Method and apparatus for oil spill detection

• US 8,124,931 B2
• Filed: 08/07/2008
• Issued: 02/28/2012
• Est. Priority Date: 08/10/2007
• Status: Expired due to Fees

• Current Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Original Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Inventors: Andrews, Albert Ballard, Shih, Wei-Chuan, Clayton, Matthew, Mullins, Oliver C.
• Primary Examiner(s): Porta, David
• Assistant Examiner(s): GREEN, YARA B
• Application Number:
  US12/188,141
• Publication Number:
  US 20090039255A1
• Time in Patent Office: 1,300 Days
• Field of Search: 250/301, 250/484.2, 250/339.14, 250/428, 250/432.R, 250/393, 250/394, 250/253, 250/461.1
• 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 water in oil G01N33/2847
• 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 corresponding to a first intensity and surface emission from the surface corresponding to a second intensity to generate an image comprising a plurality of pixels, wherein each of the plurality of pixels is associated with the first intensity obtained using a first sensor corresponding to a first spectral band and the second intensity obtained using a second sensor corresponding to a second spectral band, wherein the first sensor and the second sensor have overlapping field of views, wherein the first intensity and the second intensity are obtained simultaneously;

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

generating a multi-dimensional histogram in a multi-dimensional space having a first dimension corresponding to the first intensity and a second dimension corresponding to the second intensity; and

identifying one or more clusters in the multi-dimensional histogram, wherein the one or more clusters correspond to the presence of the hydrocarbons; and

generating an alert based on the presence of the 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 the 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 the hydrocarbons is detected according to the decision tree.

6. The method of claim 5,

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

7. The method of claim 6, wherein the multi-dimensional histogram comprises a mean intensity and a standard deviation.

8. The method of claim 6,

wherein at least one selected from a group consisting of the first spectral band and the second spectral band comprises 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 intensity and the second intensity are obtained using a bandpass filter.

10. The method of claim 8, further comprising:

calibrating the model without the presence of the 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 the 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 the 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 the 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 system for detecting presence of hydrocarbons on a surface, comprising:

a first sensor and a second sensor for monitoring reflected atmospheric radiation corresponding to a first intensity and surface emission from the surface corresponding to a second intensity to generate an image comprising a plurality of pixels, wherein each of the plurality of pixels is associated with the first intensity obtained using the first sensor corresponding to a first spectral band and the second intensity obtained using the second sensor corresponding to a second spectral band, wherein the first sensor and the second sensor have overlapping field of views, wherein the first intensity and the second intensity are obtained simultaneously; 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 the hydrocarbons based on the reflected atmospheric radiation and the surface emission according to a decision tree by;

generating a multi-dimensional histogram in a multi-dimensional space having a first dimension corresponding to the first intensity and a second dimension corresponding to the second intensity;

identifying one or more clusters in the multi-dimensional histogram, wherein the one or more clusters correspond to the presence of the hydrocarbons,

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 the hydrocarbons on the surface and comprises at least one selected from a group consisting of reflection contrast, temperature contrast, and emissivity contrast; and

generating an alert based on the presence of the hydrocarbons.

16. The system of claim 15, 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.

17. The system of claim 15, wherein the surface is a water surface.

18. The system of claim 15, 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.

19. The system of claim 15,

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

20. The system of claim 19, wherein the statistical diagram comprises a histogram of pixel intensity, wherein the histogram comprises a mean intensity and a standard deviation.

21. The system of claim 19, 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.

22. The system of claim 19, 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.

23. The system of claim 22,

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.