DFIT Interpretation
/ Chapter 1 - Introduction

# Lesson 1.01 Course Outline - What is a DFIT?

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- 1.01 Course Outline - What is a DFIT? (16 min.) Sample Lesson
- 1.02 Hydraulic Fracturing for Stress Estimation (17 min.)
- 1.03 Permeability, Pore Pressure & Plotting Data (17 min.)

- 2.01 Wellbore Storage & Near-wellbore Tortuosity (14 min.)
- 2.02 Nolte (1979) Concept (20 min.)
- 2.03 Joint Closure & Nonlinear Stiffness (18 min.)

- 3.01 Example DFITs (19 min.)
- 3.02 EGS Colab Project Example (14 min.)

- 4.01 Pore Pressure Estimation (17 min.)
- 4.02 Practicality - Worked Examples (18 min.)
- 4.03 Relative Stiffness & Permeability Estimates (19 min.)

- 5.01 Practical Tips (14 min.)

DFIT Interpretation
/ Chapter 1 - Introduction

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01. Lesson 1.01: Course Outline - What is a DFIT?02. URTeC-2019-12303. Course Outline04. What is a DFIT?05. Typical Test Sequence06. References for the URTeC-2019-123 procedure07. Recent papers relevant to the URTeC-2019-123 procedure08. Relationship with well test analysis09. References on conventional well testing10. References on rock mechanics and fracture mechanics11. What is new/different about the URTeC-2019-123 procedure?

Hi, my name is Mark McClure and welcome to this course on the DFIT Interpretation procedure from the paper URTeC-2019-123.

This paper was written in 2019 based on an industry study that was performed by a consortium of 7 companies. The idea was to integrate modeling, analytical results, field data, and a group of experts and practitioners to develop a DFIT interpretation procedure. In some ways, it builds upon existing techniques and is very similar or incremental on those. In a handful of other situations, it's substantially different. And when I get to those points, I will point them out and explain why they are different.

So here's a course outline. This first lecture is on a general introduction to diagnostic fracture injection testing and this overall course. Then the next lecture will be on what I'm calling the ideal "S" shaped dP/dG curve. We're going to step through a standard diagnostic plot and explain what's happening and why at different points in the dataset. Then we'll talk specifically about how to estimate stress. The 4th will be on estimating pore pressure as well as estimating permeability. And then the final lecture in this course is relatively short and it provides some practical tips.

I do want to mention something that's very important. Everything I'm really going to refer to today and in this course, throughout the course, it's based on interpreting DFIT tests performed in relatively low-permeability formations. So, in high-permeability formations, the fracture closes very quickly, the fracture quickly ceases to be infinite conductivity after closure, and that leads to a fundamentally different physics and qualitatively different looking transients and the interpretation is somewhat different. And so this entire course is based on really tens of microdarcies on down and that's what this procedure is really built for.

I do want to mention something that's very important. Everything I'm really going to refer to today and in this course, throughout the course, it's based on interpreting DFIT tests performed in relatively low-permeability formations. So, in high-permeability formations, the fracture closes very quickly, the fracture quickly ceases to be infinite conductivity after closure, and that leads to a fundamentally different physics and qualitatively different looking transients and the interpretation is somewhat different. And so this entire course is based on really tens of microdarcies on down and that's what this procedure is really built for.

So let me start by defining what is a DFIT. It's an acronym that stands for Diagnostic Fracture Injection Test. This is a small volume injection test that creates a hydraulic fracture. Then we shut in and pressure is monitored to estimate pressure (pore pressure), stress, and potentially permeability.

This is a typical test sequence. This is somewhat idealized from real data. But at the beginning, when you start injecting, a hydraulic fracture has not yet formed. Assuming we're in a very low-permeability formation, the injection rate is much higher than the ability of the formation to accept injection and so we see pressure build up. And that pressure buildup is caused by wellbore storage, which is mostly from the compressibility of the fluid, which is water in the wellbore. When the hydraulic fracture forms, we'll see a leakoff point and/or a breakdown where there may or may not be a peak in pressure. But what's certainly going to happen is pressure is going to flatten out over time. And that's because a hydraulic fracture is formed and now fluid is flowing into that hydraulic fracture. That's at the fracture propagation pressure, which does not have to be constant. You can see that trending upwards or downward during injection. Then we shut in. There's a rapid drop in pressure at shut-in caused by a reduction in wellbore storage. Then a transient begins. That transient is really what we're going to analyze in this course as part of DFIT interpretation. And at some time later, we'll see the fracture close and there are potentially after closure pressure transients that we can interpret.

So let me go ahead and show a movie of this process. So this is a numerical simulation. It's a combined hydraulic fracture reservoir simulator and it's also a wellbore simulator, so that's going to allow us to really capture this full sequence of events; the wellbore storage, the fracture initiation and propagation, the fracture closure, and then fluid leakoff and kind of gradual spreading of fluid pressure over the long period of time.

So in the top right, we see pressure. In the bottom right, we see aperture. In the top left, this is a plot of wellhead pressure vs. time and rate vs. time. This is only for the first roughly 17, 18 minutes of the test. And then the shut-in, of course, goes on much longer. And in the bottom left here, we have a standard diagnostic plot called the G-function plot. We'll talk more about it later. So we don't need to kind of explain what that plot is showing right now, but we're just going to go ahead and show the movie. So here we're injecting. This crack is forming. And then when we shut in, we see the aperture falling back off, going to blue. And then at very late time, pressure is starting to spread out gradually, linearly, elliptically, and then potentially at late time, radially away from this hydraulic fracture. So I'll show the movie one more time and we can see here, this blue dot is showing how we're progressing in time. Here we've shut in, pressure is falling off, and we then can see the progression of the pressure transient down that diagnostic plot as these events occur.

So in the top right, we see pressure. In the bottom right, we see aperture. In the top left, this is a plot of wellhead pressure vs. time and rate vs. time. This is only for the first roughly 17, 18 minutes of the test. And then the shut-in, of course, goes on much longer. And in the bottom left here, we have a standard diagnostic plot called the G-function plot. We'll talk more about it later. So we don't need to kind of explain what that plot is showing right now, but we're just going to go ahead and show the movie. So here we're injecting. This crack is forming. And then when we shut in, we see the aperture falling back off, going to blue. And then at very late time, pressure is starting to spread out gradually, linearly, elliptically, and then potentially at late time, radially away from this hydraulic fracture. So I'll show the movie one more time and we can see here, this blue dot is showing how we're progressing in time. Here we've shut in, pressure is falling off, and we then can see the progression of the pressure transient down that diagnostic plot as these events occur.

One paper I like by Cramer and Nguyen (2013). Dave Cramer is one of the co-authors on the URTeC procedure. This paper was written before we developed that procedure, so there are some differences between that paper and the new procedure, but it still has a lot of really valuable information. And here he has a kind of nice narrative of the process of performing a DFIT. I won't read through it, but I recommend that you refer to this and read through this a little bit.

Other background references. So I want to refer to some of the key papers in the literature and references in the literature that I recommend and that really much of which is drawn upon in the DFIT 2019-123 procedure.

So the first paper to be aware of is the paper from 1979 by Ken Nolte, "Determination of fracture parameters from fracturing pressure decline". This is the paper where they released the G-function concept and it really is the foundation of much of the DFIT interpretation that we still do today.

If you want a nice paper or rather a nice reference on the math and the underlying concepts that Nolte developed, I really like Chapter 9 from this textbook "Reservoir Stimulation". That's written by Nolte as well as Gulrajani and they have a very nice mathematical description of how all the pieces fit together from the procedure that Nolte developed.

Now, there are 2 other references that our 2019-123 procedure draws on. One of them is a reference by Valko and Economides, "Fluid-leakoff delineation in high-permeability fracturing". And I'll talk later about how we're using that reference and why. But what I really liked about this reference is they showed how we can create a fast and efficient and practical way to quickly estimate key fracturing parameters. And we'll talk about it more later.

The second paper that I think that we're drawing on significantly, this paper by Mayerhofer, Ehlig-Economides, and Economides in 1995, "Pressure transient analysis of fracture calibration tests". They extended Nolte's techniques to account for changing pressure over time. And we're also going to draw on that sort of approach in this procedure.

So, I refer you guys to these papers as being important historically and also if you want a good mathematical description to check out this Chapter 9.

So the first paper to be aware of is the paper from 1979 by Ken Nolte, "Determination of fracture parameters from fracturing pressure decline". This is the paper where they released the G-function concept and it really is the foundation of much of the DFIT interpretation that we still do today.

If you want a nice paper or rather a nice reference on the math and the underlying concepts that Nolte developed, I really like Chapter 9 from this textbook "Reservoir Stimulation". That's written by Nolte as well as Gulrajani and they have a very nice mathematical description of how all the pieces fit together from the procedure that Nolte developed.

Now, there are 2 other references that our 2019-123 procedure draws on. One of them is a reference by Valko and Economides, "Fluid-leakoff delineation in high-permeability fracturing". And I'll talk later about how we're using that reference and why. But what I really liked about this reference is they showed how we can create a fast and efficient and practical way to quickly estimate key fracturing parameters. And we'll talk about it more later.

The second paper that I think that we're drawing on significantly, this paper by Mayerhofer, Ehlig-Economides, and Economides in 1995, "Pressure transient analysis of fracture calibration tests". They extended Nolte's techniques to account for changing pressure over time. And we're also going to draw on that sort of approach in this procedure.

So, I refer you guys to these papers as being important historically and also if you want a good mathematical description to check out this Chapter 9.

Now, there's also a lot of recent papers that have bearing on this procedure and this discussion, starting with this paper down here, "The fracture-compliance method for picking closure pressure from diagnostic fracture-injection tests". That was a paper that I wrote when I was at the University of Texas with Dr. Mukul Sharma, Hojung Jung, and Dave Cramer. We talked through the mathematics of some new concepts on how to estimate stress from the DFITs. We made some predictions based on analytical developments and numerical methods, and those predictions have been borne out by subsequent data that's been collected in the field.

So for example, this paper here, Guglielmi et al, they actually have direct physical measurements of fractures opening and closing in-situ in the earth and they can be compared with the stress estimates from the G-function plots.

Similar study was performed by Dutler et al in the Grimsel test site in Switzerland.

And then another key reference here would be Bröker and Ma that also did a comparison of methods in the last few years. So this was a numerical modeling, a mathematical derivation that made certain predictions. And it's pretty cool to see the physics working and field data being collected to validate the predictions.

A few other relevant papers here, Wang and Sharma had a follow-up paper here on estimating permeability. It's also going to be a paper that's related to what we're going to call the H-function method. So later on, when we talk about permeability estimation, we're drawing on concepts that are in this paper, also related to the Mayerhofer paper.

And then two others. One of these is a paper that Garrett Fowler and I wrote with Craig Cipolla on the Utica frac optimization case study in well spacing optimization paper. And we showed how the permeability estimate from a DFIT has major impact on decisions that people make in the field with substantial economic implications. And specifically, the permeability estimate that you use is basically that you can match production data in shale with a wide range of permeabilities, but they will lead to different estimates for effective fracture length and then different estimates for what's the optimal well spacing. So we showed how this all fits together and why it's so important to be really cautious about measuring permeability, estimating it correctly, validating estimates of effective fracture length in order to really space your wells correctly and optimally.

And then finally, this paper here that just came out a few months ago, "Best practices in DFIT interpretation: comparative analysis of 62 DFITs from nine different shale plays". This is where we went back and we reviewed 10 different companies who we had done DFIT interpretations for. We asked if we could basically anonymously summarize all the results together and give a statistical review of what it looks like when people do DFITs and I'll refer to this paper throughout the course.

So for example, this paper here, Guglielmi et al, they actually have direct physical measurements of fractures opening and closing in-situ in the earth and they can be compared with the stress estimates from the G-function plots.

Similar study was performed by Dutler et al in the Grimsel test site in Switzerland.

And then another key reference here would be Bröker and Ma that also did a comparison of methods in the last few years. So this was a numerical modeling, a mathematical derivation that made certain predictions. And it's pretty cool to see the physics working and field data being collected to validate the predictions.

A few other relevant papers here, Wang and Sharma had a follow-up paper here on estimating permeability. It's also going to be a paper that's related to what we're going to call the H-function method. So later on, when we talk about permeability estimation, we're drawing on concepts that are in this paper, also related to the Mayerhofer paper.

And then two others. One of these is a paper that Garrett Fowler and I wrote with Craig Cipolla on the Utica frac optimization case study in well spacing optimization paper. And we showed how the permeability estimate from a DFIT has major impact on decisions that people make in the field with substantial economic implications. And specifically, the permeability estimate that you use is basically that you can match production data in shale with a wide range of permeabilities, but they will lead to different estimates for effective fracture length and then different estimates for what's the optimal well spacing. So we showed how this all fits together and why it's so important to be really cautious about measuring permeability, estimating it correctly, validating estimates of effective fracture length in order to really space your wells correctly and optimally.

And then finally, this paper here that just came out a few months ago, "Best practices in DFIT interpretation: comparative analysis of 62 DFITs from nine different shale plays". This is where we went back and we reviewed 10 different companies who we had done DFIT interpretations for. We asked if we could basically anonymously summarize all the results together and give a statistical review of what it looks like when people do DFITs and I'll refer to this paper throughout the course.

Next, what about the conventional well test analysis? So, conventional well test analysis, the big difference is there's no hydraulic fracture. Or if there is a hydraulic fracture, you don't create it during the well test, right. So a drawdown test is just producing fluid from a vertical well in a conventional reservoir. You can do a drawdown test or a buildup test or any other fall-off test in a conventional well test analysis, but in those types of tests, if there is a hydraulic fracture, it's assumed to be static and not opening or closing or propagating. In a DFIT, we make a new fracture or we theoretically could be reopening an existing fracture. And the reopening and closure or fractures, this creates highly nonlinear and very large changes in the system storage coefficient, in the conductivity of the fractures, and also the fracture itself can change in size so even the geometry of the problem changes. These nonlinearities have no analog in conventional well test analysis. And this is important to point out because it's very tempting to take equations or concepts from conventional well test analysis and apply them directly to DFIT analysis. And there are certainly similarities. These are cousins. But there are key situations where well test analysis equations and concepts will lead you astray in DFIT analysis. And this is very important to keep in mind. And so you've got to be very careful. You can't assume that what you know from your conventional well test course is applicable. It's harder than learning a new topic because you're learning a similar topic and sometimes the things you know aren't true in DFIT analysis. So, it's very important to just keep in mind. So here I have a log-log plot. This is the same type of plot we'd make for a conventional well test. We're going to use that same type of plot but we have to keep in mind that there are key differences.

And so for reference on conventional well testing, if you're interested in even kind of going back further and get a good understanding of that concept, here's 4 textbooks that I recommend. All 4 of these I used to use in my well test analysis course at the University of Texas.

Finally, I want to mentioned some references on rock mechanics, because I think that some of the new ideas that we put into that URTeC-2019-123 procedure, we're really just taking mainstream rock mechanics concepts and bringing them into petroleum engineering where they really weren't being used. And so a couple of key references, this textbook "Fundamentals of Rock Mechanics" by Jaeger, Cook, and Zimmerman. A book that I absolutely love. But especially refer to Chapter 12 that talks about the hydro-mechanical behavior of fractures in rock and really brings in some really strong rock mechanics concepts that are used in this DFIT interpretation procedure.

A couple of others. Barton, Bandis, and Bakhtar, "Strength, deformation and conductivity coupling of rock joints". This is a classic paper from 1985. They did a huge amount of laboratory work with many, many different types of rock, measuring the stiffness of cracks. So, when cracks form, you put them back together again, squeeze on them, how much aperture they retain? What's that relationship between stress, pressure, and conductivity and aperture and fluid storage? This is really a key reference that we still use today.

And a more recent example, Vogler et al (2018). They also have really nice work on this topic of fracture closure and reopening, the roughness of fractures and how does that turn into conductivity and fluid flow? That's why I recommend that paper as well.

A couple of others. Barton, Bandis, and Bakhtar, "Strength, deformation and conductivity coupling of rock joints". This is a classic paper from 1985. They did a huge amount of laboratory work with many, many different types of rock, measuring the stiffness of cracks. So, when cracks form, you put them back together again, squeeze on them, how much aperture they retain? What's that relationship between stress, pressure, and conductivity and aperture and fluid storage? This is really a key reference that we still use today.

And a more recent example, Vogler et al (2018). They also have really nice work on this topic of fracture closure and reopening, the roughness of fractures and how does that turn into conductivity and fluid flow? That's why I recommend that paper as well.

So, what's new and different about this URTeC-2019-123 paper? If you already think you know how to do DFIT interpretation, is this course just a review of what you already know? And in some cases, yes, it will be a reveiw of what you already know. But there are a few really sharp differences from past or other procedures.

#1, as I've mentioned, both mathematical theory and now in-situ measurements suggest that the cotangent method of estimating stress that was advocated by Barree et al. 2009, that technique is systematically too low. Now, I'll talk about it later. Sometimes that procedure and the procedure in the URTeC paper will get very similar answers or they'll be within 100 psi. I think that the uncertainty of a stress measurement from a DFIT is certainly within 100 psi. And so, in cases like that where the methods are similar, maybe this doesn't make a big difference. But particularly in formations where the fluid pressure is much lower than stress, so the bigger the difference between stress and pore pressure, the bigger the difference between the Barree et al. 2009 method and this URTeC procedure. And I'll share some statistics on differences. Sometimes they're as large as 1,000 psi or more. So, sometimes it doesn't make a big difference, sometimes it does make a pretty substantial difference.

Secondly, we identify a few permeability estimation procedures that have been used in industry that can be quite inaccurate. And again, there's an equation from the Barree et al reference where it's generally between 10 - 1,000x too high on permeability. And this affects some key aspects of how people develop shale resources.

And I'll mention one more. There are certain qualitative G-function plot interpretations. People look at a G-function plot and they say, oh, that's transverse storage or height session. And really, that's not recommended anymore. And some of those procedures, rather, some of those interpretations appear to be misinterpretations of what's really happening.

All right, so when I get to a point where I'm diverging from kind of what you might already know or what you've already gotten from a DFIT interpretation procedure, I'll pause and explain how this procedure is different and why.

McClure, M., 2019. A collaborative study on DFIT interpretation: Integrating modeling, field data, and analytical techniques.Cramer, D., 2013. Diagnostic fracture injection testing tactics in unconventional reservoirs.Nolte, K., 1979. Determination of fracture parameters from fracturing pressure decline.Economides, M., 1989. Reservoir stimulation.Economides, M., 1999. Fluid-leakoff delineation in high-permeability fracturing.Mayerhofer, M., 1995. Pressure transient analysis of fracture calibration tests.McClure, M., 2016. The fracture-compliance method for picking closure pressure from diagnostic fracture-injection tests.Bröker, K., 2021. Estimating the least principal stress in a granitic rock mass: systematic mini-frac tests and elaborated pressure transient analysis.Fowler, G., 2019. A Utica case study: The impact of permeability estimates on history Matching, fracture length, and well spacing.Dutler, N., 2020. Hydromechanical insight of fracture opening and closure during in-situ hydraulic fracturing in crystalline rock.Wang, H., 2019. A novel approach for estimating formation permeability and revisiting after-closure analysis of diagnostic fracture-injection tests.McClure, M., 2022. Best practices in DFIT interpretation: comparative analysis of 62 DFITs from nine different shale plays.Guglielmi, Y., 2022. Estimating Stress from Fracture Injection Tests: Comparing Pressure Transient Interpretations with In-Situ Strain Measurements. Horne, R., 1995. Modern well test analysis.Stewart, G., 2011. Well test design & analysis.Kamal, M., 2009. Transient Well Testing.Spivey, J., 2013. Applied well test interpretation.Jaeger, J., 2009. Fundamentals of rock mechanics.Barton, N., 1985. Strength, deformation and conductivity coupling of rock joints.Vogler, D., 2018. Experiments and simulations of fully hydro‐mechanically coupled response of rough fractures exposed to high‐pressure fluid injection.Barree, R., 2009. Holistic fracture diagnostics: consistent interpretation of prefrac injection tests using multiple analysis methods.

#1, as I've mentioned, both mathematical theory and now in-situ measurements suggest that the cotangent method of estimating stress that was advocated by Barree et al. 2009, that technique is systematically too low. Now, I'll talk about it later. Sometimes that procedure and the procedure in the URTeC paper will get very similar answers or they'll be within 100 psi. I think that the uncertainty of a stress measurement from a DFIT is certainly within 100 psi. And so, in cases like that where the methods are similar, maybe this doesn't make a big difference. But particularly in formations where the fluid pressure is much lower than stress, so the bigger the difference between stress and pore pressure, the bigger the difference between the Barree et al. 2009 method and this URTeC procedure. And I'll share some statistics on differences. Sometimes they're as large as 1,000 psi or more. So, sometimes it doesn't make a big difference, sometimes it does make a pretty substantial difference.

Secondly, we identify a few permeability estimation procedures that have been used in industry that can be quite inaccurate. And again, there's an equation from the Barree et al reference where it's generally between 10 - 1,000x too high on permeability. And this affects some key aspects of how people develop shale resources.

And I'll mention one more. There are certain qualitative G-function plot interpretations. People look at a G-function plot and they say, oh, that's transverse storage or height session. And really, that's not recommended anymore. And some of those procedures, rather, some of those interpretations appear to be misinterpretations of what's really happening.

All right, so when I get to a point where I'm diverging from kind of what you might already know or what you've already gotten from a DFIT interpretation procedure, I'll pause and explain how this procedure is different and why.

McClure, M., 2019. A collaborative study on DFIT interpretation: Integrating modeling, field data, and analytical techniques.Cramer, D., 2013. Diagnostic fracture injection testing tactics in unconventional reservoirs.Nolte, K., 1979. Determination of fracture parameters from fracturing pressure decline.Economides, M., 1989. Reservoir stimulation.Economides, M., 1999. Fluid-leakoff delineation in high-permeability fracturing.Mayerhofer, M., 1995. Pressure transient analysis of fracture calibration tests.McClure, M., 2016. The fracture-compliance method for picking closure pressure from diagnostic fracture-injection tests.Bröker, K., 2021. Estimating the least principal stress in a granitic rock mass: systematic mini-frac tests and elaborated pressure transient analysis.Fowler, G., 2019. A Utica case study: The impact of permeability estimates on history Matching, fracture length, and well spacing.Dutler, N., 2020. Hydromechanical insight of fracture opening and closure during in-situ hydraulic fracturing in crystalline rock.Wang, H., 2019. A novel approach for estimating formation permeability and revisiting after-closure analysis of diagnostic fracture-injection tests.McClure, M., 2022. Best practices in DFIT interpretation: comparative analysis of 62 DFITs from nine different shale plays.Guglielmi, Y., 2022. Estimating Stress from Fracture Injection Tests: Comparing Pressure Transient Interpretations with In-Situ Strain Measurements. Horne, R., 1995. Modern well test analysis.Stewart, G., 2011. Well test design & analysis.Kamal, M., 2009. Transient Well Testing.Spivey, J., 2013. Applied well test interpretation.Jaeger, J., 2009. Fundamentals of rock mechanics.Barton, N., 1985. Strength, deformation and conductivity coupling of rock joints.Vogler, D., 2018. Experiments and simulations of fully hydro‐mechanically coupled response of rough fractures exposed to high‐pressure fluid injection.Barree, R., 2009. Holistic fracture diagnostics: consistent interpretation of prefrac injection tests using multiple analysis methods.