Challenges for the oil and gas industryThe oil and gas industry significantly outperformed market expectations from 2005 to 2014, but now it faces signifi-cant deficits with forecasted revenue shortfalls of as much as 20 to 30 per-cent. Companies are looking for ways to meet market challenges by adjusting business models and scrambling to cut huge capital expenditures, operating costs and headcount. In addition, they are seeking more innovative solutions in individual disciplines such as drilling.

This solution brief reports on a study that used multiphysics simulation and optimization technology to explore drill-bit design. The overarching objec-tive was to reduce costs by improving drilling process efficiency. The explora-tion project team used STAR-CCM+® software for multiphysics simulation

and the built-in Optimate+ software optimization solution from product lifecycle management (PLM) specialist Siemens PLM Software. Key criteria for the project included an increase in the rate-of-penetration (ROP), which is the speed at which a drill bit breaks the rock under it to open a borehole; and the opportunity to maximize product life expectancy by reducing product wear.

Physical testing versus simulationTo achieve its objectives, the project team considered many parameters that resulted in a multitude of possible design configurations. The added com-plexity of the drilling process also imposed significant time and cost implications. The team determined that physical testing across the full array of design options was not feasible.

In order to evaluate design perfor-mance, a decision was made to use simulation technology to create a digital

Challenges• Improve drilling efficiency to reduce

operating costs

• Enhance product life expectancy by reducing overall product wear

• Avoid costly, lengthy and oversimpli-fied lab/bench tests by deploying the digital twin to gain faster, more significant design insights

www.siemens.com/plm/simcenter

Siemens PLM Software

Maximizing drill-bit performance Solution brief

twin providing a detailed physics-based replication of the operating drilling equipment. The expectation was that the simulated model would also provide significant insight beyond physical testing results. In addition, by using the digital-twin approach, the team could combine simulation with design space exploration to leverage automated-search algorithms. This process would allow the team to efficiently explore the design space so they could more quickly develop innovative design solutions.

Creating the digital twin By using the 3D computer-aided design (CAD) modeler in STAR-CCM+, the team generated baseline geometry of the drill bit and used Optimate+ to control the primary geometric variables or design parameters (see figure 1). It is impor-tant to note that the integration process between STAR-CCM+ and Optimate+ requires no specialized knowledge of optimization theory, additional software coupling or complex script writing.

Figure 2 displays the drill bit geometric constraints (in green) on the size and location of the drilling mud holes; and the angle of the junk slots (in blue), which transport the drilling mud and cuttings up the drill string and away from the cutting face.

The digital-twin simulation was set up in STAR-CCM+ as a homogenous fluid using the k-epsilon realizable turbu-lence model with second order accuracy for convective flow and turbulence. The fluid domain was meshed with 336,000 polyhedral cells, and the drill bit was simulated at a rotation of 200 revolu-tions per minute (RPM). Using a moving reference frame for the drill-bit motion, the team used a steady-state approach to perform the simulation.

Design exploration and optimizationThe design space exploration objective was to maximize the cleaning effi-ciency; for example, to optimize the flow that removes drill cuttings from the drilling area. Cleaning efficiency was measured as a function of the wall shear stress at the cutting teeth and its ability to keep the drilling region clear of cuttings. The performance target was to be achieved while:

• Maintaining flow uniformity around the drill bit to efficiently transport cuttings up the drill string. The stan-dard deviation of the drill mud flow was to be lower than 0.1 on the plane noted in figure 3

• Not increasing the pressure drop across the drill mud delivery holes

• Working within the geometric design constraints summarized in figure 2

Solution focus

Figure 1: 3D model of drill bit created using STAR-CCM+ software.

Solutions • Use STAR-CCM+ to create CAD

baseline geometry and employ multiphysics simulation in design exploration studies

• Use Optimate+ to provide a built-in, easy-to-use solution for design optimization

Results • Significantly increased cleaning

efficiency

• Increased wall shear stress on the optimized drill-bit cutting face by 260 percent

• Improved flow uniformity for the optimized drill-bit face by 40 percent

• Determined that large drill mud supply holes near the center of the drill bit work the best

• Performed complete optimization study overnight on a desktop personal computer

The team controlled the design search procedure by using Optimate+, which features simultaneous hybrid explora-tion that is robust, progressive and adaptive (SHERPA), an optimization algorithm. SHERPA is part of Siemens PLM Software’s HEEDS™ software optimization suite. By using the optimi-zation solution, the team was able to automatically control the tuning param-eters of the design based on previous analyses results and adjustments. The design exploration process is outlined in figure 4.

With the model size and selected approach in place, the design explora-tion study commenced. The project contained 75 evaluations using models with approximately 336,000 cells each, and it was easily completed overnight using a personal computer. Key findings included:

• A 260-percent increase in cleaning efficiency with wall shear stress on the cutting face

• A 40-percent improvement in flow uniformity at the cutting face with a baseline standard fluid velocity deviation of 0.06 that was reduced to 0.038

It is important to note these key performance indicators (KPIs) were significantly improved while the pres-sure drop across the drill mud delivery holes was maintained below target.

Variable Unit Minimum Baseline Maximum

Angle deg 5 10 15

L1 m 0.04 0.05 0.08

L2 m 0.06 0.07 0.09

R1 m 0.008 0.01 0.0125

R2 m 0.006 0.0075 0.008

Figure 3: Measurement locations for flow uniformity, wall shear and pressure drop.

Figure 2: Drill-bit geometric constraints.

STAR-CCM+

• Verify meshing process and results

• Setup postprocessing

Optimate+

• Choose analysis

• Create variables and choose reports

• Enable access to power tokens

• Launch analysis

Postprocessing

• Postprocess data from all cases

• Response surfaces, Pareto front

Baseline Optimized

Wall shear stress 2.68 Pa 7 PaFlow uniformity 0.06 0.038

Pressure drop 1345.6 Pa 2963.2 PaGeometry constraints - -

Angle 5.3° 6.5°

HoleDist1 0.0752 m 0.04 mHoleDist2 0.0828 m 0.05 m

HoleRadius1 0.01196 m 0.0129 mHoleRadius2 0.0068 m 0.01 m

Figure 4: Automated design exploration procedure.

Figure 5: Post parallel plot of completed design exploration study results.

Table 1: Comparison of baseline and optimized design exploration results.

Figure 5 illustrates the complete design exploration study results and superim-poses the baseline and best designs over the other tested configurations. This data represents how each simu-lated design performed across the range of defined design and perfor-mance variables identified in the optimization study. The best-perform-ing design (highest wall shear stress) had the largest allowable drilling mud hole diameters (for both sets of holes), while minimizing the spacing between holes. Results are summarized in table 1.

A side-by-side comparison of the base-line and optimized drill bit presented in figures 6A and 6B highlights the differ-ence in the drilling mud flow delivery to the cutting face. The streamlines (iden-tified in figure 6a) show that moving the drilling mud holes closer to the center of the drill bit reduced the dead zone of low flow at the tip of the baseline.

The wall shear stress contour plot on the cutting teeth confirms the opti-mized design holes exhibit significantly higher wall shear. Wall shear stress improvements were realized with larger drill mud delivery holes that are located closer together with only a small change in junk slot angle, 5.3 degrees in the baseline compared to 6.5 degrees in the optimized design.

Baseline model

Results

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a)

b)

Figure 6a: Baseline versus optimized streamline plots. Figure 6b: Baseline versus optimized wall shear stress.

ConclusionBy using STAR-CCM+ and Optimate+ for the design space exploration study, the team produced a drill-bit design that resulted in a 260-percent increase in the wall shear stress, the key parameter in the removal of cuttings from the drilling area, and improved overall cleaning efficiency. In addition, flow uniformity was enhanced by approxi-mately 40 percent, which improved drill cutting transport up the drill string. These results were achieved while maintaining the required pressure-drop requirements.

The drill-bit optimization study helped the team determine that performance was improved by taking full advantage of the size of the drilling mud supply holes and positioning them closer to the center of the drill bit. Additionally, the team concurred that STAR-CCM+ and Optimate+ provided them with the capabilities to create better designs faster in order to rapidly deliver more effective, efficient and durable drill bits in the field.