Image processing of aerial imagery for energy infrastructure site status analysis

• US 10,460,170 B1
• Filed: 05/29/2019
• Issued: 10/29/2019
• Est. Priority Date: 01/14/2019
• Status: Active Grant

• Current Assignee: Ponderosa Advisors LLC
• Original Assignee: Sourcewater, Inc.
• Inventors: Adler, Joshua
• Primary Examiner(s): Tsai, Tsung Yin
• Application Number:
  US16/425,235
• Time in Patent Office: 153 Days
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/047 Probabilistic or stochastic networks
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06T 17/05 Geographic models
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/82 using neural networks
• CPC Class Codes: G06V 20/176 Urban or other man-made structures

Abstract

A computer-implemented method for processing images to determine EI site status is provided. The method includes image processing of an aerial image by two EI feature recognition models. A first EI feature recognition model recognizes a first EI feature and a second EI feature recognition model recognizes a second EI feature. The results of each model are further used to determine a composite indication of EI site status.

Claims

1. A computer-implemented method for processing images to determine Energy Infrastructure (EI) site status, the method to be carried out by at least one processor executing computer instructions, the method comprising:

receiving a working image including at least one aerial image of a portion of global terrain;

applying a first EI feature recognition model to the working image to generate information on a first EI feature at a first geographical location in the portion of global terrain at a first confidence level according to image content of the working image;

applying a second EI feature recognition model to the working image to generate information on a second EI feature at a second geographical location in the portion of global terrain at a second confidence level according to image content of the working image;

determining a composite indication of an EI site status based on at least the information on the first EI feature, the information on the second EI feature, the first confidence level and the second confidence level.

2. The computer-implemented method of claim 1, wherein the first EI feature is associated with a first EI feature type, and the second EI feature is associated with a second EI feature type, and wherein the first and second EI feature types are members of a set of EI feature types including one or more of:

an EI development site;

a frac-water pit, frac pond or frac water impoundment,

a well pad,

a drilling rig,

pipeline infrastructure,

a service road,

a clearing,

a vehicle or truck,

a tank battery,

a proppant store,

a drilling reserve pit,

a frac spread,

a sand mine,

a producing well,

a flare system,

solar panel mounts,

solar panels,

an electrical substation,

a security fence,

a building,

a cable system,

a wind energy collector,

meteorological monitoring equipment,

construction equipment,

hydroelectric reservoirs or forebays,

hydroelectric intake structures,

penstocks,

surge chambers,

a hydroelectric power house,

a hydroelectric tailrace.

3. The computer-implemented method of claim 2, wherein at least one of the information on the first EI feature and the information on the second EI feature further comprises a status attribute representative of a status of the respective first EI feature or second EI feature, and wherein the status attribute is a member of a set of status attributes including one or more of:

a detection date or time,

a location,

a type,

an area, length, width, height, size or volume,

a number,

a number of sub-parts,

a surface rights owner,

a mineral rights owner,

a fluid level or volume,

a fluid or material type,

a fluid or material color,

a fluid or material quality,

a fluid or material attribute,

a surface type,

a level of activity, inactivity or operation,

a brightness, intensity or spectral content,

a connectivity,

a power delivery or capability,

a bore size,

a flow rate.

4. The computer-implemented method of claim 1, further comprising:

obtaining, based on the first geographical location or the second geographical location, supplemental information from a supplemental information source;

determining the composite indication of an EI site status based further on the supplemental information.

5. The computer-implemented method of claim 4, wherein the supplemental information source is a public records information source or an EI feature database.

6. The computer-implemented method of claim 1, wherein the composite indication of EI site status relates to an existing or potential EI site, and is indicative of one or more of:

an EI site has reached a predetermined stage of development;

An oilfield EI site has all necessary facilities to commence drilling;

drilling has commenced on an oilfield EI site;

drilling has ceased on an oilfield EI site;

hydraulic fracturing has commenced on an oilfield EI site;

hydraulic fracturing has ceased on an oilfield EI site;

an EI site exhibits an absence of activity;

an EI site exhibits a commencement or recommencement activity;

a need for transport or infrastructure associated with a resource at an EI site has been identified;

a shortage or abundance of supplies, resource or equipment has been detected at an EI site,

an EI site is non-operational and is not supplying energy to an electrical power grid,

an EI site is operational and is supplying energy to an electrical power grid.

7. The method of claim 1, wherein the determining of the composite indication of an EI site status is performed by a processing function executing a pre-defined mathematical function.

8. The method of claim 1, wherein the determining of the composite indication of an EI site status is performed by a processing function utilizing a neural network.

9. The method of claim 1, wherein the determining of the composite indication of an EI site status is further based on information on a relationship between the first EI feature and the second EI feature.

10. The computer-implemented method of claim 9, wherein the information on a relationship between the first EI feature and the second EI feature comprises one or more of:

a functional or operational dependence between a type of the first EI feature and a type of the second EI feature;

a surface-rights ownership of the first and second geographical locations;

a mineral rights ownership of the first and second geographical locations;

a statistical distribution of the distance between a type of the first EI feature and a type of the second EI feature;

a conditional probability associated with the first EI feature and the second EI feature;

an association of the first or second locations to an identifier or location of an existing or potential EI site;

an association of the first or second oilfield features to an identifier or location of an existing or potential EI site.

11. The computer-implemented method of claim 1, wherein the composite indication is associated with a binary value indicative of whether conditions associated with the composite indication have been met.

12. The computer-implemented method of claim 1, wherein the composite indication is associated with a confidence level, or with a value indicative of the degree to which conditions associated with the composite indication have been met.

13. The computer-implemented method of claim 1, further comprising providing the composite indication of an EI site status to a user of an online platform.