Summary
This article presents applications of deterministic and conditional geostatistical reservoir characterization methods to the heterogeneous carbonates of the upper Shuaiba formation in Daleel field, Oman. High-resolution reservoir descriptions based on the integration of logs, core, pressure transient tests, geology, and seismic data are constructed; and upscaled for use in reservoir simulation models to history match field performance data. Generally, geostatistical techniques combined with geology and proper upscaling of permeability heterogeneity yield best results without artificial alterations in various fluid and rock properties. Although acceptable history matches can be obtained with compromised less-detailed reservoir descriptions, these require modifications to reservoir data beyond reasonable ranges. Only detailed and concise reservoir descriptions result in history matches that are consistent with a variety of measured data sources.
Introduction
Reservoir characterization has gained a new momentum in the past decade, largely due to the introduction of geostatistical methods to the petroleum industry and rapid progress made in their advancement.1 The keen interest in reservoir characterization arises because it is well recognized that reservoir heterogeneity has a profound affect on all phases of hydrocarbon recovery, ranging from oil in-place calculations to sweep and conformance efficiency determination of various injection processes. Thus, any improved understanding of a reservoir will aid in better management and better exploitation of its hydrocarbon recovery potential.
The challenge in understanding and predicting reservoir performance is two-fold: first, to describe reservoir geologic heterogeneities realistically and quantitatively, and second to model reservoir flow behavior in the presence of all heterogeneities accurately and efficiently.2 While large-scale reservoir features (such as main layers or major faults) can be described by deterministic techniques, less-correlated medium-scale and more-chaotic small-scale heterogeneities may be characterized by geostatistical methods or related interpolative techniques. This is especially true for estimating interwell reservoir properties based on a limited amount of information available at wells.
The approaches to reservoir characterization fall into three categories: deterministic, stochastic, and combination of the two. The deterministic approach has been in use for several decades and ample success with it has been reported. The interwell properties are generally interpolated or extrapolated using algorithms based on the inverse-distance-square principle or variations of it. Usually, adjustments to the number of layers, gridblock properties, relative permeabilities, and even fluid properties are made in order to history match field performance. Some of these adjustments are warranted and some are solely knobs that are arbitrarily tuned in simulation models without physical bases. Thus, the resulting reservoir models may lack reliability and predictive capability.
Geostatistical methods, however, generate multiple realizations of reservoir heterogeneity that honor available data, but differ from one another by interwell properties where direct information is not available. The data used in these models are by in large of static nature coming mainly from cores, logs, and seismic attribute extractions. Dynamic information, such as pressure transient tests and production data, are usually excluded from explicit use in geostatistical reservoir characterization, primarily due to difficulty on how to best integrate them a priori into such models. However, recent advances have been made for direct inclusion of this dynamic information through the techniques of simulated annealing3 or direct volume-averaged upscaling.4 Nevertheless, these geostatical reservoir descriptions are capable of capturing detailed geology more realistically and of producing acceptable history matches to field performance data without artificial alterations to various reservoir or fluid properties.5–10
This article applies both methods of deterministic and geostatistical reservoir characterizations to describe and history match the primary recovery performance of a complex carbonate reservoir in Daleel field, Oman. This is a comparative study in an attempt to identify an applicable description method for this field to aid in its exploitation. The deterministic model investigates effects of layering and fluid bubblepoint pressure on production performance. The geostatistical approaches model detailed reservoir heterogeneity and evaluate the importance of proper representation of heterogeneity in flow simulations. During the course of the study, new or alternate approaches for various elements of reservoir characterization techniques have been developed, which are also included.
Background
Field Description.
The reservoir of Daleel field is an elongated carbonate shoal sands and back carbonates in the upper Shuaiba formation. Five geographical sedimentary environments of protected back shoal, shoal, shoal margin slope, inner shelf, and outer shelf comprise the formation. The productive portion of the reservoir is situated in the protected back shoal region (central part of the carbonate mound) and its marginal parts are located in regions with alternating cycles of shoal and shelf sequences. The reservoir is a stratigraphic-structural oil trap accumulation. Bioclastic peloidal packstone and wackstone form the main reservoir sedimentary material in this field. Repeated upward shallowing parasequence cycles, which relate to the geographical sedimentary environment, are recognized on wireline responses. These parasequence boundaries may be considered as synchronous surfaces for interwell correlation.
Detailed core and thin section studies have identified 12 lithofacies in the upper Shuaiba, ranging from coarse grain porous limestone to argillaceous lime and lime mudstone. Microstylolites, burrowing and other forms of diagenesis are common. Therefore, pore/throat size distribution and their connectivity as influenced by secondary diagenesis processes mainly control porosity and permeability developments. Significant changes in these lithofacies occur laterally and vertically, and there is an important tightly consolidated discontinuous lime mudstone deposit in the middle of the productive upper zone in the central part of the field.
3D Geostatistical Modeling and Uncertainty Analysis in a Carbonate Reservoir, SW Iran
