Maximize Fracking Profitability with ANSYS

This article explains how ANSYS and few other tools can be used to perform hydraulic fracturing, or commonly known as fracking, to reduce costs and increase profitability of shale gas projects.

Shale Gas

Shale gas is a form of natural gas trapped within shale formations. Because of its abundance, shale gas is a lot cheaper than it has been in years. Hydraulic fracturing or fracking helps in extracting it efficiently.

According to American Enterprise Institute, “the direct benefit of increasing oil and gas production includes the value of increased production attributable to the technology. In 2011, the USA produced 8.5 trillion cubic feet of natural gas from shale gas wells. Taking an average price of $4.24 per thousand cubic feet, that’s a value of about $36 billion, due to shale gas alone.” As a result of increase in fracking, natural gas imports in United States reduced by 25 percent between 2007 and 2011.

What is Fracking?

The term simply means creating fractures using hydraulic fluids. In this technique, production teams pump huge volumes of water and proppant at high pressure into the gas well. They also mix a few chemicals, which improve fracking performance, along with the water during pumping. Shale layers, being less permeable, minimize the flow of the natural shale gas trapped.

Fracking is useful in creating a connected fractured network between pores of the rock through which natural gas escapes out. In the first step, production teams drill horizontally along the shale layers. From the perforations, specialists pumps water into the rock. Since water is sent in with high pressures, the shale layers fractures. Once the pressure is decreased, they retrieve water from the shale layers leaving behind sand particles. However, the proppant dwells in the rock layers keeping the cracks open thereby allowing gas to escape.

Benefits and Disadvantages of Fracking

Fracking helps in accessing the natural shale gas trapped deep down beneath the earth. With traditional methods of extraction, we cannot exploit this energy potential. Recently-developed methods of vertical and horizontal drilling added favor to fracking. They permit drilling thousands of feet deep inside the ground in order to access the trapped shale gas.

It is said that shale gas causes lesser air pollution when compared to other dirty fuels like coal and oil. However there are ways in which fracking itself can cause more devastating effects such as air emissions and climate change, high water consumption, water contamination, land use, risk of earthquakes, noise pollution, and health effects on humans.

Economic Benefits of Simulation

To achieve an optimal design for a gas well, standard industry practice is to conduct a large number of field trials that require high capital investment and time which significantly increases the project value.

In order to obtain a profitable production of shale gas, I recommend you to use a fully coupled 3D hydraulic-mechanical simulation. Obviously the costs of such simulation are a lot lower than traditional methods. Many of our customers in the Oil & Gas industry have yielded better output with a higher project profitability.

You can find the schematic view of simulating Hydraulic Fracture below.Schematic view for fracking simulation

Essential Pre-Requisites for Simulation

We gather the input data for simulation from different physics such as geology, petrophysics and geomechanics. From the geology of the rock structure, we extract the lithology and layering, altitudes of beddings and natural fracture data. Accurate determination of petrophysical properties for both the reservoir and fluid contents is necessary. We also need to consider features like porosity, permeability and saturation for the reservoir. It also includes evaluating the properties that help in determining the hydrocarbon concentrations in the reservoir and its ability to produce the gas.

Along with the surface and sub-surface properties of the rock, the in-situ stress parameters also have same importance in simulation. I also account for elastic properties and strength parameters of intact rocks. The geomechanical studies of the rock structure also reveal the strength parameters of natural fractures, if any. Using multiPlas, I model these rock-specific material parameters and joints.

Of course, gathering this data can look daunting to you. However our expertise combined with strengths from Dynardo GmbH – the leading global experts in simulation of hydraulic fracturing – can help!

Fracking Simulation – Readying the Model

In the simulation of fracking process, I use a sequential coupled hydraulic-mechanical modeling approach. Therefore, I construct two models – a hydraulic flow model and a mechanical model simultaneously.

3D model with different soil layers for fracking simulation
3D model with different soil layers

To account the strength and stress anisotropies of the rock structure, I need to consider a 3D model. These variables help us to constantly monitor the behavior of fracking process. To capture the anisotropic nature of the rocks, you’ll need strength and stress anisotropies of the rock matrix and fracture system.

Sequentially Coupled Hydraulic-Mechanical Analysis in ANSYS

In ANSYS Mechanical, we start with a transient hydraulic flow analysis (analogous to transient thermal analysis) to understand the pore pressure field. The pressure increases in the fracture-initiated locations due to the pumping of fluid and low permeability of rock. If the pressure is large enough, the rock starts to fail and fractures open up. As a result, the permeability of the rock structure increases and changes the pressure distribution in the hydraulic flow model. From a mechanical perspective, pressure increase changes the effective stresses within the rock. After every fluid time increment, change in the mechanical forces from pore pressure change will be introduced into the mechanical analysis. The forces on every discretization point of the smeared continuum are computed from the pore pressure gradient.

I setup the coupling inside ANSYS in an explicit manner. Consequently, one iteration cycle is performed for every time step. The time step needs to adequately represent the progress of the fracture growth. At each time step, a transient hydraulic flow analysis starts first. Then the mechanical analysis with the updated pressure field from the hydraulic flow model is conducted. The mechanical analysis results in updated stress, plastic strain fields and hydraulic conductivities. i apply the updated hydraulic conductivities to the hydraulic model in the subsequent time step.

Crack expansion in the model while performing fracking analysis
Crack expansion in the model

In mechanical analysis, the development of fractures is represented by a plastic model in ANSYS. As a result, I cannot directly measure fracture openings and hence I’ll need to calculate it based on the plastic strains.

Model Calibration & Optimization of Fracking Paramaters

Because of large number of statistically-varying and reservoir parameters, the reservoir model needs advanced calibration procedure. At first, I will need to calibrate numerical parameters such as maximum permeability of open joints or energy dissipation at pore pressure frontier.

After calibration of all the parameters, I identify the most important parameters contributing to maximum crack volume using optiSLang software. As you will recognize, maximum crack volume correlates to maximum shale gas output. I validate the behavior of such important parameters and then calibrate the analysis model to the field measurements. I use the calibrated model later in order to optimize the simulated volume and predict the gas production rate of the wells.

Summary & Outlook

Evidently, application of simulation to the fracking process will underline its predictability. Simulation cut downs the costs of field trials, brings down the time-to-market thereby significantly increases the project profitability.

If you’re into gas exploration, you should contact us filling this form or by writing to We’ll be glad to explain some of our recent projects that have benefited customers in Oil & Gas industry.

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How Fatigue Made Me Fall From The Chair?

This article explains the setup of a simple fatigue analysis in ANSYS Workbench using an example. For beginners, this article demystifies fatigue analysis.


When I was ten years old, I was fond of a chair which was small and easily movable. After school, I used to sit on it and watch Aladdin tales on the television. One day, as usual, I sat on it. Suddenly the chair got broke in half and I fell on the floor in front of my sister. For obvious reasons, I got embarrassed and my sister made fun of me the whole day. I slept that day with few unanswered questions.

Why did the chair fail when it was working fine for a few years? Why didn’t it fail on the first day I sat on it?

Illustration of a broken chair as a result of fatigue
My broken chair! 🙁

Fast forward to my engineering days, I was told that cyclic loading on any structure can make that structure fail – fatigue failure. Only then I could understand why my beloved chair failed.

Many of you might have heard stories like the one mentioned above or even experienced it yourself. However, the fact that majority of structures irrespective of their size experience a phenomenon like fatigue is real. If a simple structure with a simple load cycle could fail because of fatigue, imagine a complex structure with a complex loading cycle. Yes, the consequences are catastrophic for the manufacturer as well as the user.

According to NBS report, “between 80-90 % of all structural failures occur through a fatigue mechanism.” Incorporating fatigue simulation upfront into the product development cycle plays a vital role in optimizing the structural integrity of your product and it significantly reduces the cost of failure.

In this article, a simple fatigue analysis is shown which was carried out using ANSYS Fatigue Tool. If you wish to conduct the analysis as per FKM guidelines, you’ll be interested this CADFEM ANSYS Extension.


For a fatigue analysis, static structural or transient analysis is a prerequisite. To achieve this, I consider a simple chair geometry for static structural analysis; appropriate loads and boundary conditions were defined. I define a point mass of 75 kg to act on the chair. This loading can be considered as a misuse for a child’s chair. Resultant static stress (24 MPa) did not exceed the yield strength (54 MPa) of the assigned material.

There! I got the answer to one of the questions from my story. The chair didn’t fail on the first day I sat on it because the load applied on the first day was not sufficient enough to exceed the yield strength of the material.

Analysis setup for fatigue study
Loads and Boundary Conditions
Results of static structural analysis before fatigue analysis
Equivalent von-Mises Stress








Setting up the analysis

Subsequent to the setup of static structural analysis, I launch the ANSYS Fatigue Tool using the following steps.

Setting up fatigue analysis
Solution>Insert>Fatigue>Fatigue tool

Analysis Type

ANSYS Fatigue Tool offers two methods to calculate fatigue life.

  • Strain Life
  • Stress Life

While strain life approach is widely used, at present, because of its ability to characterize low cycle fatigue (<100,000 cycles), stress life approach addresses high cycle fatigue (>100,000 cycles).

Specifying details in the fatigue tool
Details View of Fatigue tool

I chose the stress life approach to execute this example and subsequently I defined the appropriate S-N (Stress–Cycles) curve in the engineering data.

Loading Type

Contrary to static stress, fatigue damage occurs when stress at a point changes over time. Therefore, it is essential to define the way the load could repeat after a single cycle, in other words the type of fatigue loading determines how the load repeats over time.

Accordingly, I chose zero-based loading type for the current example, which means I apply the load and remove it, thereby resulting in an equivalent load ratio of 0. For a fully-reversed loading, I would apply a load and then apply an equal and opposite load which will result into a load ratio of -1.

Applying zero-based loading in fatigue analysis
Zero-Based loading

In both the cases the amplitude of load remains constant. Therefore looking at the single set of simulation results will give you an idea where fatigue failure might occur.

Mean Stress Theory

Now that I have defined analysis and loading types, I need to choose a mean stress theory.

Zero Mean Stress loading for fatigue analysis
Zero Mean Stress loading

Mean stress is the average of maximum and minimum stress during the fatigue load cycle. Mostly, fatigue data is assumed for zero mean stress, which means fully reversed loading. However, fully reversed loading conditions (zero mean stress) are rarely met in engineering practice. Hence Mean Stress Correction Theory has to be chosen to account for mean stress.

For stress life approach: If experimental data at different mean stresses exist, I can account for the mean stress directly by interpolating different material curves. However, it is unlikely to have experimental data at all mean stresses. Therefore, several empirical relations are available including Goodman, Soderberg and Gerber theories which use static material properties (yield strength and tensile strength) and S-N data to account for mean stress. In general, I don’t advise you to use empirical relations if multiple mean stress data (S-N curves) exists.

Different Mean Stress Theories for Fatigue Analysis
Different mean stress correction theories (Goodman Theory is highlighted)

Goodman Mean Stress Theory is a common choice for plastic materials, whereas Gerber Theory is a common choice for ductile metals. For the current analysis, I chose the Goodman Theory.

Fatigue Life

Like any other result in ANSYS Workbench, fatigue life can be scoped on a geometric entity. For stress life with constant amplitude loading, life at that point will be used if the equivalent alternating stress is lower than the lowest alternating stress defined in the S-N curve

For this example, 3,100,000 cycles is the expected life of the chair. This means that a person of 75 kg can sit on this child’s chair for 3.1 million times. If he ignores and continues to sit beyond the expected life, very soon he might face the same fate as the boy in the story.

Fatigue life extracted from ANSYS Fatigue Module
Fatigue life extracted from ANSYS Fatigue Tool

Wasn’t it easy? Yes, it is easy to perform this analysis provided you have the material data. In case you are not aware, ANSYS Mechanical Pro, Premium, Enterprise and ANSYS AIM offer ANSYS Fatigue Tool.

What are you waiting for? Start realizing your product promise using ANSYS products.

P.S. Just in case you were wondering what happened after the chair broke, my mother bought us a brand new chair the next day!

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Structural Analysis – ANSYS 18 Innovations

ANSYS Release 18 is packed with lot of innovative features for structural analysis. This article summarizes the various advancements in the new release.

ANSYS 18 enables users like you and me to meet customer demands to develop lighter, stronger, and more efficient products. The new release has new tools and technologies to analyze complex materials, optimizing designs and shapes for new manufacturing methods and ensuring structural reliability of electrical components.

With the new parallel Topology Optimization technology, you can perform lightweighting of structures, easily extract CAD shapes and quickly verify the optimized designs. You can easily simulate spatially-dependent materials like composite parts, 3D printed components, and bones and tissues for more accurate results. The new spectral fatigue capability enables you to accurately model vias and calculate product life to better measure the reliability of electronic components. The addition of a new concrete material law, along with the ability to easily define reinforced structures, makes it easy to model complex structures in the civil engineering and nuclear application areas.

In summary, ANSYS Mechanical has brought in much awaited enhancements which were long overdue for users performing structural analysis. Therefore the new release revolutionizes problem handling and solving capabilities across various industrial domains. Here are the highlights.

Easier and Faster Usage
  • There are enhancements in sorting and filtering options, hotkeys and selection utilities leading to effective utilization of ANSYS Mechanical
  • You will find advancements in contact formulation and detection capabilities that lead to faster convergence
Image of a coupling element while performing structural analysis
Ease of Use in ANSYS 18
Advanced Material Modeling

ANSYS has introduced improvement to existing material models in order to help accurately simulate complex plasticity.

Enhancements for Dynamics

Developments in rotor-dynamics and performance improvements in CMS will lead to reduction of computational time while performing structural analysis.

Image of a turbomachinery component with results after structural analysis
Advancements in Rotordynamics
Additive Manufacturing Technologies

The introduction of advanced options for topology optimization is another significant enhancement that will help manufacturing sector with material savings.

Mechanical Reliability of Electronics

Lastly the enhanced coupling between Electronic and Mechanical helps to model Thermo-Mechanical effects in intricate and minute electronic components better.

Besides the above advancements, ANSYS 18 offers many avenues for users to realize their product promise! If you’re interested to learn more about ANSYS 18 innovations for structural analysis, then join our webinar on March 24. There’s a lot to learn!

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3 Benefits of ANSYS SpaceClaim for 3D Printing

In this article, I will describe 3 benefits of ANSYS SpaceClaim Direct Modeler for 3D Printing and other applications. Specifically I will focus my attention on the Facet Tool in this article.

While searching for freely-available CAD models on, I chanced upon the challenges section because it piqued my interest. To my surprise, I found about 75% of the recent challenges to be related to topology optimization. For most of these challenges, lightweighting will yield a final design output that is optimum in weight. However such an output will be complex for traditional manufacturing processes. In the recent years, additive manufacturing or, often referred to as, 3D printing has appeared to be the manufacturing process of choice for several contemporary applications.

For topology optimization, ANSYS is the simulation tool of choice. In the latest Release 18, a significant thrust was provided to this topic. The technology is very powerful and highly-effective for lightweighting the designs. Typically, topology optimization results in the design in STL file format. In my experience, this design output is often fraught with poor facet quality and this requires cleanup by a competent tool.

Typical STL File Output of a Bracket after Topology Optimization towards 3D Printing
Typical STL File Output of a Bracket after Topology Optimization

The full suite of ANSYS Simulation Software offers not just solvers for multiple physics, but also several value added tools such as ANSYS SpaceClaim Direct Modeler (SCDM). This tool allows product companies to launch their offerings faster to market.

Now SCDM has several useful features that allow geometry manipulation and clean-up. Among many features, I found the Facet Tool to be extremely useful. After completion of topology optimization, the STL file output from ANSYS is imported into SCDM.  This Facet Tool helps in cleaning up the STL file output containing poor facet quality and helps me prepare the design for validation using ANSYS Mechanical.

For better understanding, I have included the typical workflow below.

Workflow for Topology Optimization for 3D Printing
Workflow for Topology Optimization

With this context in place, I will now introduce you to the 3 significant benefits of using ANSYS SpaceClaim Direct Modeler for 3D Printing applications.

HIPP Add-In for Reverse Engineering

HIPP is an SCDM add-in developed by This tool is quite useful for engineers performing reverse engineering – with the eventual goal of producing the desired part using 3D Printing. For this case, the approach typically starts with scanning of the part desired for reverse engineering. The scan results in an STL file format created directly in SCDM; this automatic scan to STL is powered by the HIPP add-in. The Facet Tool in SCDM is then used to repair and prepare a watertight geometry.

Here’s an example of the scanned geometry of top profile of a piston rod that was generated in SCDM using the HIPP add-in. The facets in this geometry did not capture the profile accurately. Furthermore the geometry has undesired holes along with unwanted parts.

Image of a scanned geometry of a part in SCDM (using HIPP Add-In) for 3D Printing
Scanned geometry of a part in SCDM (using HIPP Add-In)

Using the Facet Tool, the repaired geometry is now ready for topology optimization and design validation before producing it using 3D Printing.

Image of the modified geometry in SCDM using Facet Tool for 3D Printing
Modified geometry in SCDM using Facet Tool
Save Resources – Faster to Market

There are numerous software tools for STL preparation, however SCDM Facet Tool has many value-adding, additional capabilities. With a very little investment, the Facet Tool provides a strong hold in combining multiple solid parts with faceted geometries in a user-friendly manner; this feature has several advantageous implications for 3D printing. Furthermore the tool is very easy and requires little knowledge for geometry repair and preparation. To prepare the bracket geometry (illustrated at the beginning of the article), it took me 10-15 minutes. See the below image. Now I found it to be fairly quick when compared to 2-3 times more using other facet modeling tools.

Image of bracket geometry modified after using SCDM Facet Tool for 3D Printing
Bracket geometry modified after using SCDM Facet Tool
Preventing Failures in 3D Printing

The Facet Tool has features to detect thickness and overhang problems before the model is sent for 3D Printing. Now these overhangs present a challenge to 3D printing without using support material. Problems such as these can be prevented by few techniques like tear-dropping, tapering among others. The effects of overhang cannot be judged immediately until you are a 3D Printing professional.

Facet Tool has a feature which detects the overhangs by providing parameters specific to 3D Printing. In particular, the thickness feature detects all geometry that is thinner than the minimum thickness specified by the printer OEM. In addition, I could understand thickness and overhangs-related problems beforehand by providing the direction of printing as well.

Other Applications

This topic is also of CADFEM’s particular interest because we invest into Digital Cities – a strategic initiative of CADFEM International that aims to simulate cities of our future. This topic is quite special and important since it involves studying the effects of disaster scenarios such as earthquake, tsunamis, pollution, crowd behavior among others.

virtualcitySYSTEMS, a CADFEM International group company, develops 3D city models using scanned data of terrains. For these city models, we use the Facet Tool to repair the geometry before performing urban simulations.

In future posts, I will delve further into using CFD and particle simulations for better modeling of 3D Printing applications.

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Debugging Convergence for Large Sliding Problems

This is the first part in a series of posts related to debugging convergence. This post talks about large sliding problems in particular.

Sliding contact is an imperative characteristic defining the functionality of many products. In this article, I aim to help in debugging convergence issues while modeling and simulating large sliding contact problems in ANSYS Mechanical.

A conventional practice for modeling contacts in a simulation environment tends to accommodate slight inter-penetration of mating parts in order to allow the solution to converge. Inter-penetration can pose serious concerns in the form of under prediction of force reactions and stresses for a sliding contact scenario. The lack of solution accuracy is in the name of solution convergence. In order to derive a reasonably accurate solution for a sliding contact scenario, we should strive to regulate contact penetration to a bare minimum.

Two Approaches to Sliding Contact Problems

Let’s get into the nitty-gritty of solving sliding contact problems. Now ANSYS Mechanical’s settings for penalty-based methods (Pure Penalty and Augmented Lagrange) allow for some penetration (depends upon contact stiffness) leading to easier convergence. Results are not accurate with the penalty-based method. Despite this, many chose to use this approach in order to achieve solution convergence.

Normal Lagrange formulation guarantees almost zero penetration, with good solution accuracy, because there is no contact stiffness in the normal direction. Instead, the method uses some additional contact degrees of freedom i.e. contact pressure acting normal to contacting surface in order to prevent penetration and a tangential contact stiffness based on penalty method.

So the Normal Lagrange formulation can handle large frictional sliding problems more effectively. It is not suited for sticking application, i.e. valid only for frictional/friction-less contacts. Conversely, this method can be used where penetration is undesirable – as in applications such as snap fit, gears & other sensitive applications where penetration leads to less accuracy in the results.

However Normal Lagrange formulation is not the proverbial knight in shining armor for these applications.

Solution has not converged after 12 iterations for contact status change!

Screenshot of ANSYS Mechanical solver output highlighting the lack of change of contact status. This image is used in support of the article on Normal Lagrange formulation

Achieving Solution Convergence with Normal Lagrange Formulation

While working with the Normal Lagrange formulation, many of you would have faced this challenge. In addition to it be very frustrating, the time consumed to achieve solution convergence reduces our engineering productivity.

Typically when we activate Normal Lagrange formulation, the ANSYS solver, by default, bisects at the 12th iteration due to contact status change even though the force convergence trend is good. The figure below illustrates this. If the bisection were not to happen, the solution were likely to converge in the next iterations.

Screenshot of a delayed solution convergence with Normal Lagrange formulation.

Can we increase this bisection limit? Yes! This, little known, undocumented key is available with the CUTCONTROL command.


In ANSYS Workbench, this command can be inserted in the tree under analysis system as shown in the below image.

Screenshot of ANSYS Workbench demonstrating the location to add the APDL command. This image is used in support of the article on Normal Lagrange formulation.

Seen below is the force convergence behavior of a demo case study with and without using the CUTCONTROL command.

Image of force convergence behavior of a test case shown using a plot without CUTCONTROL command in support of the article on Normal Lagrange formulation.
Without CUTCONTROL command
Image of force convergence behavior of a test case shown using a plot with CUTCONTROL command in support of the article on Normal Lagrange formulation
With CUTCONTROL command

Generally, in industry, there is a misconception that Normal Lagrange is not preferable for achieving convergence in many cases. As demonstrated, this contact formulation is best suited for large sliding problems which is both, accurate and faster.

If you encounter problems with large sliding contacts, please do try my suggestion and let me know your feedback. If you have a better solution in mind, please do share in the comments section.

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