1. Finding the Optimum BHA through Data Analytics & Modeling
Brandon Cherry

2. Outline Introduction BHA Modeling Data Case Study-Post Analysis
Description of the Model
Rock-Bit-BHA coupling
Bit Steerability
Vibrations
Data
TFO efficiency
WOB
Hole Overgauge
Case Study-Post Analysis
Curve
Lateral
Conclusion

3. Introduction
The methodology proposed in this presentation shows an effective way to analyze post run data and to understand and predict downhole behavior:
The Drilling Bit Characteristics
Steerability (Side cutting ability)
Walking tendency (Turn rate)
The Rock Formation:
Hardness (UCS)
Anisotropy (Dip angle)
The Directional System:
Rotary Steerable System (RSS)
BHA Rotary
Steerable Mud Motor
With/Without Reamer Capability
The methodology proposed in this presentation shows an effective way to analyze post run data and to understand and predict downhole behavior:
The three main factors that we consider are the bit characteristics, the rock formation, and the directional system.
(State each bullet point)

4. (Deflection, Tilt, Bending Moment, Contact Forces)
Bit-Rock-BHA Model
Rock-Bit Model
BHA Model + + =
(Deflection, Tilt, Bending Moment, Contact Forces)
We’ve found that combining a BHA model with a detailed bit/formation model can maximize an engineer’s understanding of the interaction between the rock, the bit, and the BHA.

5. Bit Steerability & Walk
Turn Rate
Build/Drop
Rate
High Bit Steerability = High Side-Cutting ability of the bit
Bit Steerability = % for most PDC Bits
Bit steerability is defined as the side-cutting ability of the bit and attributes to build and drop rates
The bit walk angle is the angle between where the side force is applied and the direction of deformation. This attributes to turn rates.

6. Effective Gauge Length
Bit Steerability
Effective Gauge Length
Lab Results
Model
Bit Steerability (%)
Gauge Length (in)
It’s important to understand the effect that gauge length can have when considering a bit.
We can see here that lab tests show that an increase in gauge length decreases bit steerability and vice versa for a short gauge bit.

7. Bit Tilt Theory
This slide shows us the differences between long gauge and short gauge bits.
A longer gauge bit will naturally want to drill in the direction of the system’s tilt. While the shorter gauge bit will want to drill into the direction of the side force.
Formation characteristics also play a large role in drilling behavior (Next slide).

8. Bit Steerability vs. Rock Formation
Effect of Rock Hardness
We can see that if we have the same bit and same BHA, it’s still possible to not get the same build rates. This is due to potential differing formations and rock hardness.
The bit steerability drastically drops as we transition from a soft formation to a hard formation.
It’s extremely important to know the UCS of the formation you are drilling to improve efficiency.

9. Vibration Modal Analysis
• The evaluation of critical RPM based on resonant frequency of the BHA
• Torsional and Axial Nodes
– Dependent on entire Drill String
– Dependent on Stiffness/Mass
– Easy to plan for in advance and apply across several wells/fields
• Lateral Node
– Dependent mainly on BHA & Well Path
– Sensitive to WOB & Hole Overgauge

10. Data Quality BHA Details Drilling Parameters (i.e. WOB)
Bit Characteristics
Motor/RSS Specifications
String Diameters
Stabilizer Placement
Drilling Parameters (i.e. WOB)
Toolface Orientation & Slide/Rotate Length (Raw Data vs. Slide Sheet)
Rock Formation Hardness (UCS)
Mention each bullet point.

11. Bottom Hole Assembly
Having a detailed and accurate BHA is crucial when trying to understand and predict the drilling behavior down hole.
This is an example of a detailed BHA input with accurate OD’s, ID’s, and contact points in the wellbore.

12. Tool Face Tendency
Planning ahead for Slide Efficiency & Slide Time is key for designing your BHA build rate requirements
Toolface Control
Reactive Torque
Formation deflections
Slide vs Rotate
% of time sliding vs rotating 0°
15°
30°
45°
When trying to build the optimum BHA for build rates, some trend analysis should be done from offset wells or known formation tendencies.
Knowing this information will help you to predict reactive torque and possible formation deflections.
It’s also critical to plan the percent of time sliding vs. rotating as switching back and fourth can create some tortuosity/micro doglegs in the wellbore.
This figure shows us the build and turn rates calculated for a steerable mud motor at different toolface orientations.
(Elaborate on graph).

13. Slide Sheet vs TFO Data
Discrepancies in slide sheets vs. actual toolface orientation can be detrimental to the accuracy of post analysis.
Slide Sheet = 340 deg
Avg. Raw TFO = 324 deg
Discrepancies in slide sheets can be detrimental to the accuracy of post analysis.
With a constant 340 deg TFO for the entire stand, an assumption has to be made that there is no tortuosity present and we have a perfectly smooth borehole.
However, looking at the EDR data, we can see that due to possible reactive torque or deflections, there are fluctuations in the TFO. This leads to tortuosity being present.

14. Weight on Bit
The WOB applied during drilling operations has a major effect on modeling
Deflection and contact points can change according to the level of compression
WOB (klbf)
Inclination (deg)
Build Rate (deg/100 ft) 20 10 15 30
16.6
Accurate WOB data is also very important when it comes to modeling and predicting BHA behavior.
This particular study showed that at the same inclination, applying more WOB would increase the build rate by almost 2 degrees.

15. Hole Overgauge
The larger the hole overgauge, the more likely you wont achieve your build rates
Much like WOB, the presence of Hole Overgauge can result in drastically different build rates than what was originally predicted.
We can see here that the difference in 0 and 1 inch hole overgauge led to a drop of almost 5 degrees in build rates.
Putting all of this information and data together allows us to build strong models and ultimately gain a better understanding of the formation we are drilling, as we’re about to see in the next slides.

16. Case Study – BHA Post Analysis Methodology
Designed an optimized BHA by:
Observing the results of a steerable mud motor BHA that drilled in multiple formations in the curve and lateral
Collecting accurate post run data from the field
Defining or zoning specific areas for segmentation
Performing a sensitivity analysis on hole overgauge, bit steerability/walk, and friction factor

17. Case Study – Data Segmentation
Input:
Actual Surveys
Run Interval & MW
Actual BHA
WOB Log
TFO Log
Activation Level
Calculating:
Activation %
Average TF
Average WOB
User Selected:
Intervals based on similar trend, RSS Activation, Inclination, Formation, etc
After obtaining data from the field, specific zones or segments were created to isolate trends and behaviors.

18. Case Study – Data Segmentation
Next, a sensitivity analysis was performed in order to match the model’s predicted behavior to what actually occurred.
This is done by adjusting bit steerability, walk, and hole overgauge.

19. Post Analysis – Curve Section
Actual Build Rates (Red Lines) vs Predicted/Calibrated Build Rates (Green Squares)
The results of the case study showed that the two formations in the curve section had very different hole overgauges, which lead to lower build rates in one vs. the other.

20. Hole Overgauge – Curve Section
First contact point shifted from sleeve to motor bend when Overgauge increases from 0.25in to 0.75in
The model showed that while drilling with a smaller overgauge, build rates were sustained due to the contact point on the motor being on the sleeve.
The contact point then shifted to the motor bend when drilling with the larger overgauge, which lead to the drop in build rates.

21. Post Analysis – Lateral Section

22. Rotating Tendency – Lateral Section
BHA Rotating 90 degree Inclination –
Effect of WOB & Bit Steerability
In this case, we noticed that at around 15% bit steerability, the effect of WOB was much less and the build/drop rate was within +/- 20 deg/100ft.
One suggestion to improve this BHA was to slightly increase the gauge length of the bit to reduce the bit steerability.
The calibration performed in this case study allowed us to

23. Conclusions
Coupling Bit, Rock and BHA models effective for understanding directional behavior
Case study allowed the determination of UCS, hole overgauge, and ultimately, an optimized BHA design for the next well

24. Thank You