METHOD AND APPARATUS FOR OIL SPILL DETECTION

• US 20090039255A1
• Filed: 08/07/2008
• Published: 02/12/2009
• Est. Priority Date: 08/10/2007
• Status: Active Grant

• Current Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Original Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Inventors: Shih, Wei-Chuan, Mullins, Oliver C., Clayton, Matthew, Andrews, Albert Ballard
• Granted Patent: US 8,124,931 B2
• Time in Patent Office: Days
• US Class Current: 250/301
• CPC Class Codes: G01N 2021/1793 Remote sensing
• CPC Class Codes: G01N 21/35 using infrared light G01N21/39 takes precedence
• CPC Class Codes: G01N 21/3563 for analysing solids; Preparation of samples therefor
• CPC Class Codes: G01N 21/3577 for analysing liquids, e.g. polluted water
• CPC Class Codes: G01N 21/3581 using far infrared light; using Terahertz radiation
• CPC Class Codes: G01N 2201/0616 Ambient light is used
• CPC Class Codes: G01N 33/1833 Oil in water
• CPC Class Codes: G01V 8/02 Prospecting
• CPC Class Codes: Y02A 20/20 Controlling water pollution; Waste water treatment

Abstract

The invention relates to a method for detecting the presence of hydrocarbons near an unmanned offshore oil platform. The method steps include monitoring reflected atmospheric and thermal radiation, detecting the presence of hydrocarbons, and generating an alert based on the presence of hydrocarbons.

Claims

1. A method for detecting presence of hydrocarbons on a surface, comprising:

monitoring reflected atmospheric radiation and surface emission from the surface;

detecting the presence of hydrocarbons based on the reflected atmospheric radiation and the surface emission; and

generating an alert based on the presence of hydrocarbons.

2. The method of claim 1 wherein said monitoring is accomplished using at least one selected from a group consisting of a visible camera, a near-infrared camera, and a long-wavelength-infrared (LWIR) camera.

3. The method of claim 1, wherein the surface is a water surface.

4. The method of claim 1, further comprising:

calculating a statistical parameter indicating a possible extent of the presence of the hydrocarbon on the surface,

wherein the alert is generated based on the statistical parameter being outside of a pre-determined range.

5. The method of claim 1, further comprising:

providing a model for modeling radiance contrast of the reflected atmospheric radiation and the surface emission in at least one selected from a group consisting of daytime condition, nighttime condition, and pre-determined weather condition, wherein the radiance contrast is induced by the presence of hydrocarbons on the surface and comprises at least one selected from a group consisting of reflection contrast, temperature contrast, and emissivity contrast; and

defining a decision tree based on the model,

wherein the presence of hydrocarbons is detected according to the decision tree.

6. The method of claim 5, further comprising:

obtaining a first image stream from monitoring the reflected atmospheric radiation and the surface emission;

generating a statistical diagram from the first image stream; and

identifying one or more clusters in the statistical diagram,

wherein the presence of hydrocarbons is detected based on the one or more clusters according to the decision tree.

7. The method of claim 6, wherein the statistical diagram comprises a histogram of pixel intensity, wherein the histogram comprises a mean intensity and a standard deviation.

8. The method of claim 6, further comprising:

obtaining a second image stream from monitoring the reflected atmospheric radiation and surface emission; and

further generating the statistical diagram from the second image stream,

wherein the statistical diagram is a multi-dimensional statistical diagram, and

wherein at least one selected from a group consisting of the first image stream and the second image stream are obtained from at least one selected from a group consisting of a first visible band, a second visible band, a first near-infrared (NIR) band, a second NIR band, a first long-wavelength-infrared (LWIR) band, a second LWIR band, a fluorescent band, and a Raman effect.

9. The method of claim 8, wherein the first image stream and the second image stream are obtained using a bandpass filter.

10. The method of claim 8, further comprising:

calibrating the model without the presence of hydrocarbons to generate historical data, wherein the decision tree comprises a comparison based on the historical data; and

comparing the one or more clusters to historical data according to the decision tree to validate the detection of the presence of hydrocarbons.

11. The method of claim 10,

wherein historical data comprises statistics of a plurality of images obtained from monitoring the reflected atmospheric radiation and the surface emission without the presence of hydrocarbons,

wherein the statistics are generated based on parametric classification,

wherein historical data further comprises one or more objects identified from the statistics based on rule based classification, and

wherein the one or more clusters are compared to the one or more objects in the historical data to validate the detection of the presence of hydrocarbons.

12. The method of claim 5, further comprising:

irradiating the surface using at least one selected from a group consisting of ultraviolet source, visible light source, and infrared source to improve the radiance contrast.

13. The method of claim 5, further comprising:

irradiating the surface using at least one selected from a group consisting of ultraviolet source and visible light source to generate fluorescence response.

14. The method of claim 5, further comprising:

irradiating the surface using at least one selected from a group consisting of ultraviolet source and visible light source to generate Raman signal.

15. A method for detecting presence of hydrocarbons on a surface, comprising:

monitoring surface emission from the surface in an infrared band;

providing a model for modeling emissivity contrast of the surface emission, wherein the emissivity contrast is induced by the presence of hydrocarbons on the surface;

detecting the presence of hydrocarbons from the surface emission based on the model; and

generating an alert based on the presence of hydrocarbons.

16. The method of claim 15, wherein the emissivity contrast comprises at least one selected from a group consisting of temperature contrast, spectral contrast, and thickness contrast.

17. The method of claim 16,

wherein the model comprises a wavelength dependent emissivity model for the spectral contrast,

and further comprising adjusting a wavelength of the infrared band to detect the spectral contrast.

18. The method of claim 16,

wherein the model comprises a thickness dependent emissivity model for the thickness contrast induced by a thickness variation of hydrocarbon,

and further comprising configuring a wavelength range of the infrared band to detect the thickness contrast, wherein the presence of hydrocarbons is detected based on the thickness contrast.

19. The method of claim 15, wherein the surface is a water surface

20. The method of claim 19,

wherein the model comprises an undetectable range for the temperature contrast based on radiometric temperatures of hydrocarbon, water, and sky, and

wherein the undetectable range is dependent on a wavelength of the infrared band,

and further comprising adjusting the wavelength of the infrared band to avoid the undetectable range, wherein the presence of hydrocarbons is detected based on the temperature contrast.

21. The method of claim 19,

wherein the model comprises a positive range and a negative range for the temperature contrast based on radiometric temperatures of hydrocarbon, water, and sky, and

wherein the positive range and the negative range is dependent on an wavelength of the infrared band,

and further comprising adjusting the wavelength of the infrared band to detect a change in the temperature contrast, wherein the presence of hydrocarbons is detected based on the change in the temperature contrast.

22. A system for detecting presence of hydrocarbons on a surface, comprising:

a plurality of sensors for monitoring reflected atmospheric radiation and surface emission from the surface; and

a memory and a processor, embodying instructions stored in the memory and executable by the processor, the instructions comprising functionality to;

detect the presence of hydrocarbons based on the reflected atmospheric radiation and the surface emission according to a decision tree, wherein the decision tree is based on a model for modeling radiance contrast of the reflected atmospheric radiation and the surface emission in at least one selected from a group consisting of daytime condition, nighttime condition, and pre-determined weather condition, wherein the radiance contrast is induced by the presence of hydrocarbons on the surface and comprises at least one selected from a group consisting of reflection contrast, temperature contrast, and emissivity contrast; and

generate an alert based on the presence of hydrocarbons.

23. The system of claim 22, wherein said monitoring is accomplished using at least one selected from a group consisting of a visible camera, a near-infrared camera, and a long-wavelength-infrared (LWIR) camera.

24. The system of claim 22, wherein the surface is a water surface.

25. The system of claim 22, the instructions further comprising functionality to:

calculate a statistical parameter indicating a possible extent of the presence of the hydrocarbon on the surface,

wherein the alert is generated based on the statistical parameter being outside of a pre-determined range.

26. The system of claim 22, the instructions further comprising functionality to:

obtain a first image stream from monitoring the reflected atmospheric radiation and the surface emission;

generate a statistical diagram from the first image stream; and

identify one or more clusters in the statistical diagram,

wherein the presence of hydrocarbons is detected based on the one or more clusters according to the decision tree.

27. The system of claim 26, wherein the statistical diagram comprises a histogram of pixel intensity, wherein the histogram comprises a mean intensity and a standard deviation.

28. The system of claim 26, the instructions further comprising functionality to:

obtain a second image stream from monitoring the reflected atmospheric radiation and surface emission; and

further generate the statistical diagram from the second image stream,

wherein the statistical diagram is a multi-dimensional statistical diagram, and

wherein at least one selected from a group consisting of the first image stream and the second image stream are obtained from at least one selected from a group consisting of a first visible band, a second visible band, a first near-infrared (NIR) band, a second NIR band, a first long-wavelength-infrared (LWIR) band, a second LWIR band, a fluorescent band, and a Raman effect.

29. The system of claim 26, the instructions further comprising functionality to:

calibrate the model without the presence of hydrocarbons to generate historical data, wherein the decision tree comprises a comparison based on the historical data; and

compare the one or more clusters to historical data according to the decision tree to validate the detection of the presence of hydrocarbons.

30. The system of claim 29,

wherein historical data comprises statistics of a plurality of images obtained from monitoring the reflected atmospheric radiation and the surface emission without the presence of hydrocarbons,

wherein the statistics are generated based on parametric classification,

wherein historical data further comprises one or more objects identified from the statistics based on rule based classification, and

wherein the one or more clusters are compared to the one or more objects in the historical data to validate the detection of the presence of hydrocarbons.

31. A system for detecting presence of hydrocarbons on a surface, comprising:

a plurality of sensors for monitoring surface emission from the surface in an infrared band; and

a memory and a processor, embodying instructions stored in the memory and executable by the processor, the instructions comprising functionality to;

detect the presence of hydrocarbons based on the surface emission using a model for modeling emissivity contrast of the surface emission, wherein the emissivity contrast is induced by the presence of hydrocarbons on the surface and comprises at least one selected from a group consisting of temperature contrast, spectral contrast and thickness contrast; and

generate an alert based on the presence of hydrocarbons.

32. The system of claim 31, wherein the surface is a water surface.

33. The system of claim 32,

wherein the model comprises an undetectable range for the temperature contrast based on radiometric temperatures of hydrocarbon, water, and sky, and

wherein the undetectable range is dependent on a wavelength of the infrared band, the instructions further comprising functionality to:

adjust the wavelength of the infrared band to avoid the undetectable range, wherein the presence of hydrocarbons is detected based on the temperature contrast.

34. The system of claim 32,

wherein the model comprises a positive range and a negative range for the temperature contrast based on radiometric temperatures of hydrocarbon, water, and sky, and

wherein the positive range and the negative range is dependent on an wavelength of the infrared band,

the instructions further comprising functionality to:

adjust the wavelength of the infrared band to detect a change in the temperature contrast, wherein the presence of hydrocarbons is detected based on the change in the temperature contrast.

35. The system of claim 31,

wherein the model comprises a wavelength dependent emissivity model for the spectral contrast,

the instructions further comprising functionality to:

adjust a wavelength of the infrared band to detect the spectral contrast.

36. The system of claim 31,

wherein the model comprises a thickness dependent emissivity model for the thickness contrast induced by a thickness variation of hydrocarbon,

the instructions further comprising functionality to:

configure a wavelength range of the infrared band to detect the thickness contrast, wherein the presence of hydrocarbons is detected based on the thickness contrast.