Systems and methods for subsurface oil recovery optimization

Patent metadata

Field	Value
Publication number	US-10415349-B2
Application number	US-201214350009-A
Country	US
Kind code	B2
Filing date	Oct 5, 2012
Priority date	Oct 6, 2011
Publication date	Sep 17, 2019
Grant date	Sep 17, 2019

Abstract

Systems and methods for subsurface secondary and/or tertiary oil recovery optimization based on either a short term, medium term or long term optimization analysis of selected zones, wells, patterns/clusters and/or fields.

First claim

The invention claimed is:

1. A computer-implemented method which comprises:
receiving, using a processor, input corresponding to a selection of one or more zones, wells, patterns/clusters or fields of a hydrocarbon fluid reservoir;
identifying one or more conditions associated with the one or more zones, wells, patterns/clusters or fields, the one or more conditions being identified based on real-time field data associated with the one or more zones, wells, patterns/clusters or fields;
determining a prediction for the one or more conditions by executing a predictive model that evaluates the real-time field data;
selecting one or more scenarios from a plurality of scenarios, the selection being based on the determined prediction, and each of the one or more selected scenarios corresponding to an action that optimizes the one or more conditions;
displaying a visual representation of the one or more selected scenarios, the visual representation indicating the action corresponding to each selected scenario, the one or more scenarios being ranked according to at least one of net present value, increased oil recovery, or reduced recovery of unwanted gas or fluids, and the one or more scenarios diagnosing a cause of an undesirable sweep efficiency health indicator by estimating correlation factors and well allocation factors;
receiving input corresponding to a selection of each of a scenario of the one or more selected scenarios and a prediction date;
determining, using the processor, an effect on the one or more conditions of the action corresponding to the selected scenario, the effect being determined as of the prediction date; and
performing the action corresponding to the selected scenario, the action proactively optimizing the one or more conditions of the one or more selected zones, wells, patterns/clusters or fields, so as to prevent the prediction from occurring.

2. The method of claim 1 , further comprising determining if optimization is desired based on the one or more selected scenarios and the effect of each corresponding action on the one or more selected zones, wells, patterns/clusters or fields.

3. The method of claim 2 , further comprising selecting one or more scenarios from the one or more selected scenarios for implementation.

4. The method of claim 3 , further comprising executing the corresponding action for each selected scenario as a medium term optimization response to an undesirable sweep efficiency health indicator.

5. The method of claim 4 , wherein the corresponding action for each selected scenario is remotely executed.

6. The method of claim 3 , further comprising sending an approval for manual implementation of the corresponding action for each selected scenario.

7. The method of claim 3 , further comprising sending a request for the implementation of the corresponding action for each scenario with a business case report and recommendation.

8. The method of claim 1 , wherein the one or more zones, wells, patterns/clusters or fields is selected from a sweep efficiency health display, which comprises one of a current sweep efficiency health display and one of multiple predicted sweep efficiency health displays.

9. The method of claim 8 , wherein the current sweep efficiency health display is based on current conditions data, which comprises real-time surveillance field data.

10. The method of claim 8 , wherein the cause of the undesirable sweep efficiency health indicator for the sweep efficiency health display is diagnosed using streamline numerical calculation to estimate the correlation factors and the well allocation factors.

11. The method of claim 1 , wherein the displayed scenarios and corresponding actions are ranked for proactive optimization.

12. The method of claim 1 , further comprising running the one or more selected scenarios on a simulator in real-time to determine the effect of each corresponding action on the one or more selected zones, wells, patterns/clusters or fields on the prediction date.

13. The method of claim 1 , wherein the displayed scenarios and corresponding actions comprise at least one workover or recompletion.

14. A non-transitory program carrier device carrying computer executable instructions for medium term oil recovery optimization, the instructions being executable to implement:
receiving, using a processor, input corresponding to a selection of one or more zones, wells, patterns/clusters or fields of a hydrocarbon fluid reservoir;
identifying one or more conditions associated with the one or more zones, wells, patterns/clusters or fields, the one or more conditions being identified based on real-time field data associated with the one or more zones, wells, patterns/clusters or fields;
determining a prediction for the one or more conditions by executing a predictive model that evaluates the real-time field data;
selecting one or more scenarios from a plurality of scenarios, the selection being based on the determined prediction, and each of the one or more selected scenarios corresponding to an action that optimizes the one or more conditions;
displaying a visual representation of the one or more selected scenarios, the visual representation indicating the action corresponding to each selected scenario, the one or more scenarios being ranked according to at least one of net present value, increased oil recovery, or reduced recovery of unwanted gas or fluids, and the one or more scenarios diagnosing a cause of an undesirable sweep efficiency health indicator by estimating correlation factors and well allocation factors;
receiving input corresponding to a selection of each of a scenario of the one or more selected scenarios and a prediction date;
determining, using the processor, an effect on the one or more conditions of the action corresponding to the selected scenario, the effect being determined as of the prediction date; and
performing the action corresponding to the selected scenario, the action proactively optimizing the one or more conditions of the one or more selected zones, wells, patterns/clusters or fields, so as to prevent the prediction from occurring.

15. The non-transitory program carrier device of claim 14 , further comprising determining if optimization is desired based on the one or more selected scenarios, the effect of each corresponding action on the one or more selected zones, wells, patterns/clusters or fields and an updated field development plan.

16. The non-transitory program carrier device of claim 15 , further comprising selecting one or more scenarios from the one or more selected scenarios for implementation.

17. The non-transitory program carrier device of claim 16 , further comprising executing the corresponding action for each selected scenario as a medium term optimization response to an undesirable sweep efficiency health indicator.

18. The non-transitory program carrier device of claim 17 , wherein the corresponding action for each selected scenario is remotely executed.

19. The non-transitory program carrier device of claim 16 , further comprising sending an approval for manual implementation of the corresponding action for each selected scenario.

20. The non-transitory program carrier device of claim 16 , further comprising sending a request for the implementation of the corresponding action for each selected scenario with a business case report and recommendation.

21. The non-transitory program carrier device of claim 14 , wherein the one or more zones, wells, patterns/clusters or fields is

Assignees

• Landmark Graphics Corp

Inventors

• Ranjan Priyesh
• Gorell Sheldon Burt
• Kumar Amit
• Cullick Alvin Stanley
• Carvajal Gustavo A
• Urrutia Karelis Alejandra
• Khan Hasnain
• Saputelli Luigi
• Nasr Hatem

Classifications

• G06F30/00

  Computer-aided design [CAD] · CPC title

• F16L21/005

  made of elastic material, e.g. partly or completely surrounded by clamping devices (comprising packing adapted to sealing by fluid pressure F16L17/04) · CPC title

• G01B7/023

  for measuring distance between sensor and object (G01B7/082 and G01B7/102 take precedence) · CPC title

• B60R3/007 Primary

  Removable steps or ladders, e.g. foldable (as access means for vehicle tops B60R3/005) · CPC title

• B65F2003/003

  Footboards · CPC title