CLIAMS:We claim:
1. A method to perform oil and gas upstream surveillance, the method comprising:
generating, by a production surveillance device, one or more real-time patterns from one or more sensor data received from one or more sensors;
comparing, by the production surveillance device, the one or more real-time patterns with one or more pre-defined patterns;
determining, by the production surveillance device, a confidence prediction score based on the comparison of the one or more real-time patterns with the one or more pre-defined patterns; and
generating, by the production surveillance device, one or more alerts based on the confidence prediction score to perform oil and gas upstream surveillance.
2. The method of claim 1, further comprising updating the production surveillance device with the one or more real-time patterns.
3. The method of claim 1, wherein the one or more pre-defined patterns comprises one or more pre-recorded patterns associated with one or more equipment failure events.
4. The method of claim 3, wherein the one or more equipment failure events comprises gas-oil-ratio event and water-cut ratio event.
5. The method of claim 3, wherein the pre-recorded one or more patterns are generated by extrapolating, simulating and normalizing the one or more sensor data for the one or more equipment failure events.
6. The method of claim 1, wherein the confidence prediction score is determined as a normalized form of the one or more sensor data expressed in terms of a percentile value and a mean percentile.
7. A production surveillance device comprising:
a memory;
a processor coupled to the memory storing processor executable instructions which when executed by the processor causes the processor to perform operations comprising:
generating one or more real-time patterns from one or more sensor data received from one or more sensors.
comparing the one or more real-time patterns with one or more pre-defined patterns;
determining a confidence prediction score based on the comparison of the one or more real-time patterns with the one or more pre-defined patterns; and
generating one or more alerts based on the confidence prediction score to perform oil and gas upstream surveillance.
8. The production surveillance device of claim 7, further comprising updating a training model with the one or more real-time patterns.
9. The production surveillance device of claim 7, wherein the one or more pre-defined patterns comprises one or more pre-recorded patterns associated with one or more equipment failure events.
10. The production surveillance device of claim 9, wherein the one or more equipment failure events comprises gas-oil-ratio event, water-cut ratio event.
11. The production surveillance device of claim 9, wherein the one or more pre-recorded patterns are generated by extrapolating, simulating and normalizing the one or more sensor data for the one or more equipment failure events.
12. The production surveillance device of claim 7, wherein the confidence prediction score is determined as a normalized form of the one or more sensor data expressed in terms of a percentile value and a mean percentile.

13. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor causes a production surveillance device to perform operations comprising:
generating one or more real-time patterns from one or more sensor data received from one or more sensors.
comparing the one or more real-time patterns with one or more pre-defined patterns;
determining a confidence prediction score based on the comparison of the one or more real-time patterns with one or more pre-defined patterns; and
generating one or more alerts based on the confidence prediction score to perform oil and gas upstream surveillance.

Dated this 20th day of May, 2015

SHWETHA A CHIMALGI
OF K & S PARTNERS
AGENT FOR THE APPLICANTS
,TagSPECI:FIELD OF THE INVENTION
This disclosure relates generally to monitoring mechanical equipment in oil and gas production, and more particularly to a system and method for improved production surveillance using visual pattern recognition in oil and gas upstream.