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I dedicate this volume to my professional society of choice during my career, The American Association of Petroleum Geologists. I have certainly been a member of other societies, but the AAPG is the one that I have supported over 40 years and that has supported me over that period as well. I have been an author, course instructor, reviewer, Distinguished Lecturer, Committee Chair, Trustee Associate and Executive Committee member over the years and have learned how to be an active professional from the example of other AAPG members.
The study of natural fractures can be viewed as a progression from basic qualitative observation, to detailed measurement, to analysis of the collected measurements, to use of the analyses and collected data. Early fracture studies focused on understanding the deformation of rock as recorded by the development of fractures, but since the middle of the 20th century fractures have also been recognized as important controls on fluid flow in fractured media, including hydrocarbon reservoirs. Early fracture data‐collection and analyses techniques, developed for structural purposes, were not always applicable to the later purposes of understanding fluid flow. This volume, however, bridges that gap, offering insights and techniques useful in fracture analyses specific to hydrocarbon reservoirs, and provides methods for adapting those insights and the collected data to their ultimate use in modeling naturally‐fractured reservoirs.
Ron Nelson has had a long and productive history in the hydrocarbon industry, having early appreciated the need to understand natural fractures and contributing significantly to solving the related problems. He studied under the pioneers of the field (John Handin, David Stearns, Mel Friedman, John Logan, Bob Berg) at the Center for Tectonophysics, Texas A&M, writing his dissertation in 1975 on fracture characteristics in strata of the Colorado Plateau (Nelson, 1975). His history of 26 years at the Amoco Oil Company made him a pioneer in his own right, and included practical problem‐solving in improving recovery from specific fractured reservoirs as well as more widely‐applicable research on the problems associated with fractured reservoirs. Since leaving Amoco almost two decades ago he has become a highly‐respected consultant to the hydrocarbon industry and a widely‐recognized fracture expert whose services are in demand around the world. Throughout his active work schedule, he has also found time to publish extensively on fractures, including writing and later revising an acclaimed volume on naturally fractured reservoirs (Nelson, 2001). In doing so he has generously and openly shared his knowledge with industry and students.
This volume is a practical, useful, and in‐depth source for geologists who need to learn about fracture data‐collection from the important sources presently used by the hydrocarbon industry (seismic, core, outcrop, image logs, engineering, etc.). It provides a much‐needed link between fracture data collection and fractured‐reservoir modeling.
New Mexico, February, 2019
I have certainly had a long career, and over that time have benefitted much from interactions with colleagues and companies I have worked with. Indeed, the 50 companies I have either worked for, or consulted with, have given me a broad exposure to structural geology and fractured reservoir endeavors worldwide. In addition, the numerous geologists, geophysicists, petrophysicists, and engineers in those companies have taught me much about both technical issues and about how to be an effective team member in our industry. Without these experiences this current volume would not have been possible.
The purpose of this manuscript is to provide a guide for the construction of a quantitative Static Conceptual Fracture Model (SCFM) from predominantly physical descriptive rock data, which along with a Dynamic Conceptual Model (DCFM) constructed from predominantly fluid and reservoir engineering data, can be used for reservoir flow simulation (concept from Trice 2000). These simulations constrain the current reservoir behavior, as well as predict how it will perform in the future.
This manuscript will discuss the various parameters that are needed to constrain the SCFM, and later, populate computer models used to generate gridded fracture models as input to simulation. The various parameters will be detailed along with techniques I have used to gather the needed data and populate the computer models. The parameters discussed are the same regardless of the simulation modeling style used or the computer programs used to house the data and make the needed reservoir calculations. In addition, I will comment on what to do and not do in technical planning when acquiring some of the needed data sets.
An important aspect of the modeling process is, in my mind, innovation. The rock and fracture data needed for the models can come from different sources and different scales of measurement. For example, constraining fracture corridor width in the subsurface can come from core, image logs and geophysical data. All three are measured at different scales and levels of precision, therefore, giving different values and accuracy. The important thing in the modeling is to make the measurement however you can with the data you have. The variation within the distribution of the measures is perhaps more important than the actual values, as values can be shifted in bulk during history matching to obtain credible results with respect to reservoir response. The guiding principle in my mind is innovation. Get the parameter distributions however you can with the data available.
Several of the topic areas described herein have previously been documented in the two editions of a previous textbook (Nelson 1985, 2001). However, this author is not a computer modeler. Rather, I have more than 40 years' experience studying fractured reservoirs and providing real‐time assistance to the experienced computer modelers during the process.
The computer modelers know very well the ins‐and‐outs of inputting the data and successfully getting appropriate results in the proper format. However, a team of multidisciplinary workers (geologists, geophysicists, engineers, petrophysicists, etc.) are needed to generate the basic fracture and reservoir data. This team is intimately familiar with the input data and knows its strengths and weaknesses which is especially important during history matching of simulation results. They, or their representative (a Fracture Champion), are the appropriate people to assist the computer modeling expert(s) in evaluating and selecting appropriate input of the natural fracture‐related data. An excellent example of the process is given in Richard et al. (2017).
What is presented here is a procedure for completion of a well‐constrained SCFM. Of course, individual reservoir studies may lack many of the data types needed for the complete model, especially early in the history of a project. In most studies, the SCFM generation occurs in steps over time. We move from early model descriptions with little hard data to later models with richer data bases to draw from, therefore, leading to a better constrained model with lower associated risk.
The procedure detailed in this book has been created using several guiding principles. These include the following in Figure 1.1.