Systems and methods for analyzing resource production

• US 10,410,298 B1
• Filed: 02/24/2016
• Issued: 09/10/2019
• Est. Priority Date: 06/08/2015
• Status: Active Grant

• Current Assignee: Datainfocom Usa, Inc.
• Original Assignee: Datainfocom Usa, Inc.
• Inventors: Basu, Atanu, Mohan, Daniel, Wang, Chun, Venter, Frederick
• Primary Examiner(s): Shah, Kamini S
• Assistant Examiner(s): Guill, Russ
• Application Number:
  US15/052,634
• Time in Patent Office: 1,294 Days
• Field of Search: 703 10
• CPC Class Codes: E21B 2200/20 Computer models or simulations, e.g. for reservoirs under production, drill bits
• CPC Class Codes: E21B 2200/22 Fuzzy logic, artificial intelligence, neural networks or the like
• CPC Class Codes: E21B 43/11 Perforators; Permeators
• CPC Class Codes: E21B 43/12 Methods or apparatus for controlling the flow of the obtained fluid to or in wells E21B43/25 takes precedence; valve arrangements E21B34/00
• CPC Class Codes: E21B 43/121 Lifting well fluids monitoring of down-hole pump systems E21B47/008
• CPC Class Codes: E21B 43/122 Gas lift
• CPC Class Codes: E21B 43/128 Adaptation of pump systems with down-hole electric drives
• CPC Class Codes: E21B 43/129 Adaptations of down-hole pump systems powered by fluid supplied from outside the borehole gas-lift E21B43/122; jet pumps E21B43/124
• CPC Class Codes: E21B 43/16 Enhanced recovery methods for obtaining hydrocarbons
• CPC Class Codes: E21B 43/164 Injecting CO2 or carbonated water in combination with organic material C09K8/594
• CPC Class Codes: E21B 43/20 Displacing by water
• CPC Class Codes: E21B 43/26 by forming crevices or fractures
• CPC Class Codes: E21B 44/00 Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
• CPC Class Codes: E21B 47/022 of the borehole, e.g. using geomagnetism
• CPC Class Codes: E21B 49/00 Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
• CPC Class Codes: E21B 49/003 by analysing drilling variables or conditions E21B49/005 takes precedence; systems specially adapted for monitoring a plurality of drilling variables or conditions E21B44/00
• CPC Class Codes: E21B 7/00 Special methods or apparatus for drilling
• CPC Class Codes: E21B 7/04 Directional drilling
• CPC Class Codes: E21B 7/046 horizontal drilling drilling with mechanical conveying means E21B7/003
• CPC Class Codes: G01N 2333/4706 stimulating, promoting or activating activity
• CPC Class Codes: G01V 1/00 : Seismology; Seismic or acoustic prospecting or detecting
• CPC Class Codes: G01V 11/002 : Details, e.g. power supply systems for logging instruments, transmitting or recording data, specially adapted for well logging, also if the prospecting method is irrelevant means for transmitting well survey signals E21B47/12; signal transmission systems in general G08C; transmission in general H04B
• CPC Class Codes: G01V 20/00 : Geomodelling in general
• CPC Class Codes: G01V 2210/66 : Subsurface modeling
• CPC Class Codes: G01V 2210/665 : using geostatistical modeling
• CPC Class Codes: G05B 13/028 : using expert systems only
• CPC Class Codes: G05B 13/048 : using a predictor
• CPC Class Codes: G06F 16/35 : Clustering; Classification
• CPC Class Codes: G06F 30/17 : Mechanical parametric or variational design
• CPC Class Codes: G06F 30/20 : Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 3/02 : Neural networks
• CPC Class Codes: G06N 3/08 : Learning methods
• CPC Class Codes: G06N 3/126 : Evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: G06Q 10/06 : Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06313 : Resource planning in a project environment
• CPC Class Codes: G06Q 10/06315 : Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 : Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/067 : Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/105 : Human resources
• CPC Class Codes: G06Q 10/1097 : Task assignment
• CPC Class Codes: G06Q 30/00 : Commerce
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0235 : constrained by time limit or expiration date
• CPC Class Codes: G06Q 30/0255 : based on user history
• CPC Class Codes: G06Q 30/06 : Buying, selling or leasing transactions
• CPC Class Codes: G06Q 40/00 : Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 50/02 : Agriculture; Fishing; Forestry; Mining
• CPC Class Codes: Y02P 90/80 : Management or planning

Abstract

A method for completing a well includes receiving completion parameters associated with a well within a field; projecting a production of the well based on the completion parameters using a completion engine applied to a field-specific model; prescribing proposed completion parameters for the well to comply with a production objective using the completion engine applied to the field-specific model; projecting a proposed production based on the proposed completion parameters using the completion engine applied to the field-specific model; and recompleting the well in accordance with the proposed completion parameters.

Claims

1. A method for completing a well within a field, the method comprising:

receiving completion parameters associated with one or more additional wells within the field, a first portion of the completion parameters being received in a form of structured data, and a second portion of the completion parameters being received in a form of unstructured data;

transforming the unstructured data into transformed structured data;

based on the received completion parameters in the form of the structured data and the transformed structured data, building a plurality of field-specific models;

selecting one of the plurality of field-specific models, wherein the selected field-specific model incorporates a proximity depletion synthetic variable derived from distances to adjacent wells from the well within the field and times of production of the adjacent wells;

receiving a production objective associated with the well within the field;

based on the selected field-specific model, prescribing proposed completion parameters for the well to comply with the production objective using a completion engine;

based on the proposed completion parameters and the selected field-specific model, projecting a proposed production for the well using the completion engine; and

recompleting or reworking the well in accordance with the proposed completion parameters.

2. The method of claim 1, further comprising receiving a location of the well, wherein the projecting and the prescribing are based on the location.

3. The method of claim 2, wherein the location includes a horizontal location within the geological structure.

4. The method of claim 1, further comprising receiving one or more geological, geophysical, petrophysical, lithological, and/or mineralogical parameters associated with the field, wherein the projecting and the prescribing are based on the received geological, geophysical, petrophysical, lithological, and/or mineralogical parameters.

5. The method of claim 1, wherein the completion parameters include casing parameters.

6. The method of claim 1, wherein the completion parameters include identification of stages.

7. The method of claim 1, wherein the completion parameters include perforation parameters.

8. The method of claim 7, wherein the perforation parameters include location.

9. The method of claim 7, wherein the perforation parameters include a number of perforations.

10. The method of claim 1, wherein the completion parameters include fracking parameters.

11. The method of claim 10, wherein the fracking parameters include pressure.

12. The method of claim 10, wherein the fracking parameters include proppant amount.

13. The method of claim 10, wherein the fracking parameters include proppant composition.

14. The method of claim 10, wherein the fracking parameters include flow rate.

15. The method of claim 1, wherein the completion engine includes a neural network.

16. The method of claim 1, wherein the completion engine includes a regression.

17. The method of claim 1, wherein projecting the proposed production for the well includes projecting a proposed cumulative production for the well.

18. The method of claim 1, further comprising projecting a production of one or more of the adjacent wells proximal to the well.

19. The method of claim 1, further comprising comparing a recompletion cost to benefits associated with the proposed production for the well.