GeoScienceWorld
Volume

Anatomy of a Giant Carbonate Reservoir:

Fullerton Clear Fork (Lower Permian) Field, Permian Basin, Texas

Edited by Stephen C. Ruppel

Abstract

Despite declining production rates, existing reservoirs in the United States contain large quantities of remaining oil and gas that constitute an enormous target for improved diagnosis and imaging of reservoir properties. The resource target is especially large in carbonate reservoirs, where con entional data and methodologies are normally insufficient to resolve critical scales of reservoir heterogeneity. The objectives of the research described in this volume were to develop and test such methodologies for improvedimaging, measurement, modeling, and prediction of reservoir properties in carbonate hydrocarbon reservoirs. The focus of the study is the Permian Fullerton Clear Fork reservoir of the Permian Basin of west Texas. This reservoir is an especially appropriate choice because the Permian Basin is the la gest oil-bearing basin in the United States and, as a play, Clear Fork reservoirs have exhibited the lowest recovery efficiencies of all carbonate reservoirs in the Permian Basin.

  1. Page 1
    Abstract

    Despite declining production rates, existing reservoirs in the United States contain large quantities of remaining oil and gas that constitute an enormous target for improved diagnosis and imaging of reservoir properties. The resource target is especially large in carbonate reservoirs, where con entional data and methodologies are normally insufficient to resolve critical scales of reservoir heterogeneity. The objectives of the research described in this volume were to develop and test such methodologies for improvedimaging, measurement, modeling, and prediction of reservoir properties in carbonate hydrocarbon reservoirs. The focus of the study is the Permian Fullerton Clear Fork reservoir of the Permian Basin of west Texas. This reservoir is an especially appropriate choice because the Permian Basin is the la gest oil-bearing basin in the United States and, as a play, Clear Fork reservoirs have exhibited the lowest recovery efficiencies of all carbonate reservoirs in the Permian Basin.

  2. Page 5
    Abstract

    Clear Fork reservoirs in the Permian Basin typically display a wide range of geologic and petrophysical properties that make the efficient recovery of hydrocarbons difficult. A key step in improving recovery efficiency is defining the patterns of variability in these rocks. The critical elements of variability that must be defined are facies, groupings of rocklike properties; and sequence architecture, the framework of facies variability. As in all carbonate reservoirs, rock-based studies must form a fundamental basis for characterizing and modeling facies and sequence architecture variability through the reservoir. Combined with wireline-log data, they provide a basis for defining both rock attribute distributions and reservoir framework.

    At Fullerton field, we used 29 cores (>14,000 ft [>4270 m]), well logs from approximately 800 wells, three-dimensional seismic data, and outcrop data to define facies (rock attributes) and sequence stratigraphy (reservoir framework). The Fullerton reservoir section averages 500 ft (152 m) that can be subdivided into three stratigraphic units (Abo, Wichita, and Lower Clear Fork) and parts of two composite and six high-frequency sequences. At the base of the reservoir section, Abo rocks (sequences L1.1 and L1.2) consist of clinoformal, outer-platform, subtidal, fusulinid-crinoid packstones that exhibit locally excellent porosity and permeability characteristics but are highly variable in continuity. Wichita rocks were deposited in peritidal tidal-flat settings and consist of mud-rich facies that generally display poor continuity and commonly very low permeability and oil saturation despite locally high porosity. Wichita rocks (sequences L1.2 and L2.0) are updip inner-platform equivalents of both partly underlying Abo and overlying Lower Clear Fork facies. Lower Clear Fork rocks (sequences L2.1 and L2.2) are dominantly middle-platform subtidal, grain-rich ooid-peloid packstone and grainstone facies that exhibit the best permeability and oil saturation properties.

    Although basic facies distributions are defined by high-frequency sequence architecture, the reservoir framework must be based on the correlation of higher resolution depositional cycles. Because gamma-ray logs showed little or no relationship to facies and cyclicity, we calibrated porosity logs to cyclicity and used them to define 10 to 15 ft (3 to 5 m) cycles throughout the reservoir.

  3. Page 49
    Abstract

    A major task in building a reservoir model is quantifying the geologic framework using petrophysical properties. Porosity and water saturation values can be obtained from wireline logs, but permeability is a rock property that cannot be obtained directly from logs. Commonly, a single porosity-permeability transform is used to estimate permeability from porosity logs. However, such an approach fails to account for variations in porosity-permeability relationships that are common in carbonates. In this study, rock-fabric-specific porosity-permeability transforms are used together with log porosity to calculate permeability. Although the reservoir at Fullerton field contains several rock fabrics, they can all be grouped into three petrophysical groups, each having a unique porosity-permeability relationship. These petrophysical groups can be linked to facies and stratigraphy using an integrated study of thin sections and cores.

    The lowermost stratigraphic unit in the reservoir (the Wichita of sequences L1 and L2) is composed dominantly of peritidal facies consisting of fine-crystalline mud-dominated dolostones and mud-dominated limestones, all of which can be assigned to a single petrophysical group (class 3). In contrast, rocks of the overlying Lower Clear Fork (sequences L2.1–L2.3) display far more petrophysical variability, both stratigraphically and geographically. Sequence L2.1 comprises an upper late highstand peritidal succession and a lower, transgressive, and early highstand systems tract succession of subtidal facies. The peritidal rocks such as those of the Wichita are fine-crystalline mud-dominated fabrics of petrophysical class 3. The subtidal rocks, which contain both limestone and dolostone, are more variable. Dolostones are mostly medium-crystalline, subtidal grain-dominated dolopackstones and medium-crystalline, mud-dominated petrophysical class 2 rocks. Limestones are composed of oomoldic grainstone. Although grainstones normally possess petrophysical class 1 rock fabrics, they display class 2 petrophysical relationships because they are moldic. Lower Clear Fork sequence L2.2 is also dominated by class 2 medium-crystalline dolostone fabrics. However, these rocks display class 1 porosity-permeability relationships because of abundant poikilotopic anhydrite. Oomoldic limestone, such as that in sequence L2.1, is also locally common. The uppermost L2.3 reservoir sequence contains fine-crystalline dolostone, class 3 peritidal facies.

  4. Page 67
    Abstract

    We present the procedures used to develop an accurate wireline-log database for the Fullerton Clear Fork field reservoir. We first review the borehole logging history of the field then discuss the assembly and quality checking of the log data and normalization of neutron-porosity logs, and calibration to core porosity. The procedures documented here deviate somewhat from the norm in that the assembly of the database and quality control of data occurred concurrent with data interpretation. Because of the complex nature of the field data, traditional log-normalization methods were not adequate. A method of normalization is described that is a modification of traditional methods, which overcomes the unique problems of the Fullerton Clear Fork reservoir.

  5. Page 77
    Abstract

    Estimating permeability from wireline logs has been difficult historically because of the large petrophysical heterogeneity typical of carbonate rocks. A simple relationship between porosity and permeability has not been observed, only between porosity, permeability, and pore size. In Clear Fork carbonates at Fullerton field, pore size is related to rock fabrics. Permeability was calcu-lated for each well using porosity from wireline logs and rock-fabric information from stratigraphic relationships. Permeability profiles, calculated using a global transform, compare well with core permeability values. An exception is in the lower section of the reservoir (Wichita Formation), where karst fabrics are present, suggesting a touching-vug pore system.

    Initial water saturation is required for estimating original oil in place and for flow simulation studies. Because most of the original wells in this field had very old log suites and the new wells were drilled after the advent of waterflooding, calculation of initial water saturation from wireline logs for most of these wells was not feasible. In this study, initial water saturations were calculated using capillary-pressure models generated for each petrophysical rock-fabric class. A generic rock-fabric model for class 1 fabrics was used, and new rock-fabric models were developed for class 2 and class 3 fabrics using the Thomeer approach. Water saturations calculated from capillary-pressure models show good agreement to saturations calculated using the Archie equation from wireline logs in intervals thought to be unflooded. The success of the rock-fabric-based method in calculating permeability and saturation in the Fullerton Clear Fork reservoir illustrates how valuable this technique can be in defining the petrophysical properties in carbonate reservoirs.

  6. Page 93
    Abstract

    Geology-guided reconditioning of seismic data is the key to improving extraction of relevant geologic information from three-dimensional (3-D) data volumes. In the Fullerton Clear Fork reservoir, the most convenient and useful tools for data reconditioning are phase shifting and high-frequency enhancement. A simple seismic phase rotation (to 90°) reconditions seismic data for impedance representation, roughly linking seismic amplitude directly to log lithology and porosity and making stratigraphic correlation more accurate. High-frequency enhancement raises the dominant frequency of 3-D seismic data from 30 to 50 Hz, improving seismic resolution without significantly deteriorating signal-to-noise ratio. More accurate and finer scale seismic mapping of reservoir parameters is achieved from model-based progressive inversion that seamlessly integrates geologic interpretation of well-derived seismic data and model-based seismic inversion for high-resolution (2 ft [0.6 m]) impedance models.

  7. Page 111
    Abstract

    Simulation studies and three-dimensional (3-D) reservoir modeling were conducted as part of an integrated geologie, petrophysical, and geophysical effort to better define the distribution of remaining oil and the opportunities for a more effective recovery of remaining hydrocarbons. Two 3-D reservoir models—a 2000-ac window model and a fieldwide model—were built using a cycle-based geologic framework and rock-fabric–dependent petrophysical properties. A comprehensive sensitivity study on volumetrics was conducted using the fieldwide model, and reservoir simulation was performed in a 1600-ac area in the window model.

    Original oil in place (OOIP) is a complex function of log-data quality, mapping parameters, vertical resolution of the 3-D grid, oil-water contact, and cutoff values in porosity, permeability, and water saturation. The high vertical-resolution 3-D model calculates higher OOIP than the 36-layer cycle-based model by 8 to 30%, depending on the cutoff criteria. Because permeability is a function of porosity and rock fabric, the permeability cutoff is equivalent to rock-fabric-dependent porosity or water saturation cutoffs and is less sensitive to grid vertical resolution than porosity and water saturation cutoffs.

    The simulation study was divided into two phases: sensitivity analysis and history matching. The sensitivity study was used to evaluate and rank the importance of reservoir parameters affecting production performance. During simulation, oil relative permeability for primary recovery has a strong effect on recovery from waterflooding. Because fractures and breccias are common in testing and core data, negative skin factors (or effective wellbore radii) were used to simulate near-wellbore fractures, and permeability values in the lower Wichita were modified to simulate karst-related breccias. Through history matching, optimal fluid and rock properties were determined.

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