System and Method for Modeling and Design of Pulse Fracturing Networks

Patent metadata

Field	Value
Publication number	US-2016003019-A1
Application number	US-201414322516-A
Country	US
Kind code	A1
Filing date	Jul 2, 2014
Priority date	Jul 2, 2014
Publication date	Jan 7, 2016
Grant date	—

Abstract

Systems and methods for analyzing and designing a customized pulse fracturing operation for fracturing a wellbore in a reservoir formation are disclosed. Pulsed fracturing can create multiple fractures that radiate away from the wellbore while minimizing near wellbore damage. This network can further be extended into the reservoir by utilizing an optimized pumping rate over a predetermined amount of time. The optimized pulse rate and duration can be determined by using a geomechanical and a reservoir simulator which can help in quantifying the production efficiency of the induced fracture network.

First claim

What is claimed is:

1 . A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause one or more processors to:
receive a plurality of input parameters, each input parameter relating to a wellbore in a reservoir formation; develop a rate and pressure dependent failure model based on the received input parameters; and simulate propagation of a pulse fracturing network in the reservoir formation by applying one or more pulse fracturing techniques to maximize fracture network extent while minimizing near wellbore damage.

2 . The non-transitory program storage device of claim 1 , wherein the failure model comprises predicting rate and pressure dependent failure surfaces.

3 . The non-transitory program storage device of claim 1 , wherein the failure model comprises predicting tensile failure.

4 . The non-transitory program storage device of claim 1 , wherein the failure model comprises predicting compactive failure.

5 . The non-transitory program storage device of claim 1 , wherein the failure model comprises predicting shear failure.

6 . The non-transitory program storage device of claim 1 , wherein the instructions further cause the one or more processors to create a customized pulse fracturing operation based on the simulation.

7 . The non-transitory program storage device of claim 6 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse rise period using formation specific material properties and rate and pressure dependent failure surfaces.

8 . The non-transitory program storage device of claim 6 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse peak using formation specific material properties and rate and pressure dependent failure surfaces.

9 . The non-transitory program storage device of claim 6 , wherein the customized fracturing operation comprises pulse load with a customized number of pulse cycles using formation specific properties and rate and pressure dependent failure surfaces.

10 . The non-transitory program storage device of claim 1 , wherein the input parameters comprise at least one of Young's Modulus, Poisson's ratio, porous rock density, rock gain density, unconfined compressive strength, cohesion, internal friction angle, formation anisotropy, and natural fracture characteristics.

11 . The non-transitory program storage device of claim 1 , wherein the instructions further cause the one or more processors to predict a fracture potential of a reservoir formation under pulse fracturing application.

12 . The non-transitory program storage device of claim 1 , wherein the input parameters are ranked and weighted.

13 . A method for designing a pulse fracturing operation, the method comprising:
receiving a plurality of input parameters, each input parameter relating to a wellbore in a reservoir formation; developing a rate and pressure dependent failure model based on the received input parameters; and simulating propagation of a pulse fracturing network in the reservoir formation by applying one or more pulse fracturing techniques to maximize fracture network extent while minimizing near wellbore damage.

14 . The method of claim 13 , wherein the failure model comprises predicting rate and pressure dependent failure surfaces.

15 . The method of claim 13 , wherein the failure model comprises predicting tensile failure.

16 . The method of claim 13 , wherein the failure model comprises predicting compactive failure.

17 . The method of claim 13 , wherein the failure model comprises predicting shear failure.

18 . The method of claim 13 , further comprising creating a customized pulse fracturing operation based on the simulation.

19 . The method of claim 18 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse rise period using formation specific properties and rate and pressure dependent failure surfaces.

20 . The method of claim 18 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse peak using formation specific properties and rate and pressure dependent failure surfaces.

21 . The method of claim 18 , wherein the customized pulse fracturing operation comprises pulse load with a customized number of pulse cycles using formation specific properties and rate and pressure dependent failure surfaces.

22 . The method of claim 19 , further comprising performing the customized pulse fracturing operation on the wellbore.

23 . The method of claim 13 , wherein the input parameters comprise at least one of Young's Modulus, Poisson's ratio, porous rock density, rock gain density, unconfined compressive strength, cohesion, internal friction angle, formation anisotropy, and natural fracture characteristics.

24 . The method of claim 13 , further comprising predicting a fracture potential of the wellbore under pulse fracturing application.

25 . The method of claim 13 , wherein the input parameters are ranked and weighted.

26 . A system, comprising:
a memory; a display device; and a processor operatively coupled to the memory and the display device and adapted to execute program code stored in the memory to: receive a plurality of input parameters, each input parameter relating to a wellbore in a reservoir formation; develop a rate and pressure dependent failure model based on the received input parameters; and
simulate propagation of a pulse fracturing fracture network in a reservoir formation by applying one or more pulse fracturing techniques to maximize fracture network extent while minimizing near wellbore damage.

27 . The system of claim 26 , wherein the failure model comprises predicting rate and pressure dependent failure surfaces.

28 . The system of claim 26 , wherein the failure model comprises predicting tensile failure.

29 . The system of claim 26 , wherein the failure model comprises predicting compactive failure.

30 . The system of claim 26 , wherein the failure model comprises predicting shear failure.

31 . The system of claim 26 , further comprising creating a customized pulse fracturing operation based on the simulation.

32 . The system of claim 31 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse rise period using formation specific material properties and rate and pressure dependent failure surfaces.

33 . The system of claim 31 , wherein the customized pulse fracturing operation comprises pulse load with a customized pulse peak using formation specific material properties and rate and pressure dependent failure surfaces.

34 . The system of claim 31 , wherein the customized fracturing operation comprises pulse load with a customized number of pulse cycles using formation specific properties and rate and pressure dependent failure surfaces.

35 . The system of claim 31 , further comprising initiating performance of the customized pulse fracturing operation on the wellbore.

36 . The system of claim 26 , wherein the input parameters comprise at least one of Young's Modulus, Poisson's ratio, porous rock density, rock gain density, unconfined

Assignees

• Weatherford Lamb

Inventors

• Safariforoshani Mohammadreza
• Huang Jian
• Lakshminarayanan Sunil
• Mutlu Ovunc

Classifications

• G06F30/28 Primary

  using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD] · CPC title

• E21B43/26 Primary

  by forming crevices or fractures · CPC title

• E21B49/006

  Measuring wall stresses in the borehole · CPC title

• E21B28/00

  Vibration generating arrangements for boreholes or wells, e.g. for stimulating production ({for fishing for or freeing objects E21B31/005;} for transmitting measuring-signals E21B47/14; for geophysical measurements G01V1/02) · CPC title