September 2004 – Reserve Overbooking – An issue of Professional Ethics

 Revelations of financial mismanagement and the resulting increase in legal and regulatory scrutiny have focused attention on how publicly-traded oil and gas companies report and book reserves. In spite of this, reserve overbooking remains a persistent problem, one that, while widely acknowledged, is only reluctantly discussed.

We see two broad categories of reserve overbooking: 1) errors of omission; and 2) errors of commission. The first relates to errors resulting from ignorance, which can be addressed through education, training and mentoring. The second relates to those things we know about – the choices we face when we find ourselves 1) tempted to intentionally overstate reserves for motivational reasons; or 2) faced with the need to de-book reserves. These are not technical issues; they are ethical ones, often influenced by misguided incentives.

Why is there so much reluctance and hand-wringing associated with de-booking reserves? It is because, for publicly traded companies, the market impacts can be quite negative, at least in the near term. But repeated experience has shown that ultimately, the "Piper must be paid"; unfortunately, it is the shareholders who often suffer the most. Are proper controls in place to mandate unbiased professional behavior? On paper they are, through stated company policies, governmental regulations and professional-society guidelines. Are these controls working? For the majority of firms who take seriously the fiduciary responsibilities entrusted to them, we believe they work most of the time. However, based on recent revelations of financial mismanagement, having the proper policies, controls and definitions in place is not enough. Ultimately, compliance is an issue of character and ethics – of personal and corporate values.


Mark A. McLane is a Partner in the international consulting firm of Rose & Associates, LLP. He holds a BSc with Honors in Petroleum Engineering from The University of Texas at Austin. He has a diverse technical and business background spanning 25 years in the petroleum industry. He joined Rose & Associates in January 2000 after three years with Pioneer Natural Resources and 17 Years with Exxon Company, U.S.A. He has co-authored several technical papers and served on the Professional Ethics/Registration Panel at the 2003 SPE ATCE in Denver, Colorado.


November 2004 – Production Data Analysis

Over the last 30 years, production data analysis, also called advanced decline curve analysis, has become one of the most important tools for the production or reservoir engineer working in tight gas basins. Advanced decline curve analysis fills a role intermediate between that of conventional decline curve analysis on the one hand, and reservoir simulation on the other.

The first part of the presentation looks at a number of different production data analysis techniques that have been developed over the years. Most of these techniques are based on one of three different approaches, each of which has its strengths and weaknesses. The first approach is to match the production rate and/or cumulative production data using log-log type curves. The Fetkovich type curve method is perhaps most well-known of these methods. In the second approach, plotting functions are used to transform the rate response from a well produced at constant pressure to an equivalent pressure response from a well produced at constant rate. The data can then be analyzed like a pressure transient test, taking advantage of the wide range of type curves and specialized methods that have been developed for pressure transient analysis. The third approach is to use an analytical model coupled with a non-linear regression algorithm to automatically history-match the production data.

Regardless of the approach, there are limits to the information that can be obtained from production data. The second part of the presentation discusses what production data analysis can and cannot do. Like pressure transient analysis, production data analysis is an inverse problem. Pressure transient tests are usually run over a short period of time under carefully controlled conditions. As a result, the pressure transient analyst usually has high quality data with which to work. In contrast, production data are taken over an extended period of time under typical operating conditions. Thus, production data are usually much more erratic than pressure transient data.

With a proper understanding of its limitations, production data analysis can be a very useful tool for production forecasting, reservoir evaluation, and restimulation candidate selection.


Dr. John P. Spivey has over 20 years experience in the petroleum industry, with interests in pressure transient analysis, production data analysis, reservoir engineering, continuing education, and software development. From 1984 to 1990, he worked for SoftSearch, Inc./Dwights EnergyData developing pretroleum enconomics and engineering software.

In 1990, Dr. Spivey joined S.A. Holditch & Associates (SAH), which was purchased by Schlumberger (SLB) in 1997. While at SAH/SLB he conducted reservoir simulation, gas storage, and tight gas application studies and taught industry short courses in well testing and production data analysis. He also designed and developed PROMAT, an analytical production data analysis program, and WELLTEST, an interactive pressure transient test analysis program.

Dr. Spivey remained with Schlumberger until 2004, when he left to start his own reservoir engineering consulting and software development company, Phoenix Reservoir Engineering. He is currently developing a new production data analysis software package, scheduled to be released by the end of 2004.

Dr. Spivey is the editor of the SPE Reprint Series Vol. 52, Gas Reservoir Engineering, and Vol. 57, Pressure Transient Testing, and coauthor of SPE Textbook Series Vol. 9, Pressure Transient Testing. He has published over 15 papers and articles in industry journals and trade publications.


January 2005 – The Application and Technology of Slickwater Fracturing

Much has been said and asked about the use of slick water as the primary fracture fluid to stimulate wells throughout the U.S. Operations. Slickwater has been used for years in many naturally fractured carbonates with great success.

In recent years and since the 1996 publication of SPE Paper 38611 "Proppants". We Don’t Need No Proppants" the "technology " and applications of this method to complete tight gas sands have generating significant discussion. This presentation will focus on the criteria for slickwater frac stimulation candidates and their success. There are many areas and formations where this technique is being utilized. The successes in these areas have been dependent on continual change on the completion to find the optimal treatment. The stimulation design then becomes based on how specific reservoirs respond to the treatment during pumping requiring much more than doing in one area what works in another area. These changes include determining the optimum volume, proppant concentration, proppant size/type and pumping technique used to place the best treatment. The final test for the success of these treatments is the production results for areas where slickwater fracturing treatments are performed.


Gary has BS degree from Northern Arizona University in 1978 and joined BJ Services. He has worked in well completions and stimulation for 25 years.

He began work in the Mid-Continent Area as a Service Supervisor and District Engineer prior to moving to Houston where he was Product Manager and Engineer analyzing well treatments and design.

He transferred to Dallas, Texas as Region Technical Manager in 1993 and has been responsible for the treatment design and completions engineering for the East Region, which includes North Texas, East Texas, North Louisiana, and Mississippi. He is responsible for over 2,000 jobs per year performed within the Region.

Gary has served on SPE Technical Paper Selection Committee for well completions and authored several SPE papers on well completions.


February 2005 – Global Energy Markets

David will be talking about the current and future state of global energy markets. Please check back for more information on this compelling talk.


David Pursell is currently director of Upstream Research at Pickering Energy Partners, Inc.

A graduate of Texas A&M with both B.S. and M.S. degrees in Petroleum Engineering, David began his career at Arco, Alaska Inc., based in Anchorage as a Production Engineer. After nearly four years in Alaska, David joined S.A. Holditch and Associates, Inc. where he worked on various domestic and international oil and gas consulting projects.

In 1998, David joined Simmons and Company, Intl., as a research analyst, focusing on macro oil and gas supply and demand issues. Earlier this year, David helped form Pickering Energy Partners, an independent oil and gas research organization.

March 2005 – Virtual Intelligence:  A panacea or Hype for Long Standing Reservoir Engineering Issues?

Virtual intelligence technology offers a different paradigm for computing, as biologically inspired computing (soft computing) is radically different from conventional computing (hard computing). In discussing virtual intelligence, it is common to present it using a biological metaphor. We have some understanding of how humans process information and learn. Virtual intelligence techniques such as artificial neural networks (ANNs), genetic algorithms, and fuzzy logic are used as rough models of mental processes. As these techniques operate in a massively parallel fashion, they can process information and carry out solutions almost simultaneously in an intuitive manner. This is why some interactive non-linear processes that cannot be tracked through the diligent use of analytical formulations can be practically solved using soft computing techniques.

In this presentation, four ANN applications to four different reservoir engineering problems are discussed. The first application demonstrates the utilization of an artificial neural network for predicting the relative permeability characteristics. The second application is designed to overcome some of the significant challenges that are faced in positioning a new well during a field development study. The third application shows the use of soft computing methodology in the analysis of pressure transient data. Finally, the fourth application involves the use of artificial neural networks as a screening tool for CO2 sequestration process in coal seams. In all of these applications the question that we are trying to answer is whether the virtual intelligence is capable to minimize a cost function, energy function, time function or a complex combination of these functions in finding the optimum solution to reservoir engineering problems which fall under one of these groups.


T. Ertekin is professor and chairman of petroleum and natural gas engineering at Penn State University where he is also holder of the George E. Trimble Chair in Earth and Mineral Sciences. He holds B.Sc, M.Sc. and Ph.D. degrees in petroleum engineering. He has authored and/or co-authored more than 150 papers, 4 books, and supervised more than 70 graduate theses. He is the recipient of several awards at Penn State University as well as he is the 1998 recipient of the SPE Distinguished Faculty Achievement Award and 2001 SPE Lester C. Uren Award.


April 2005 – Production Optimization at the Surface Level

Smart wells and real-time optimization systems keep top-performing wells in high gear. But what about the other 90% of your producing assets? Most of the industry’s breakthroughs in field automation and production optimization have overlooked the hard-working, but unspectacular well and the maturing surface network.

It is possible to increase production and reduce operating costs, with surprising gains even for "average" O&G assets using evolving wireless, compact and affordable wellhead automation devices.

In the past, automation depended on dumb devices, sending lots and lots of information to a central server. Maybe every 10 or 15 minutes, you’d have lots of resources on your database where you’d pick up alarms. Daily reports and decisions were made from the vast information coming across, with some kind of editing and communication. Now, systems are available that deliver the right amount of data at the right time.


Doug Boone is the Vice-President of Production Solutions Product Management for IHS Energy, located in Denver, Colo. With nearly 30 years’ experience in the oil and gas industry, Boone leads the IHS Energy team that built PowerTools, a reserve analysis software program, FieldDIRECT, a Web-based field data collection service, and iNodes, a suite of hardware for affordable production optimization.

Boone previously served as technical editor for the SPE. Boone’s areas of focus include property and acquisition evaluations, oil and gas forecasting, and field data collection. Boone created the Petroleum Engineering ToolKit spreadsheet programs. The author of more than 30 articles, he has also published a 15-part series of articles for Petroleum Engineer International.


May 2005 – Hydraulic Fracture Monitoring as a tool to improve reservoir management

Understanding the created fracture geometry is key to the effectiveness of any stimulation program. However, almost all predictive models used by reservoir and production engineers to estimate recovery in stimulated wells are based on assumptions that naturally lead to oversimplified fracture geometry. Several published and unpublished microseismic monitoring campaigns reveal that in most cases, hydraulically induced fractures are asymmetric (e.g., one wing of the fracture system is predominantly longer than the other). This asymmetry is also observed in the vertical plane. This has deep implications on reservoir management. For example, if one knows where most of the depletion occurs (e.g., how does the induced fracture geometry relate to the overall existing drilling and producing field geometry), a production team can improve its infill drilling program and flood to improve production.

Micro-seismic is one of the latest and most accepted technologies allowing reservoir engineers and geoscientists to understand hydraulically induced fractures as well as naturally pre-existing fracture networks in three dimension. It uses one or several arrays of sensitive and high-vector fidelity geophones in one or several observation wells at a monitoring distance from the well to be treated. These geophones record the microseismic events generated while the formation ruptures following the hydraulic treatment. These recordings being performed along a continuous time-line, microseismic locations can be determined (as well as other source parameters) and mapped to document how the hydraulically induced fracture system propagate within the pay zone.

In plays such as the Barnett shale formation, many factors impact the ultimate hydraulically induced fracture system geometry. Understanding this geometry is not only helpful to improve large-scale reservoir management but also to design effective stimulation programs specific to a reservoir.


Dr. Joël Le Calvez graduated with a B.Sc. degree in Physics from the University of Nice. He completed a M.Sc. degree in Geosciences from the University of Nice-Sophia Antipolis before to graduate from the University of Paris VI with a pre-doctoral degree in Geodynamics. He has since completed a Ph.D. in Geology at the University of Texas at Austin where he specialized in structural geology, salt tectonics and physical modeling. While working for the Bureau of Economic Geology at the Applied Geodynamics Laboratory, his main interests were graben and fault linkage, extensional tectonics, and modeling. Since 2001, he works for Schlumberger as a geologist, where his present work focuses on microseismicity related to stimulation programs.

Sandy Conners graduated from the University of Calgary with a B.Sc degree in Geophysics in 1995. While acquiring her degree she participated in the Foothills Research Project which focuses on assisting energy companies drill for oil and gas more accurately in faulted areas such as the Rocky Mountain foothills. Upon graduation, she joined Schlumberger and worked in the GecoPrakla (currently WesternGeco) segment acquiring land seismic in Western Canada and throughout the United States. Her focus was on data quality and acquisition logistics. Eventually, she became responsible for 2D/3D land survey designs. She is currently involved in the development of hydraulic fracture monitoring in the Dallas, Fort Worth and Midland areas.