Abstract The growth in estimated ultimate recovery ( EUR ) of oil and gas fields over the course of their development has been recognized as a significant contributor to hydrocarbon supply, both in the United States and abroad. Data on changes in EUR have been examined for oil and gas fields discovered on the modern shelf of the Gulf of Mexico, in order to empirically determine the possible causes of these changes. Using a semilog regression model of EUR as a function of years since discovery, from 1975 through 2002, roughly half of fields in the study area grew and the balance either shrank or remained statistically unchanged. Fields that grew were typically large discoveries to start and the volumes by which they grew were log normally distributed. The fields making the largest contributions to aggregate growth typically had at least 20 reservoirs over at least 5,000 feet of charged section, which was deposited in generally prograda-tional environments at sediment accumulation rates between 500 and 2,500 feet per million years. The principal mechanism of field growth in the study area was through the discovery of new reservoirs. In the fields having the largest growth, these discoveries occurred in cycles based on stratigraphic interval. Within each cycle, the largest reservoirs were discovered early and the size of reservoir discoveries declined exponentially. Up to four major stratigraphically based cycles were observed; generally, but not always, each subsequent cycle added a smaller volume to EUR than those that preceded it. A secondary source of growth arises through the combined effects of recognizing an increased volume of reservoir rock containing reserves and improvement in recovery factors. The contributions of these mechanisms have been examined through analysis of single-reservoir fields and growth in fields after their last new reservoir discovery. Field growth is tied to the economic conditions surrounding oil and gas production. From the mid-1970s through mid-1980s, during a period of rising and high prices, large increases in oil and gas reserves were gained through new field discoveries, discovery of new reservoirs within fields and, to a lesser extent, positive reservoir volume revisions and increases in recovery factors. Price collapses in 1986 and again in 1998 are both reflected in reductions in field growth and actually declines in aggregate EUR . Although a short time series, EUR growth between the beginning of the current price recovery in 1998 and 2002 indicates that supply of new oil and gas in existing fields is becoming more inelastic. This is most probably due to two factors: depletion of the growth potential of old, very large fields; and because of the progressive decline in the sizes of new field discoveries and the high correlation between size and growth, as newer finds have smaller growth potential.

Abstract Schiehallion is a two billion barrel deepwater clastic reservoir, situated on the Atlantic margin of the UKCS , one of the world’s most hostile environments for hydrocarbon production. The field has been developed via subsea wells tied back to an FPSO , and is one of the first developments of its kind anywhere in the world. The field may be characterized as high productivity but low energy and, as a consequence, water injection is essential to maintaining production. However, the reservoir is channelized, faulted, and has varying degrees of connectivity between the compartments, so that a good understanding of these factors is necessary to optimize the water injection distribution. Our understanding of the ‘plumbing’, or connectivity between the wells, has evolved and matured over time, using a wide range of different data types, from the initial extended well test, through RFT’s , pressure transient analyses, interference testing, PLT’s , tracer and geochemical sampling, to bi-annual 4D seismic surveys using increasingly sophisticated processing and interpretation. Much of this understanding has been incorporated in a 3D model, which uses object modeling and seismic conditioning to represent the sand distribution. Potential barriers to flow are identified from seismic coherency analysis, and the strengths of these barriers have been used as the main history matching parameters. A key learning has been that all data needs to be interpreted with great care, and it is essential to integrate several data types in order to obtain reliable conclusions. The paper gives examples of data which has been invaluable, as well as examples where the data is ambiguous or misleading.

Abstract The Ormen Lange gas field, discovered in 1997 (Hydro operated License PL209) in 1000 m (3,281 ft) water depth and covering an area of ca. 350 km 2 (217 mi 2 ) was further appraised by four wells prior to development approval in April, 2004. The partnership, Hydro (development operator), Norske Shell (production operator), Petoro, Statoil, ExxonMobil, and Dong, had a planned production-start in October, 2007, from 8 of 28 possible production wells in a staged development using four subsea templates. The development faced a number of challenges; rough seabed topography, subzero sea bottom temperatures, harsh ocean conditions and a change of operatorship at production start-up. Reservoir characterization of the areally limited, but intensely faulted turbidite reservoir has formed an integral part of the work flows. These work flows address the uncertainty of vertically and horizontally connected reservoir volumes for productivity at well targets. Model scenarios have been constructed in a 3D visualization environment where optimal integration of a multitude of seismic data volumes, derived attributes, and geological model concepts has been achieved. The roughly polygonally distributed faults are not expected to be sealing; having developed close to sea bed, their origin rules out cataclasis and cataclasis-enhanced cementation. The common gas gradient and absence of measurable depletion during well tests support non-sealing faults and vertical connectivity. However, dynamic fault seal uncertainties related to reservoir heterogeneity and compartmentalization have necessitated risking the relatively simple tank scenario and a more cautious, stepwise approach for the development concept. A significant opportunity can be realized if the gas can be produced profitably using only three templates.

Abstract A consistent design of experiments ( DoE ) based evaluation process was used to assess the magnitude of OOIP uncertainty as well as the relative contributions from uncertainty sources as a function of the historical development of the Jurassic Humma Marrat carbonate reservoir in the Partitioned Neutral Zone ( PNZ ). Within the Marrat interval, three stratigraphic layers, known informally as the A, C, and E zones, produce oil. Porosity and permeability is best developed in the dolomitized lowermost Marrat E interval. Based on limited data, approximately 80-85% of the current oil production is from the E zone and 10-15% from the A zone. The C zone contribution is 5% or less. The uncertainty sources used in the DoE -based evaluation were: structure (time-to-depth conversion and overall interpretation uncertainty), original oil-water contact ( OOWC ), porosity histogram, and oil saturation histogram. All of the uncertainties except structure were evaluated for each of the three stratigraphic zones known to produce oil in the Marrat. High, mid, and low-case values were determined for each of the uncertainty sources listed using well log, core, and analog information available after each well was drilled or as significant new data became available ( e.g. , reprocessed seismic volume). The time period covered by this historical look-back is from 1998 (pre-drill) to 2005. The pre-drill P 50 OOIP estimate for the Humma Marrat was about 900 million reservoir barrels. Following drilling of the initial two wells, the P 50 OOIP estimate was < 400 million reservoir barrels. Subsequent drilling and structure modifications (interpretation and time-to-depth conversion) increased the P 50 OOIP estimate to just over 1500 million reservoir barrels in April 2004. The P 50 OOIP was dropped to 625 million reservoir barrels after Well F was drilled in mid-2005. The OOIP uncertainty range, defined as the P 90 OOIP value minus the P 50 OOIP value, decreased from nearly 700 million barrels in 2004 to about 130 million barrels in mid-2005. Analysis of the DoE -based results show that the significant contributors to OOIP uncertainty changed as additional wells were drilled or existing data was re-processed or reinterpreted. However, the structure and/or OOWC uncertainties were generally the largest, though not necessarily always statistically significant contributors to OOIP uncertainty (based on a 95% confidence level). A normalized uncertainty index ( UI ) derived from the probabilistic OOIP values is used to discuss delineation efficiency and may be useful in delineation well planning.

Abstract An integrated workflow has been developed that successfully characterized a new gas reservoir in the southern Gulf of Mexico, which is utilized to improve reserves estimation, reservoir development, and management planning. The reservoir intervals were contained within a faulted rollover anticline. Based upon development of a sequence stratigraphic framework, the reservoirs were identified as retrogradational shoreface parasequences sitting atop third-order sequence boundaries. AVO and spectral analysis of the seismic volume provided support for this interpretation. A new play concept was developed which incorporated sequence stratigraphy and analysis of 3D seismic attributes for more regional mapping in the area. Recommendations for well stimulation also were made based upon stratigraphic aspects of the rocks.

Abstract A set of seismic, well log, core, petrophysical, and well test data was integrated to construct a 3D geological model for reservoir characterization and later performance simulation. The model was initially built to address the unexpected performance of a single well. This well was designed as a water injector but produced sufficient oil to be deemed a producing well. The model explained the reason for this unexpected behavior—the reservoir was compartmentalized into fifteen fault blocks, many of which were not in mutual communication. Also, individual fault blocks were stratigraphically compartmentalized. The case for compartmentalization was built upon analysis of log-derived Leverett J -Functions and petrophysical and well data, all within the context of a 3D geological model constructed in GoCad TM . This case study serves as an example of the value of integrating available data to develop a 3D geological model which can address short-term production issues, broader performance issues, and infill drilling opportunities, all of which may be affected by compartmentalization.

Abstract The Eocene Misoa Formation is a prolific producer of hydrocarbons in the Maracaibo basin and traditionally has been interpreted as being deposited in a fluvio-deltaic depositional system. Sedimentological interpretation of 1,534 ft (467.6 m) of core has led to the development of a new depositional model. The Misoa Formation C sands in the LAG-3047 area have been reinterpreted as being deposited from sustained fluvial-derived hyperpycnal flows. The conceptual hyperpycnal model has been used to guide correlation of 21 wireline logs and to provide a high-resolution stratigraphic model of the lower C Misoa sands. A geo-statistical approach was used to propagate the facies and the petrophysical properties in the geological model. However, some difficulties were encountered for propagating hyperpycnal channelized-lobe systems, since a standard object-modeling algorithm is useful only for fluvial systems. An alternative three-step methodology was developed to model channelized-lobe systems which proved to be very successful. Forty realizations of the geological model were generated to assess the uncertainty in the distribution of channelized-lobe systems between wells. Simulation was used to rank the realizations; the best realizations were chosen by historical pressure and production. Two upscaled grids were generated for simulation and prediction. The hyperpycnal depositional model aided in the simulation calibration process because reservoir compartments were easily modified to match the historical pressures and therefore connected reservoir pore volumes. At the end of the calibration process, these reservoir compartments could be used to define whether new wells would be likely to contribute to the proposed waterflood or to access new reservoir pools.

Abstract Northeast Betara Field, located in the south Sumatra basin of Indonesia, is a fault-bounded reservoir comprised of the Oligocene lower Talang Akar Formation. The reservoir consists of two fluvial facies, a lower braided river facies and an upper meandering river facies. Both facies are separated by areally extensive floodplain/marine shale. Based upon both sequence stratigraphic and structural analysis of 3D seismic and well/core data, the distribution of braided river facies is controlled strongly by block faulting coupled with a significant drop in relative sea level. During subsequent early rise in relative sea level, reservoir sands have been re-cycled and reworked to provide better reservoir quality of the upper meandering river sandstones. This facies has tested >1400 BOPD , >10 MCFGPD , and some condensate from NEB #7 well. The Northeast Betara Field is highly compartmentalized both structurally (faults and folds) and stratigraphically (discontinuous sandstones and shale interbeds). The field consists of separate oil and gas-condensate reservoir systems. Volumetric reserves calculation, combined with material balance studies, indicate the potential oil reserves comprise approximately 10 to 15% of the total potential gas-condensate reserves. Recognition of reservoir compartments having varying fluid contacts constitutes an important interwell frontier for development of Northeast Betara and other, similar fields in the area. Compartments have been identified using the integrated methodology described here. In structurally and stratigraphically compartmentalized reservoirs such as Northeast Betara Field, development of an integrated 3D geologic model, numerical reservoir simulation model, and production strategy has been critical to optimize both oil and gas production. Oil rim reserves have been produced in the early stage of development, followed by current production from the main gas-condensate reservoir.

Abstract The east coast of India represents a passive Atlantic-type peri-cratonic margin setup. The Krishna-Godavari basin along the east coast of India covers the deltaic and inter-deltaic areas of Krishna and Godavari rivers and extends into the offshore; it has an area of 1,45,000 sq. km. The basin evolved through crustal rifting and subsequent drifting during Mesozoic time, followed by major fluvial and marine Tertiary sedimentation. A geologic model has been constructed for Neogene deep-water depositional systems in the Krishna-Godavari basin to conceptualize the reservoir architecture of complex channel-levee, overbank, and lobes on the shelf-slope geologic setting. While the channel-levee deposits are dominated by siltstone/sandstone prone facies assemblages, the lobes are predominantly fine-grained sandstone/siltstone/mudstone facies. High quality 3D seismic imaging and interpretation techniques, integrated with wire-line logs, litho-cut-tings and cores have been followed in characterizing the complex deep-water reservoirs. The study integrates different data sets and methodologies such as (1) high quality 3D seismic with rigorous quality control in acquisition and processing using interactive geological input; (2) imaging enhancement through pre-stack depth migration of selective areas; (3) extensive use of rock-physics attributes through inversion and AVO studies; (4) detailing of depositional architecture through stratal-amplitude attribute, spectral decomposition, and coherency slices; (5) high resolution wire-line logs and analysis; (6) detailed petrophysical and petro-logical evaluation of conventional cores, and (vii) quantitative computation of reservoir properties and improving bed resolution through simultaneous angle dependent inversion.

Abstract Synthetic seismic forward modeling has been used for many years to gain a better understanding of the seismic expression of subsurface geology and to ensure consistency between quantitative models and available data. With improvement in static model-building capabilities, increased computing power, and the ongoing need to optimally use seismic information to condition exploration and production models, synthetic seismic modeling approaches have evolved towards 3D modeling of realistic and complex input models. The 1D-convolutional method of generating 3D synthetic seismic models is computationally very fast and convenient to apply. However, influences of spatially varying lateral resolution, acquisition, processing, and overburden effects on the resulting seismic image are fully or partially neglected. Given the simplifying assumptions of the 1D-convolutional modeling method, it is important to understand the degree to which results are representative of the actual seismic expression of the subsurface geology. It is desirable to know under which circumstances the 1D-convolutional approach can be assumed to be a sufficiently close approximation and under which conditions the more sophisticated 3D techniques are required. As a contribution to addressing this question, two suites of 3D synthetic seismic models were constructed from high resolution, realistic, and representative static facies models of complex turbidite reservoir architecture; one using the 1D-convolutional method and the other employing a 3D-modeling technique. The latter approach honors lateral resolution, processing, acquisition, and overburden effects. Comparison of results of the two methods suggests potential pitfalls in applying inferences from the 1D method in reservoir characterization (e.g., lithofacies distribution, net-to-gross, and connectivity).

Abstract A methodology devoted to the integration of seismic information within the geological stochastic modeling workflow has been developed in order to optimize the characterization of small scale internal reservoir heterogeneities. The workflow consists of three stages detailed here and in a companion paper in this volume ( Lerat et al. , 2006 ): Litho-seismic interpretation and definition of the 3D seismic constraint; geostatistical geological modeling using a 3D seismic constraint; and reconciling seismic data with the geological model. In this paper, we present the interpretation of seismic data in terms of 3D geological facies proportions at Girassol, a large and complex turbidite field located offshore Angola. This type of interpretation requires high quality seismic data, which was the case in the present case-study. Secondly, particular attention has been paid to calibration issues: for wells with available sonic data, vertical and lateral shifts have been determined at early stages of the analysis to ensure optimal local consistency between well logs and local seismic amplitudes. For the other wells, an optimal location has been found a posteriori by comparing electrofacies analysis results with geological facies proportions predicted from seismic. The proposed workflow integrates knowledge from various sources and with different spatial resolution and support: pre-stack seismic amplitudes and velocities, well logs, stratigraphy, and structural information. It is divided into three parts. Pre-stack stratigraphic inversion; Probabilistic seismic facies analysis from the inversion results based on discriminant analysis; and Computation of geological facies proportions from the previous results by a novel approach developed to account for scale differences between seismic facies and detailed geological facies description, in order to produce a geologically interpreted 3D model of the reservoir to be used in further steps of the reservoir modeling workflow.

Abstract Reservoir production and compartmentalization in many karst-modified reservoirs can be related to features resulting from subaerial weathering, tectonic faulting and fracturing, and/or hydrothermal processes. Critical features relating to reservoir character are often subtle and are difficult to image with standard seismic attributes. We have developed new 3D seismic-based geometric attributes that, calibrated with geologic and engineering data, have the potential to image and quantify karst-modified reservoir features at an interwell scale not previously possible. Our aim is to develop innovative seismic-based methodologies and workflows for reservoir characterization of karst-modified reservoirs. We have applied our new seismic attributes to reservoirs in Kansas, Colorado, and Texas that represent a diversity of ages, lithologies, karst processes, and porosity/permeability systems. In these reservoirs, we have mapped horizon structure, faults, and fractures with a combination of conventional seismic data, coherency, and new volumetric curvature attributes. Using horizon extractions and time slices, we have imaged the geomorphology of eroded surfaces and identified subtle attribute lineaments associated with faults and fractures that relate to reservoir production and compartmentalization. We predict azimuths of open and closed fractures by matching rose diagrams of attribute lineaments with strain ellipsoids, by calibrating to wellbore data, and by relating attribute lineaments to produced fluid volumes. We use improved spectral decomposition and acoustic impedance inversion technologies to image porosity variations in the reservoir. Our attribute-based structural and stratigraphic models, populated with borehole and engineering data, serve as the basis for improved geomodels that we validate with reservoir simulation.

Abstract A reservoir study was conducted at Gaucho Field in the Chiapas of Southern Mexico, the primary objective of which was to determine porosity in the base of the upper Cretaceous carbonate in order to facilitate further field development. Conventional seismic impedance inversion alone did not adequately predict porosity nor did neural network predictions using conventional seismic attributes. Spectral decomposition and neural network inversion were integrated to produce an estimated porosity cube at the target level that provided excellent porosity indication in validation wells. The lateral variation of porosities within the area ranged from about 2% to more than 30%. Thus, the application of these techniques allowed final adjustment of drilling locations, in order to capture the maximum local porosity possible. Resulting porosity maps within the field area are shown to have important implications for field development and further exploration in this area. For spectral decomposition, this study illustrates the relationship between porosity thickness and peak frequency and between the magnitude of the average effective zone porosity and peak amplitude. Additionally, the study demonstrates the importance of training a neural network properly with (1) appropriate input attributes and (2) utilization of wells which cover the spectrum of possible porosity encountered in the area. We show how such a methodology can be applied to similar carbonate reservoirs so as to distinguish locations having minimal to no effective porosity from areas having excellent porosity where additional development drilling can be fruitful. The aim of this paper is to showcase an integrated workflow for this type of study, rather than to focus on results.

Abstract Since the introduction of electrical borehole images over twenty years ago, many very useful applications have been developed for this data. Some of these applications range from hand-picked bed dips to fracture analysis; from thin-bedded pay determination to vugular porosity measurement; and from fault geometry determination to facies analysis. These applications are made possible because of the high resolution provided by these images. Electrical borehole images provide the means to perform detailed high-resolution reservoir characterization at and adjacent to the borehole. This paper addresses several of these applications, which give the geologist, petrophysicists, and reservoir/production engineer a means to evaluate their reservoir and make decisions ranging from setting pipe, to completion strategy, to offset well placement. Various images of thin bedded formations, slumped zones, fractured intervals, and faulted and folded intervals are shown along with the associated interpretations. Also, a series of images, coupled with corresponding outcrop and/or core photos, is provided of deep-water deposits. Implications of reservoir behavior and the required action to efficiently produce the reservoir are included.

Abstract The U-P Ford zone in the Long Beach Unit of the East Wilmington Field consists of low-permeability (2-50 millidarcies) turbidites that have been waterflooded since field start-up. Forty years of successes and failures have provided valuable insights into how to best waterflood these reservoirs given their thin-bedded nature, lateral and vertical changes in reservoir quality, formation damage susceptibility, and sand control problems. Multiple techniques and technologies have been applied to describe their reservoir architecture, quantify reservoir performance, and extract the oil. This work has become more challenging as the waterflood has matured and will require the close integration of all disciplines to identify and exploit remaining opportunities.

Abstract Prudhoe Bay Field, the largest non-heavy-oil field in North America, has produced about 11 billion of 25 billion barrels of oil-in-place since production began in 1977. Co-owners ExxonMobil, ConocoPhilfield simulation modellips, and BP made the decision to build a new full-field model to evaluate future development decisions in the field. Requirements for the full-field, 12-component reservoir simulation model included a model size limit of about one million active cells and an areal grid block resolution of 5 acres (467ft/142m X 467ft/142m) and 10 to 15 feet (3.0m to 4.6m) vertically. The model incorporates approximately 2600 wells (about 1000 of which are horizontal), 1800 faults, all productive reservoir zones and other important geological controls on fluid flow such as shales and conglomeratic thief zones. A team composed of BP’s Alaskan geological, geophysical, petrophysical, and reservoir engineering staff; geocellular modelers from the three partner companies; and a consultant reservoir simulation engineer was assembled to build the model. The inclusion of operating company geoscience and engineering staff contributed specific expertise in the geology and reservoir engineering of Prudhoe Bay Field. The inclusion of multiple geocellular modeling staff contributed “best practices” from each partner company and also allowed key parts of the model, such as the structural framework and properties model, to be built concurrently, thus saving substantial time. The inclusion of the consultant reservoir simulation engineer having extensive experience with previous Prudhoe Bay full-field models provided continuity with prior modeling efforts.