1. IPS – 15-19
2015 International Perforating Symposium The Renaissance Hotel, Amsterdam May 19th-21st 2015
Production Flow Modeling of Perforation Tunnels Using Computer Tomography and Computational Fluid Dynamics
Speaker: Steve Zuklic
Rajani Satti, Dong Kim, Minsuk Ji, Derek Bale, Baker Hughes

2. Presentation Overview
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Introduction
Our Design Workflow
Objectives
Perforation Flow Laboratory
CFD Model
Results
Conclusions

3. Introduction IPS – 15-19 Critical aspects of perforation tunnels:
Size and shape of the tunnel
Complex fluid dynamics
Perforation damage
Perforation flow efficiency
Perforation flow laboratories have been
traditionally utilized to study the complex characteristics of perforation tunnels.
Challenges in flow laboratory experimentation
Large lead times
Associated costs
Limited data
Numerical tools in conjunction with experiments can provide better insight into the flow characteristics of perforated cores.
In well completions, perforation tunnels represent the conduits through which all communication with the reservoir takes place, both treating the reservoir and producing from it. The complex fluid dynamics surrounding these tunnels has been a subject of many research studies. In particular, the flow efficiency of perforation tunnels is critical in determining the economics of a completed well. Given the harsh conditions in the downhole environment, it is quite challenging to obtain such real-time measurements of tunnel performance. In recent years, perforation flow laboratories have been increasingly used to study perforation systems and their flow effectiveness in more detail (using API –RP 19B Section II and IV). However, experiments often become challenging due to large lead times in performing tests, associated costs and most importantly, limited data. As a consequence, numerical tools have been increasingly used in conjunction with experiments to provide better insight into the flow characteristics of perforated cores and perforated well-scale formations.

4. Perforated Well Scenario
Introduction
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Computational modeling of perforation systems are usually based on semi-analytical,
nodal analysis or detailed CFD studies.
Advantages of Computational Fluid Dynamics:
- Full Physics models can be employed
- Whole-field flow visualization (velocity and pressures)
Perf tunnel
formation
Drilling
damage
Well bore
Perforated tunnels
Formation
Drilling damage zone
Perforated Well Scenario
Computational Grid
Flow Modeling Results
In recent years, most of the numerical modeling on perforation systems has been based on
Semi analytical studies
Nodal analysis
CFD studies
Unlike other analysis tools, CFD provides a unique advantage, where full physics models with whole field flow visualization can be obtained. Of relevance to our study is the recent work of Sun et al & 2012, focused on developing and validating well-scale using Computational Fluid Dynamics. As seen from the figure above, the CFD workflow consists of developing a computational domain, generating the grid and finally conducting a flow analysis to visualize density, pressure, velocity.
However, all the studies mentioned above did not account for the true geometry of the tunnel (as obtained from a laboratory environment), which may not justify that the simulations are done in conjunction with laboratory.
Recent work of Datong et al.2011
CFD studies do not account for the exact geometry of the tunnel.

5. Our Design Workflow IPS – 15-19 Presented in IPS-15-5
The workflow is primarily targeted towards exploiting the capabilities of a perforation flow laboratory in conjunction with numerical modeling.
Motivated by the above, this study proposes a scientific workflow of utilizing the capabilities of the flow laboratory in conjunction with advanced CAD / CFD analysis to model and simulate the true geometry of a perforation tunnel to provide insight into the flow performance of a perforation tunnel.
Our modeling efforts are focused on two aspects:
Development of a novel full-physics CFD model that utilizes digital rock physics to simulate the flow around the true geometry of the perforation tunnel (focus of the study)
Development of a computational model based on laboratory apparatus to complement the transient effects seen in lab experiments (presented in IPS -15-5)
Presented in IPS-15-5

6. Objectives of the Study
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Develop a scientific workflow of utilizing the capabilities of the flow laboratory in conjunction with advanced CAD / CFD analysis.
Demonstrate how digital rock physics is utilized to develop a CFD ready model to model the complex flow around the tunnel.
Model and simulate the true geometry of a perforation tunnel to provide insight into the actual flow performance of a perforation tunnel.

7. Perforation Flow Laboratory
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The perforation flow laboratory is configured to provide perforation and flow testing as described in API Recommended Practice 19B and conform to the latest industry standards of Section-II and IV procedures. The flow laboratory provides the capabilities to study and qualify performance of different perforating systems in formation rock at reservoir conditions, influence of various factors on well productivity, and integrate this knowledge to develop a state-of-the-art perforation evaluation and design service. This in turn, allows us to design and qualify perforating solutions with the goal to optimize reservoir performance.
The perforation flow laboratory is configured to provide perforation and flow testing as described in API Recommended Practice 19B and conform to the latest industry standards of Section-II and IV procedures.

8. Integrated Testing Capabilities
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Apart from Standard Section-IV, we also provide the following services:
Effects of drilling damage on shaped charge performance
Influence of fluid loss control pills on productivity
Effects of acid stimulation
Quickturn Section-II testing capabilities (8 shots per day) for comprehensive characterization of shaped charge performance in downhole conditions
Advanced perforated core analysis including routine core analysis, mechanical properties, mineralogy, CT scanning, SEM, particle size analysis etc.
Integrated experimental and modeling efforts
Before discussing the modeling capabilities, it is important to mention the perforation flow laboratory and its importance to the overall perforation design optimization as well as development and validation of modeling tools. The perforating flow laboratory helps us conduct API Section II and IV experiments as well as look beyond perforating. Apart from standard Section-IV tests, we can evaluate influence of drilling damage, fluid loss control pills, acid stimulation and advanced analysis using CT scanning and routine core analysis.

9. Section-IV Test and CT scanning
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A generic shaped charge was considered to create a perforation tunnel around a sandstone Berea rock.
Details relating to the test conditions or the shape of the tunnel are not of interest in this study.
Primary interest is in demonstrating how digital rock physics can be utilized to develop a CFD ready model to model the complex flow around the tunnel.
After an API Section-IV test is conducted, the perforated core is CT scanned.
The figure shows a cross-sectional view of the perforation hole along with planar slices showing the axial extent and shape of the tunnel. Potential debris (which could be crushed rock or liner debris) is also seen in the figure. Also, note that at the terminating end of the tunnel, a thin extended region of the tunnel is also seen with this core. Again, for the purpose of the study, we are only interested in considering the shape of the tunnel (and not in how and what characterizes its shape).
CT scan of a Perforated Core
CT scanner

10. CFD : Model Assumptions
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Model Assumptions
- Steady state flow
- Neglect gravity effects
- Isothermal flow
- Incompressible fluid (water)
Conservation equations of mass and momentum are solved for a three-dimensional grid using commercial CFD software.
Flow variables (pressure, velocity etc.) are calculated from the CFD analysis.

11. CFD: Workflow from CT to CFD
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Smart-CFD approach utilized to
Simulate the true perforation geometry (instead of a cylindrical tunnel) in the flow simulation.
Accurately predict the flow characteristics around perforation tunnels.
Traditionally, while doing flow calculations, the perforation geometry has been assumed to be cylindrical and the flow is computed assuming the same. With the advent of CT scan methods, we were able to develop a smart-CFD approach where we utilized the true perforation geometry in our flow simulation to more accurately predict the flow characteristics around perforation tunnels. Fig below shows the overall analysis workflow employed for the CFD calculations.

12. CFD: Computational Domain
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Core radius = 3.5 in. (8.89 cm); core length = 30 in. (76.2 cm)
Core permeability = 200 mD
Core porosity is 15%
Pressure drawdown from inlet to outlet= 200 psi
Tunnel length = 20.7 in. (52.6 cm) with length of tip region around 4.5 in.
Water is the working medium
Inlet: axial flow condition

13. CFD: Simulation Cases and Verification
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Computational Fluid Dynamics simulations have been run for three cases.
Case 1 corresponds to the real perforation tunnel geometry including the debris left in the tunnel from the test.
Case 2 is identical to case 1 except that the debris is removed from the tunnel.
Case 3 replaces the perforation tunnel with a circular cylinder having the same volume as the real perforation tunnel and is thus called equivalent-volume cylinder.
Validation
PR from Experiments
PR from
Simulation
Case 1 (includes debris inside the tunnel)
1.1
1.4
As a first step, we attempted to conduct some preliminary validation studies using the experimental data from case 1. Case 1 (that includes the debris inside the tunnel) with inlet pressure of 2000psi provided a productivity ratio of 1.1 from the API-Section IV experiment. The CFD analysis under similar conditions yielded productivity ratio of 1.4. Although the results differ by around 30%, it is important to note the discrepancies between experiments and simulations (no damage zones accounted for in CFD analysis, core is assumed to be homogeneous etc.). In future studies, we plan to address some of these discrepancies and conduct a more detailed comparison of results.

14. CFD: Results – Flow Streamlines
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With debris
Without debris
Cylindrical tunnel
Fig shows the streamline patterns obtained from the simulations where 150 streamlines originating from the inlet end (shown on the left side of the plots) of the core are depicted. Plots from top to bottom correspond to cases 1, 2 and 3, respectively. Note that since the circular cylinder in case 3 has a uniform circular cross section whose area is the same as that of the real perforation tunnel at the outlet end of the core, and yet has the same volume as the real perforation tunnel, its length is shorter than that of the real perforation tunnel. The streamlines indicate that the flow entering the core advance somewhat into the core before changing direction toward and merging into the perforation tunnel. The further the location of flow entry point from the center of the core (perforation tunnel) at the inlet, the further the flow travels into the core before merging into the tunnel; the maximum distance is about 70% of the tunnel length. The streamline patterns become less and less complex from case 1 to 2 to 3. This is expected since cases 1 and 2 have irregular and rough perforation tunnel surfaces, while case 3 employs an axisymmetric and smooth tunnel surface. It is also noted that the velocity magnitude is much smaller when the equivalent-volume cylinder is used in place of the real perforation tunnel; maximum magnitude of 3m/s is shown for cases 1 and 2, while 0.15m/s is shown for case 3. Maximum flow velocities occur inside the perforation tunnel relatively close to the outlet, and therefore it is likely that the highly irregular surface of the real perforation tunnel leads to local acceleration of the flow, whereas the equivalent-volume cylinder surface is smooth and reduces such a mechanism.

15. CFD: Results – Pressure
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With debris
Without debris
Cylindrical tunnel
Fig shows the static pressure on the perforation tunnel surface. Plots from top to bottom correspond to cases 1, 2 and 3, respectively. Inlet (reservoir) side of the core is depicted on the left side of the plots. Maximum pressure is seen to occur at the inlet end of the perforation tunnel for all three cases (the maximum pressure shown in the legend is 40000Pa, or 5.8psi) and the static pressure decreases rapidly along the perforation tunnel toward the outlet. The surface pressure patterns are more irregular for cases 1 and 2 than case 3; this is again attributed to the irregular flows resulting from the irregular and rough surface of the real perforation tunnel.

16. CFD: Results – Velocity
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With debris
Without debris
Fig shows the velocity magnitude on the perforation tunnel surface. Similar to previous observations, more complex and larger magnitude velocities are found for cases 1 and 2 compared to case 3, because of the highly irregular surface of the real perforation tunnel. The mass flow rate at the perforation tunnel outlet is 0.025kg/s for case 1, 0.028kg/s for case 2, and 0.010kg/s for case 3. Since debris left inside the perforation tunnel hinders the flow, the mass flow rate from case 1 is smaller than that from case 2. The mass flow rate through the equivalent-volume cylinder is less than half of that from through the real perforation tunnel. Therefore, modeling the perforation tunnel with an equivalent-volume cylinder will lead to largely erroneous results, affecting predicted production rate of a well.
Cylindrical tunnel

17. CFD: Results – Localized Velocity Analysis
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With debris
Without debris
Fig. shows contours of velocity magnitude at 20 different cross sections along the perforation tunnel for case 1 (with debris) and case 2 (without debris). For the case 1, relatively large debris is seen in the front part of the tunnel (up to approximately 20% of the tunnel length). This large debris clearly block and perturb the flows in the perforation tunnel, as indicated by more complex flow patterns and higher flow velocity magnitudes at the five right-most cross sections. In contrast, case 2 does not exhibit such flow behavior.

18. Conclusions
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A first-of-its kind computational methodology of simulating the complex flow characteristics around a perforation tunnel has been developed and demonstrated.
The complex geometry of the perforation tunnel (from a typical API RP-19B Section IV experiment) is obtained using a CT-scan, digitized to generate a CAD model ready for CFD analysis.
The fluid flow simulations provided details on the following
Whole flow field visualization including fluid velocities, pressures, and flow rates.
Comparisons of flow characteristics between true geometry (with and without debris) and cylindrical geometry showed that geometry simplifications (equivalent-volume cylinder) will lead to largely erroneous results, affecting predicted production rate of a well.
Efforts are underway to:
Improve the accuracy of the CFD model (grid optimization, include turbulence effects etc.) and conduct comprehensive validation.
Integrate the advanced CFD analysis into perforating job design and optimization.

19. Acknowledgements / Thank You
Slide 19
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Acknowledgements / Thank You
Management of Baker Hughes (Steve Zuklic and David Craig) for supporting this study
Committee of the 2015 IPS Europe
This work is also being presented at the European Formation Damage Conference

20. Slide 20
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Questions ?