Pressure Dependent Permeability in Overpressured Shales. An Integrated Engineering Workflow with Fekete s F.A.S.T. TM Software

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1 page An Integrated Engineering Workflow with Fekete s F.A.S.T. TM Software. page Pressure Dependent Permeability in Overpressured Shales page 6 New Software Features for 2010 Fall 2010 Engineering & Business News from Fekete Associates Inc. An Integrated Engineering Workflow with Fekete s F.A.S.T. TM Software Lucas Ford Account Manager The integrated engineering workflow using Fekete s F.A.S.T. software is poised to become the new industry standard for reservoir and production engineering. The concept is simple and effective; each interpretation by various software applications should not be seen as independent compartmentalized stories, but rather chapters all contributing to a more complete interpretation. Improvement in Reserves by Performing Integrated Assets Modeling The workflow promotes efficiency while enabling engineers to get the most information possible from the available data. Better analysis methods and a streamlined workflow help us to achieve more informed decisions in less time. Fekete developed the integrated workflow from an actual study using real-life data. The results of the initial workflow project are said to have been the largest profit generating project for this client in Based on this, a presentation was developed which guides our clients through multiple scenarios. It touches on all Fekete F.A.S.T. software and illustrates how each contributes key pieces of knowledge to the overall story. The recent shift towards unconventional reserves as well as fluctuations in the oil and gas commodity prices have made it even more important to fully utilize all available resources. Effective use of engineering time and optimization of reserves have become necessary for every size company to remain profitable in this highly competitive market. The increase in unconventional reservoirs as a percentage of a company s portfolio leaves us with additional forecasting challenges. The effective use of Fekete s F.A.S.T. software suite helps to resolve this by introducing more engineering science into reserve forecasts. Because each company is unique, we recommend that Fekete work with your organization to fine-tune your existing workflow and ensure a proper fit. For more information or to arrange an integrated workflow presentation, please contact our sales department at or toll free within North America at Fall

2 Current Fekete Software Workflow Production Database END RESULT Group and individual well forecasts based on traditional decline methods Economic and Planning Software PalantirCASH and PalantirPLAN Merak Peep Aries Excel HARMONY forecast vs. Fekete Optimized Production Fekete Database Identify 4 wells with low RF - Focus wells CBM Wells for RTA Analysis Well 1 Identify liquid loading Tubing Optimization Project to see when / which tubing to use Feed to Piper Model (Tubing Changes) Forecast Well 2 Identify low perm with reduced access to reservoir volume Project to determine optimum well spacing & on-stream dates Feed to Piper Model (Infill Wells) Evaluate Deliverability vs. Current Production Well 3 Large OGIP from volumetrics and material balance with low rates and EUR Compare WT analysis and model to evaluate improved Xf restimulation Feed to Piper Model (restimulation) Well 4 Identify low draw-down Schedule compression to lower Pwf Improvement in Reserves by Performing Integrated Asset Management Reservoir analyzed and modeled 2

3 3 Fall 2010 Pressure Dependent Permeability in Overpressured Shales Dave Anderson Vice-President, Software In this article, we present several important findings regarding performance analysis of overpressured shales: 1. Inconsistencies observed in the analysis of production and buildup data from selected Haynesville wells provide strong evidence of a productivity index that degrades over time. Well Performance Analysis The motivation for this work arises from the need to explain the observation of inconsistencies between production and buildup data from the same well. The inconsistencies could only be resolved using a model for which well productivity degrades through time. There may be different explanations, such as increasing damage skin or influx of liquids at the wellbore, but since we are dealing with the Haynesville, it is reasonable to assume that the observed productivity loss is caused by pressure dependent permeability. When analyzing well performance data using F.A.S.T. RTA, a gradual loss in well productivity over time cannot be easily identified. Furthermore, if such a productivity loss is present, it will likely lead to incorrect (pessimistic) estimates of OGIP and EUR. Consider the example shown in Figure 1. Figure 1: Simulated Production from an Overpressured Reservoir 2. The source of the productivity loss is indeterminable using well performance analysis alone (changing kh, skin, fracture length, conductivity?). 3. Rate transient analysis, on its own, can significantly underpredict OGIP and EUR in these reservoirs. 4. If pressure buildup data is available following some production, it can provide a clear diagnostic of the inconsistency of interpretation. 5. Using analytical models that treat permeability as a pressure dependent variable, one can obtain satisfactory history matches of both production and buildup data that could not be otherwise matched using conventional static model. 6. Using these analytical models with pressure dependent permeability, one can meaningfully predict the long-term deliverability for overpressured shale gas wells. In this example, production is simulated from a Haynesville-like reservoir for a three month period, using F.A.S.T. RTA. The well is produced at restricted rates and declining flowing pressures, similar to real operating conditions observed in the Haynesville. The data are created using a model that simulates a permeability that declines exponentially with pressure (Figure 2). Figure 2: Assumed Pressure Dependent Permeability Profile Background In some gas fields, such as the Haynesville, pore pressure can be abnormally high. This creates conditions where, as production occurs through time, effective permeability may be reduced significantly because of gradual fracture closure due to compaction. This mechanism of pressure dependent permeability has been well established experimentally, through core analysis, but has proved difficult to identify from well performance analysis.

4 Yilmaz and Nur have proposed this form of permeability decline, based on experimental core analysis from tight gas wells. These data are analyzed using the Flowing Material Balance (FMB), ignoring pressure-dependent permeability (Figure 3). Figure 3: Flowing Material Balance Analysis of Simulated Data kinds of inconsistencies, in actual field cases, that have raised the red flag of productivity loss, and brought about the subsequent hypothesis of pressure dependent permeability. If we extrapolate the dotted line (static p/z), we find that the OGIP is 12 bcf, as expected. From this example, it is clear that the flowing and buildup data are both required in order to get a true sense of what is going on in the reservoir. Without it, the interpretation is incorrect. Figure 5: Flowing Material Balance Including Final Buildup Pressure and Post-Buildup Production This analysis indicates that the well is draining a limited volume (1.4 bcf). The OGIP for the model was 12 bcf, not 1.4 bcf. Clearly, this interpretation is incorrect, but if that was the only data available, 1.4 bcf would have been our conclusion. Let us consider the same example, but this time, we will include a 10-day buildup, followed by an additional one month of production (similar to a real well s production history), as shown in Figure 4. Modeling Pressure Dependent Permeability As previously stated, pressure dependent permeability can be (and has been) implemented in the analytical reservoir models. This is done by modifying the standard definitions of pseudo-pressure and pseudo-time, to include permeability, as follows: Figure 4: Simulated Production and Buildup From an Overpressured Reservoir Now, we will include the final buildup data point and post-buildup production data on the FMB plot (Figure 5). What does the graph below tell us? For one thing, it clearly shows an inconsistency (divergence) between the flowing and static pressure trends. It also suggests that the post-buildup well performance has a marked improvement in productivity. It is these How can this model be used to assist in the analysis of well performance data? Clearly, well performance analysis cannot be used to predict k(p) directly, in the same manner it is used to predict parameters such as OGIP. Rather, the process is indirect. We first identify the inconsistencies in the analysis, and then use k(p) to try to correct them. It goes without saying that the form of the k(p) function must be determined independently of the production analysis process. The function proposed by Yilmaz and Nur, as described previously appears to be one of several suitable options.

5 The series of plots (Figure 6) illustrate how the k(p) model can be used in well performance analysis. The first graph shows a model history match based on the production data only. The second shows a model match that honors the final buildup data, but misses on the production data, thereby highlighting the inconsistency. The final plot shows a history match that honors all data by including k(p) in the model. The model shown in the final plot can be used to forecast production. The resulting graph (Figure 7) shows this production forecast. For comparison purposes, a forecast from the Production Data Match model is also shown. Figure 7: Production Forecasts for Simulated Example Figure 6: History Match Plots for Various Models The diagnostic plots and models required to perform interpretation and modeling of shales with pressure dependent permeability are all currently available in the F.A.S.T. RTA software. For more information, visit us at fekete.com or contact our sales department at or toll free within North America at Dave Anderson, P. Eng., is Vice President, Software with Fekete Associates Inc. He has thirteen years of experience in the petroleum industry, including production optimization, gas deliverability modeling and well test analysis. Over the past six years, he has lead the development of Fekete's F.A.S.T. RTA software, and has become a recognized expert in the area of production analysis techniques. Dave has authored numerous papers on the subject, for which he has been awarded two Best Presented Paper awards from the Petroleum Society (both in 2005). He also received the SPE s Outstanding Young Professional award for the Rocky Mountain Region in He has lectured and presented industry courses on modern production analysis all over the world. Dave served on the SPE s Calgary Section board from 2005 to 2007 as Director for the Young Professionals Initiative and currently serves on the SPE s Reservoir Description and Dynamics committee. 5

6 New Software Features for 2010 Kevin Dunn Vice-President, Software Business Development Fekete s development team has been working on some exciting new tools and functionality that will be included in the Fall 2010 software release. By far, the most exciting of these is the multi-application environment that will initially host both F.A.S.T. RTA and F.A.S.T. Harmony. The new environment gives users the simplicity of loading input data only once, along with the convenience of a single access point for multiple software tools. During 2011 development, more Fekete applications will be integrated into this environment to make a seamless transition between most Fekete software tools. F.A.S.T. RTA has been rebuilt from the ground up and has several architecture changes that allow standard and custom workflows. A workflow is a combination of analysis techniques (in a logical order) that are appropriate for analyzing a specific reservoir type. Workflows for tight and shale gas, conventional oil and gas, and shale oil will be included. In addition to this, users also have the ability to develop their own workflows. New analytical models include horizontal with fractures and composite horizontal with fractures (as illustrated below). Inclusion of dual porosity and/or adsorbed gas (using an isotherm) is possible with any model. A new unconventional gas analysis module also links multiple analysis methods for reliable and efficient interpretation of shale gas data. This version of F.A.S.T. RTA also includes a detailed wellbore model, allowing deviated and horizontal wells, complex tubing and non-uniform temperature profiles. F.A.S.T. RTA users will also enjoy seamless access to analysis methods in F.A.S.T. Harmony. F.A.S.T. Harmony is Fekete s newest product that incorporates traditional decline analysis, volumetrics, material balance, and ratio analysis all in one software package. In addition to the integration with F.A.S.T. RTA, typecurve generating capabilities as well as material balance analysis for oil will be available. F.A.S.T. Piper has also developed some exciting new features. One of the biggest developments is the capability of multiple delivery points in a single model. While work around solutions existed in the past, it is now possible to model as many delivery points as are in your system. In addition to this, line looping is now done automatically by the software. Users still have the option of specifying which line to use as a line loop, however, many users will appreciate the logic built into F.A.S.T. Piper to automatically select which links to use. New GIS technology will allow F.A.S.T. Piper to extract pipeline specifications that have been stored in a shape file and import them directly into the gathering system editor. This assists you by reducing the work required to build and update models. When using reservoir models built in F.A.S.T. RTA and imported directly from the F.A.S.T. RTA database, maintaining the model is easier and less reworking of the data is required. F.A.S.T. WellTest feature improvements include the analytical and horizontal well models that have been added to F.A.S.T. RTA. The analysis of DFIT data has been further enhanced, and new tools for data filtering and management have been added. This has eliminated the need to use F.A.S.T. ValiData to prepare your data prior to analysis in F.A.S.T. WellTest. Fekete is committed to developing software that will meet our clients needs and our hope is that the highlighted features demonstrate this commitment. Please feel free to contact our sales team if you would like to discuss these features or have questions about our software or toll free within North America at Copyright 2010 Fekete Associates Inc. Printed in Canada 46