# US 11,907,836 B2 · Image processing of aerial imagery for energy infrastructure site status analysis

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 11,907,836 B2
- Document ID: US11907836B2
- Status: Granted
- Kind: B2
- Application number: 16/932,078
- Filed: 2020-07-17
- Published: 2021-01-07
- Granted: 2024-02-20
- Earliest claimed: 2019-01-14
- Assignees: Sourcewater, Inc.
- Applicants: Sourcewater, Inc.
- Inventors: Joshua Adler
- Web page: https://patentgrep.com/patent/US11907836B2

## CPC

- G06N 3/08: Learning methods
- 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)}
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06N 3/047: Probabilistic or stochastic networks
- G06N 3/09: Supervised learning
- G06T 17/05: Geographic models
- G06V 10/764: using classification, e.g. of video objects
- G06V 10/82: using neural networks
- G06V 20/176: {Urban or other man-made structures}
- G06N 3/045: Combinations of networks
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## 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

### Claim 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 an image including at least one captured image of a portion of terrain;
applying an EI feature recognition model to the image to generate information on an EI feature at a location in the portion of terrain;
obtaining, based on the location, supplemental information from a supplemental information source, the supplemental information source including at least one of a public records information source, an EI feature database, and location information of vehicles or vehicle drivers associated with the EI feature; and
determining the EI site status based on the information on the EI feature and the supplemental information.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, further comprising predicting future EI site activity based on the EI site status.

### Claim 3 (depends on 2)

The computer-implemented method of claim 2,
wherein the supplemental information source includes the EI feature database,
the method further comprising:
identifying at least one status attribute of the EI feature; and
storing a history of the at least one status attribute in the EI feature database,
wherein predicting the future EI site activity is based further on the history of the at least one status attribute.

### Claim 4 (depends on 2)

The computer-implemented method of claim 2, wherein predicting the future EI site activity includes predicting commencement of drilling or well completion on a specified timescale.

### Claim 5 (depends on 2)

The computer-implemented method of claim 2, wherein predicting the future EI site activity includes predicting a future service need.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, wherein the EI feature is a flare system associated with an oilfield well, and wherein determining the EI site status is further based on detecting flares or gas emissions from the flare system.

### Claim 7 (depends on 6)

The computer-implemented method of claim 6, wherein the supplemental information source is the public records information source including reports of oilfield well productivity and wherein determining the EI site status further includes predicting productivity of the oilfield well or a decline curve of the oilfield well based on a correlation between the reports of oilfield well productivity and the flares or gas emissions.

### Claim 8 (depends on 1)

The computer-implemented method of claim 1, wherein the EI feature is a flare system associated with an oilfield well and wherein determining the EI site status includes one or more of predicting pipeline capacity shortages, economic bases for transporting and selling oil and gas, and cost of well operations.

### Claim 9 (depends on 1)

The computer-implemented method of claim 1, wherein the supplemental information source is the EI feature database, and the supplemental information includes information about at least one additional EI feature selected from:
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.

### Claim 10

A system for processing images to determine Energy Infrastructure (EI) site status, the system comprising:
a non-transitory computer readable memory unit; and
at least one processor configured to execute computer instructions to:
receive an image including at least one captured image of a portion of terrain,
apply an EI feature recognition model to the image to generate information on an EI feature at a location in the portion of terrain,
obtain, based on the location, supplemental information from a supplemental information source, the supplemental information source including at least one of a public records information source, an EI feature database, and location information of vehicles or vehicle drivers associated with the EI feature, and
determine the EI site status based on the information on the EI feature and the supplemental information.

### Claim 11 (depends on 10)

The system of claim 10, wherein the at least one processor is further configured to execute the computer instructions to predict future EI site activity based on the EI site status.

### Claim 12 (depends on 11)

The system of claim 11, wherein the at least one processor is further configured to:
identify at least one status attribute of the EI feature;
store a history of the at least one status attribute in an EI feature database; and
predict the future EI site activity based further on the history of the at least one status attribute.

### Claim 13 (depends on 11)

The system of claim 11, wherein the at least one processor is further configured to predict the future EI site activity by predicting at least one of commencement of drilling or well completion on a specified timescale and predicting a future service need.

### Claim 14 (depends on 10)

The system of claim 10, wherein the EI feature is a flare system associated with an oilfield well and wherein the at least one processor is further configured to determine the EI site status based on detecting flares or gas emissions from the flare system.

### Claim 15 (depends on 14)

The system of claim 14, wherein the supplemental information source is the public records information source including reports of oilfield well productivity and wherein the at least one processor is further configured to determine at least one of productivity of the oilfield well, a decline curve of the oilfield well, a pipeline capacity shortages, economic bases for transporting and selling oil and gas, and cost of well operations based on the flares or gas emissions.

### Claim 16 (depends on 10)

The system of claim 10, wherein the supplemental information source is the EI feature database, and
the supplemental information includes information about at least one additional EI feature selected from:
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.

### Claim 17

A non-transitory computer readable medium storing computer instructions that, when executed by a processor, cause the processor to carry out a method for processing images to determine Energy Infrastructure (EI) site status, the method comprising:
receiving an image including at least one captured image of a portion of terrain;
applying an EI feature recognition model to the image to generate information on an EI feature at a location in the portion of terrain;
obtaining, based on the location, supplemental information from a supplemental information source, the supplemental information including at least one of a public records information source, an EI feature database, and location information of vehicles or vehicle drivers associated with the EI feature; and
determining the EI site status based on the information on the EI feature and the supplemental information.

### Claim 18 (depends on 17)

The non-transitory computer readable medium of claim 17, wherein determining EI site activity includes predicting future EI site activity.

### Claim 19 (depends on 18)

The non-transitory computer readable medium of claim 18, the method further comprising:
identifying at least one status attribute of the EI feature;
storing a history of the at least one status attribute in an EI feature database; and
predicting the future EI site activity based further on the history of the at least one status attribute.

### Claim 20 (depends on 17)

The non-transitory computer readable medium of claim 17, wherein the supplemental information source is the public records information source including reports of oilfield well productivity, wherein the EI feature is a flare system associated with an oilfield well, and wherein determining the EI site status is further based on detecting flares or gas emissions from the flare system and includes predicting one or more of productivity of the oilfield well, a decline curve of the oilfield well, pipeline capacity shortages, economic bases for transporting and selling oil and gas, and cost of well operations.