[PDF] Dynamic Reservoir Characterization Of Naturally Fractured Reservoirs From An Inter Well Tracer Test eBook
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After field redevelopment in the Sherrod Unit of the Spraberry Trend Area, an inter-well tracer test was conducted at the field scale in order to understand the fracture system, which forms preferential flow paths for better management of waterflooding. The test consisted of 13 injection wells and more than 110 producing wells that were sampled, with each injector having its own unique tracer. A wide range of tracer responses was observed in terms of tracer recovery, breakthrough time, and tracer velocity. Additional noise on tracer data was noticed due to reinjection of produced water. In this study, a comprehensive workflow is presented for dynamic reservoir characterization of naturally fractured reservoirs from an inter-well tracer test by incorporation of analytical interpretation, streamline simulation, and streamline-based optimization techniques. Categorized tracer responses were mapped according to analytical analysis, and dominating flow trends were detected in E-W and NE-SW directions before the simulation study. The constructed three-phase, dual-porosity model was simulated by a streamline simulator. Certain parameters in the model were modified based on high tracer response until a reasonable match was obtained for an inverted nine-spot pattern and breakthrough time of the injected tracer. Once the model became capable of matching historical field production, a 1-year prediction run was conducted for optimization. Cumulative oil production was increased by 8,000 bbl by allocating more water toward efficient producers, and 10,000 bbl less water was produced for the optimized case. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151965
In order to understand the complex fracture network that controls water movement in Sherrod Area of Spraberry Field in West Texas and to better manage the on-going waterflood performance, a field scale inter-well tracer test was implemented. This test presents the largest inter-well tracer test in naturally fractured reservoirs reported in the industry and includes the injection of 13 different tracers and sampling of 110 producers in an area covering 6533 acres. Sherrod tracer test generated a total of 598 tracer responses from 51 out of the 110 sampled producers. Tracer responses showed a wide range of velocities from 14 ft/day to ultra-high velocities exceeding 10,000 ft/day with same-day tracer breakthrough. Re-injection of produced water has caused the tracers to be re-injected and added an additional challenge to diagnose and distinguish tracer responses affected by water recycling. Historical performance of the field showed simultaneous water breakthrough of a large number of wells covering entire Sherrod area. This research investigate analytical, numerical, and inversion modeling approaches in order to categorize, history match, and connect tracer responses with water-cut responses with the objective to construct multiple fracture realizations based entirely on water-cut and tracers' profiles. In addition, the research highlight best practices in the design of inter-well tracer tests in naturally fractured reservoirs through lessons learned from Sherrod Area. The large number of tracer responses from Sherrod case presents a case of naturally fractured reservoir characterization entirely based on dynamic data. Results indicates that tracer responses could be categorized based on statistical analysis of tracer recoveries of all pairs of injectors and producers with each category showing distinguishing behavior in tracers' movement and breakthrough time. In addition, it showed that tracer and water-cut responses in the field are dominantly controlled by the fracture system revealing minimum information about the matrix system. Numerical simulation studies showed limitation in dual porosity formulation/solvers to model tracer velocities exceeding 2200 ft/day. Inversion modeling using Gradzone Analysis showed that east and north-west of Sherrod have significantly lower pore volume compared to south-west. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151192
The main purpose of this book is to provide the reader with a basic understanding of the behaviour of fractured reservoirs, using evaluation techniques based on processing pressure and flow-rate data resulting from production testing.It covers the fundamental reservoir engineering principles involved in the analysis of fluid flow through fractured reservoirs, the application of existing models to field cases, and the evaluation and description of reservoirs, based on processed data from pressure and production tests. The author also discusses production decline analysis, the understanding of which is a key factor influencing completion or abandonment of a well or even a field.The theoretical concepts are presented as clearly and simply as possible in order to aid comprehension. The book is thus suitable for training and educational purposes, and will help the reader who is unfamiliar with the subject acquire the necessary skills for successful interpretation and analysis of field data.One of the most important features of the book is that it fills the gap between field operations and research, in regard to proper management of reservoirs. The book also contains a computer program (FORTRAN language) which can be incorporated in existing software designed for reservoir evaluation; type curves generation, test design and interpretation, can be achieved by using this program.Petroleum engineers, reservoir engineers, petroleum geologists, research engineers and students in these fields, will be interested in this book as a reference source. It can also be used as a text book for training production and reservoir engineering professionals. It should be available in university and oil company libraries.
A thorough understanding of the subsurface fracture network is crucial for the effective exploitation and management of geothermal energy, unconventional hydrocarbon resources, groundwater reservoirs, etc. While conventional tracer technology is a useful tool to characterize the complex network of flowpaths in geologic reservoirs, tracers are limited in unique variations and hence insufficient for characterizing reservoirs with a large number of wells. In addition, conventional tracer testing only provides a "snapshot" of the flowpath properties which may be inadequate for reservoirs that are subjected to changes. This research sought to resolve the limitations of conventional tracer testing by exploring novel, DNA-based tracer candidates. DNA's infinite number of unique sequences and hence great degree of specificity makes it a promising tracer candidate for improved subsurface characterization. We first investigated the use of uniquely designed, synthetic DNA fragments as injected tracers. The method to measure target-specific DNA tracer concentration is described. The effect of DNA sequence, fragment length and porous medium on DNA transport was studied to provide guidance to potential field applications and data interpretation. It was found that DNA transport was not affected by DNA sequence (i.e. the arrangement of nucleotides). The length of DNA fragments does not affect the shape of the tracer return curve, but does affect tracer mass recovery. Shorter DNA appeared to be more prone to adsorption, while longer DNA appeared to be more prone to size exclusion effect. We then extended the concept of DNA-based tracers towards the genomic DNA of fluid-associated microorganisms that naturally colonize a geologic reservoir. Instead of targeting just a few microbes, we proposed taking advantage of the entire microbial community population in a reservoir fluid sample as unique signatures pinpointing the origins of fluids. We tested this method at a mesoscale enhanced geothermal system (EGS) testbed at Sanford Underground Research Facility (SURF) by sampling indigenous fluids produced from separate fractures and analyzing their microbial community structure via high-throughput 16S rRNA gene amplicon sequencing. We found that hydraulically isolated fractures at our field site hosted distinct microbial community populations, demonstrating substantial microbial heterogeneity across fractures. However, locally within a fracture, the microbial community were relatively homogenized, serving as a unique natural tracer or "fingerprint" of the fracture. We demonstrated at our field site that sampling indigenous fluids from an undisturbed, newly developed reservoir could help us identify natural interwell connectivity when more than one well were drilled into the same natural fracture. Finally, building upon the idea of reservoir indigenous microbial populations as natural tracers, we investigated the potential of this novel data source in an actively circulating, dynamic reservoir. Again using the EGS testbed at SURF, we sampled the produced fluids from the reservoir that underwent long-term flow circulation. Sampling was conducted regularly in a 5-month time series and the microbial populations in the fluids were sequenced. We found that although the whole circulating reservoir were connected hydraulically, the difference in relative connectivity among fractures still allowed different flowing fractures to have different microbial community signatures. The long-term microbial monitoring at our site identified the switch of production zone of a borehole likely due to major changes in the fracture network. Changes in fracture network were also observed from microbial time-series data after a week-long injection halt, likely due to the reopened hydraulic fracture not restoring to its initial state. We thereby demonstrated that long-term microbial community monitoring in an active reservoir may effectively enable the direct observation of fracture network evolution. Such information is difficult to achieve via other reservoir diagnostic methods.
Geologists, engineers, and petrophysicists concerned with hydrocarbon production from naturally fractured reservoirs will find this book a valuable tool for obtaining pertinent rock data to evaluate reserves and optimize well location and performance. Nelson emphasizes geological, petrophysical, and rock mechanics to complement other studies of the subject that use well logging and classical engineering approaches. This well organized, updated edition contains a wealth of field and laboratory data, case histories, and practical advice. A great how-to-guide for anyone working with fractured or highly anisotropic reservoirs Provides real-life illustrations through case histories and field and laboratory data
This report focuses on integrating geoscience and engineering data to develop a consistent characterization of the naturally fractured reservoirs. During this reporting period, effort was focused on relating seismic data to reservoir properties of naturally fractured reservoirs, scaling well log data to generate interwell descriptors of these reservoirs, enhancing and debugging a naturally fractured reservoir simulator, and developing a horizontal wellbore model for use in the simulator.
Reservoir Characterization is a collection of papers presented at the Reservoir Characterization Technical Conference, held at the Westin Hotel-Galleria in Dallas on April 29-May 1, 1985. Conference held April 29-May 1, 1985, at the Westin Hotel—Galleria in Dallas. The conference was sponsored by the National Institute for Petroleum and Energy Research, Bartlesville, Oklahoma. Reservoir characterization is a process for quantitatively assigning reservoir properties, recognizing geologic information and uncertainties in spatial variability. This book contains 19 chapters, and begins with the geological characterization of sandstone reservoir, followed by the geological prediction of shale distribution within the Prudhoe Bay field. The subsequent chapters are devoted to determination of reservoir properties, such as porosity, mineral occurrence, and permeability variation estimation. The discussion then shifts to the utility of a Bayesian-type formalism to delineate qualitative ""soft"" information and expert interpretation of reservoir description data. This topic is followed by papers concerning reservoir simulation, parameter assignment, and method of calculation of wetting phase relative permeability. This text also deals with the role of discontinuous vertical flow barriers in reservoir engineering. The last chapters focus on the effect of reservoir heterogeneity on oil reservoir. Petroleum engineers, scientists, and researchers will find this book of great value.
Reservoir description is an important step to make reliable reservoir performance predctons. In general, reservoir description can be defined as the process of describing various reservoir characteristics (e.g., porosity, permeabiIity, thickness,etc.) that honor all the available data (e.g., geological, geophysical, petrophysical,production data). The appropriate way to reach this goal is to integrate all available data from different sources; geologic knowledge, seismic data, well test pressure data, production history, etc. However, how to efficiently integrate all these data coming from different sources is a challenge to the person or team working inreservoir description area.Although, geostatistical methods (Kriging, cokriging, etc. ) are well-suited tointegrate static (1inear or hard) data coming from geology, logs, seismic and core analysis, they are limited when applied to dynamic data such as well test pressure,tracer test and production data. Because dynamic data are non-linear with respect tomodel parameters, conditioning to dynamic data possesses some difficulties. inrecent years, it has been shown that the inverse problem theory based on Bayesian estimation provides a powerful methodology not only to generate rock property fields conditioned to both static and dynamic data, but also to assess the uncertaintyin performance predictions. To date, standard applications of inverse problem theory given in the literature assume that rock property tields obey multinormal(Gaussian) distribution and are second order stationary. in this work, the main objective is to extend the inverse problem theory to cases where rock property tields( only porosity and permeabiIity tields are considered) come from fractal distributions so that one can be able to generate fractal rock property tields conditioned to both static and well test pressure data.Recent studies have shown that ftactals like fractional Gaussian noise (fGn) and fractional Brownian motion ( fBm) are promising approaches to characterize porosity and/or permeabiIity , in general the hydraulic property variations in the subsurface.in the literature, there exist stochastic interpolation methods that can be used to generate conditional fractal simulations honoring variograms and hard data(measurements of porosity and permeabiIity at wells). However, there exists nostudy in the literature that considers generating fractal flelds conditioned to dynamicdata, in particular to well-test pressure data. Thus, the objective of this work is togenerate fractal (fGn and fBm) porosity and permeability tields conditioned tovariograms, hard data and well-test pressure data by using the inverse problemtheory .The thesis is organized as follows. In Chapter 2, we begin by presenting the theoryof fractal and fractal distributions in detail. Because, in this work, we define rockproperty fields, specifically permeability and porosity , using the fractaldistributions, we note various statistical properties of fGn and ffim distributions.We also provide the methods that can be used to generate unconditional realizationsof isotropic or anisotropic ffim/fGn random functions. In Chapter 3, we review theinverse problem theory based on Bayesian estimation, because in this study, we usethis theory to generate rock property fields (porosity and permeability) conditioned to both well-test pressure, static ( core and well log) and geostatistical data. Becauseour objective in this study is to extend the inverse problem methodology to generateporosity and permeability fields that show fractal (fGn and ffim) behavior, we show how one can extend the commonly used inverse problem methodology based onstationary Gaussian fields to fractal fields. In Chapter 4, we present one, two, andthree dimensional applications of inverse problem theory based on Bayesian estimation (explained in Chapter 3) to generate fGn/fBm porosity and 1n-permeability fields conditioned to well-test pressure, static ( core and well log) and geostatistical data for single phase problems. In Chapter 5, we study transport over fracture network that can be considered as a fractal object. We present fractal pressure transient behavior and analysis of a single or multiple vertical well systems (with wellbore storage and skin effects) producing in fractured reservoirs without matrix participation. Nonlinear regression analysis for pressure data from such systems is presented and discussed for analysis purposes. Also, analysis of aninterference pressure data from Kizildere geothermal field using fractal model is presented.
Reservoir Characterization, Modeling and Quantitative Interpretation: Recent Workflows to Emerging Technologies offers a wide spectrum of reservoir characterization techniques and technologies, focusing on the latest breakthroughs and most efficient methodologies in hydrocarbon exploration and development. Topics covered include 4D seismic technologies, AVAz inversion, fracture characterization, multiscale imaging technologies, static and dynamic reservoir characterization, among others. The content is delivered through an inductive approach, which will help readers gain comprehensive insights on advanced practices and be able to relate them to other subareas of reservoir characterization, including CO2 storage and data-driven modeling. This will be especially useful for field scientists in collecting and analyzing field data, prospect evaluation, developing reservoir models, and adopting new technologies to mitigate exploration risk. They will be able to solve the practical and challenging problems faced in the field of reservoir characterization, as it will offer systematic industrial workflows covering every aspect of this branch of Earth Science, including subsurface geoscientific perspectives of carbon geosequestration. This resource is a 21st Century guide for exploration geologists, geoscience students at postgraduate level and above, and petrophysicists working in the oil and gas industry. Covers the latest and most effective technologies in reservoir characterization, including Avo analysis, AVAz inversion, wave field separation and Machine Learning techniques Provides a balanced blend of both theoretical and practical approaches for solving challenges in reservoir characterization Includes detailed industry-standard practical workflows, along with code structures for algorithms and practice exercises