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A GUI for drilling simulation platform powered by AI in geothermal wells.

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Energy Department Announces $11.4 Million for New Projects to Advance Efficient Drilling for Geothermal Energy

WASHINGTON, D.C. – Today, the U.S. Department of Energy (DOE) announced the selection of seven projects totaling nearly $11.4 million to advance geothermal energy development. The projects will focus on accelerating the research and development (R&D) of innovative geothermal energy technologies in America.

“Geothermal energy is a clean and efficient base-load energy resource, making it an important part of our nation’s diverse energy portfolio,” U.S. Secretary of Energy Rick Perry said. “Developing new, efficient drilling technologies will reduce these costs and increase the availability of this domestic renewable energy resource.”

Currently, American geothermal electricity production is located solely in the western states, where conventional geothermal resources put about 3.8 gigawatts (GW) of electricity on the grid. It has the potential to expand through hydrothermal and enhanced geothermal systems, which could tap into an estimated 100 GW of currently inaccessible resources and remove the geographic barriers of conventional geothermal resources.

Technological innovation is necessary to economically convert these resources into cost-effective energy resources. The awardees will focus on early-stage R&D projects exploring innovative technologies for drilling geothermal wells that show the ability to reduce non-drilling time, improve rates of penetration, and identify methods to accelerate the transfer of geothermal drilling and related technologies from the laboratory to the marketplace.

Realtime Drilling Optimziation Software

This is part of a DOE project at Oklahoma State University.

Team members:

PI: Dr. Geir Hareland
Co-PI: Dr. Runar Nygaard
Co-PI: Dr. Mohammed F. Al Dushaishi
Dr. Saman Akhtarmanesh
Dr. Amin Atashnezhad

The project incorporates several modules to achieve a Real-time drilling optimization system with emphasis on geothermal drilling (Utah-Forge).

The PDC ROP modeling:

A model was developed for hard-rocks considering the PDC bit details including number of cutters, number of blades, cutter back rake, cutter side rake, cutter diameter, bit diameter, and operational parameters such as RPM, WOB, and apparent rock strength. Two concepts, including threshold weight on cutter (WOC_t) and threshold rate of penetration (ROP_t) introduced and used to detect the two main regions in drilling ROP-WOB plots.

The SALib library was used for sensitivity analysis to identify parameters with a significant effect on ROP, as seen in the following figure.

The size of black circles shows the contribution of each parameter on the dependent parameter (ROP). The connections are representative of the second-order interaction between parameters.

Drill string vibration model:

The drill string vibration model developed (Al Dushaishi et al. 2019) was used for vibration simulation and to detect the critical speed regions. The critical regions are considered and are avoided for operational parameter design purposes.

PDC cutter temperature model:

Glowka (1978) developed an analytical PDC cutter temperature model. The Glowka model was used for tracking the cutter temperature in real-time considering several parameters including bit grade.

Realtime bit wear model:

A Real-time bit wear model was developed to track the bit grade in real-time. This is essential due to the fact that the cutters are progressively worn out which will affect the drilling performance, depth of cut, rate of penetration, cutter temperature, etc.

The Realtime Drilling Optimization Platform has five tabs including

  • Main Page
  • Analysis Details
  • QC Analysis
  • Plot Results
  • Streaming

The system simulates the ROP, taking the essential parameters as a .csv file including depth, dt, WOB, RPM, ROP_data, and rock strength. In the Analysis tab shown below, the user has access to around 110 design parameters.

PDC ROP Simulation results:

In step one, the ROP is simulated using the drilling optimization software and the results are seen in the following figures.

Above Figures reference: 
ARMA 21–1214
ROP Model for PDC Bits in Geothermal Drilling
Akhtarmanesh, S.
Oklahoma State University, Stillwater, OK, USA
Atashnezhad, A., Hareland, G. and Al Dushaishi, M.
Oklahoma State University, Stillwater, OK, USA

In step two, the software back calculates the rock strength in real-time, using the ROP model and ROP_data and bit details. The ROP_data is used in the ROP model and the one unknown parameter (ARS) is back-calculated. The ARS then is turned into the CCS and UCS considering the depth and MW into account.

In step three, the user can run the software to calculate the best WOB and RPM for the current foot of drilling and assuming that the rock strength is the same for the next foot. Knowing the rock strength, a foot ahead, the searching algorithm (differential evolution algorithm) will find the best WOB and RPM to maximize the objective function (defined by the user, i.e. MSE, ROP, or combination of MSE and ROP) while avoiding the critical vibrational and cutter temperature defined by the user.

The user also can-do separate drill string vibration analyses on different rock strengths.

The Software output for vibration analysis is seen below:

The software will plot and compares the simulation results in 5 separate stages. The user can save the analysis design in CSV format along with the simulation outputs from three steps. The software can read the WITSML file and generates its necessary input file to be used in simulation and optimization procedures.

ROP, Temperature and MSE simulation:

A simulation for ROP, Temprature, MSE for different BG values and at constant rock strength are seen at the following.

Artificial Intelligence realtime optimization results

The drilling real-time optimization system was used for Utah-Forge Well 58-32. The results are seen in the following figures.

Above Figures reference: 
ARMA 21–1215
Developing a Drilling Optimization System for Improved
Overall Rate of Penetration in Geothermal Wells
Atashnezhad, A.
Oklahoma State University, Stillwater, OK, USA
Akhtarmanesh, S., Hareland, G., and Al Dushaishi, M.
Oklahoma State University, Stillwater, OK, USA

As it is seen in the drilling time plot, there is a potential for decreasing the drilling time of the drilling intervals by 43%.

The GDR website has made available the final GUI at the following link.

https://gdr.openei.org/submissions/1367