 , or 1445 m −1 sr −1 . 5. The method of claim 2 , wherein the F void is in the range of about 10 −8 to 10 −3 . 6. The method of claim 1 , wherein the shallow water environment has a depth less than about 15 meters. 7. The method of claim 1 , wherein the shallow water environment has a depth of less than about 10 meters. 8. The method of claim 1 , wherein the shallow water environment has a depth of less than about 5 meters. 9. The method of claim 1 , wherein the LIDAR system has a signal-to-noise ratio of greater than zero (0) decibels, or has a signal-to-backscatter ratio greater than zero (0) decibels. 10. The method of claim 1 , wherein the LIDAR system has a signal-to-noise ratio in decibels and a signal-to-background ration in decibels, wherein the signal-to-noise ratio and the signal-to-background ratio are unequal. 11. The method of claim 1 , wherein the surveying of the shallow water environment comprises discovering surface hydrocarbon bubble plumes in order to locate a hydrocarbon system. 12. The method of claim 1 , wherein detecting the surface hydrocarbon bubbles from the natural hydrocarbon seeps is performed using a LIDAR model that uses a signal-to-noise ratio for the hydrocarbon bubbles (SNR bubble ) and signal-to-background ratio for the hydrocarbon bubbles (SBR bubble ); wherein the SNR bubble exceeds zero (0) decibels; and wherein the SNR bubble and the SBR bubble are unequal. 13. The method of claim 2 , wherein glint return results from LIDAR signals from the surface hydrocarbon bubbles being contaminated by specular return; and wherein the bubble volume scattering coefficient is greater than the glint return.
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