Zulfiquar A. Reza

Lateral periodic variations in the petrophysical and geochemical properties of dolomite

Mississippian dolowackestones contain periodic oscillations in the lateral distribution of trace-element concentrations, porosity, and permeability. Random variations at #30 cm spacing account for 50%-70% of the total variability. The remainder of the variability occurs in short- and long-range oscillatory patterns with periods of 1.2-7.6 m, which can only be resolved by high-resolution sampling of an ;150 m lateral transect. Possible origins for these patterns are: (1) inheritance from the depositional precursor, (2) for- mation by self-organizing processes during dolomitization, or (3) overprinting by late dia- genesis. These oscillatory patterns have up to now been unrecognized, and addressing their origin and meaning(s) represents a new approach to the study of dolomites. Under- standing the lateral distribution of petrophysical properties can also improve models of fluid flow in dolomite petroleum reservoirs and contaminant transport between matrix and conduits in dolomite aquifers. Further, if 30%-50% of the variability in a geochemical attribute in any bed is due to lateral periodicity, one must ask if that variability is too great to assume a spot sample will be a suitable proxy for ancient geologic processes and conditions.

Reservoir-scale characterization and multiphase fluid-flow modelling of lateral petrophysical heterogeneity within dolomite facies of the Madison Formation, Sheep Canyon and Lysite Mountain, Wyoming, USA

Carbonate reservoirs often exhibit complex pore networks and various scales of petrophysical heterogeneity associated with stratigraphic cyclicity, facies distribution and diagenesis. In addition, petrophysical variability also exists within distinct rock fabrics at the interwell scale. Data from lateral transects through dolomitized carbonates of the Mississippian Madison Formation in north and central Wyoming exhibit three scales of lateral petrophysical variability. These include a near-random component (nugget effect), short-range variability and a long-range periodic trend (hole effect) that is observed in both dolowackestone (Sheep Canyon) and dolograinstone (Lysite Mountain) facies. The dolowackestone represents outer and middle ramp mud-supported fabrics, while the dolograinstone represents amalgamated skeletal and oolitic shoals. Detailed 3D petrophysical models of the dolomite facies and 2D multiphase waterflood simulations explore the effects of this heterogeneity on reservoir performance through several model scenarios. Fingering of the injected fluid front, sweep-efficiency, breakthrough time and bottom-hole well pressures are sensitive to lateral reservoir heterogeneity and rock fabric. Models with greater short-scale continuity of petrophysical properties have higher degrees of large-scale fingering, higher sweep efficiency and shorter breakthrough times. The reservoir performance of the dolowackestone differs from the dolograinstone for those models that exhibit a specific range of short-scale heterogeneity. In general, the dolowackestone has a higher degree of both small- and large-scale fingering, lower sweep efficiency and longer breakthrough time compared with the dolograinstone. Intra-facies scale variability is significant in regard to reservoir performance and is often difficult or impossible to determine from typical subsurface datasets. Information from outcrop analogues is necessary to create conceptual 3D geological models and to begin to quantify interwell heterogeneity within dolomite reservoirs.

ModDRE: A program to model deepwater-reservoir elements using geomorphic and stratigraphic constraints☆

Abstract In deepwater-reservoir modeling, the proper representation of the spatial distribution of architectural elements is important to account for pore-volume distribution and the connectivity of reservoir sand bodies. This is especially critical for rock and fluid-volume estimates, reservoir-performance predictions, and development-well planning. A new integrated stochastic reservoir-modeling approach (ModDRE—Modeling Deepwater Reservoir Elements) accounts for geomorphic and stratigraphic controls to generate the deepwater-reservoir architecture. Information on stratal-package evolution and sediment provenance can be integrated into the reservoir-modeling process. A slope-area analytical approach is implemented to account for topographical constraints on channel and sheet-form reservoir architectures and their distribution. Inferred sediment–source statistics and architectural-element variability (from seismic, outcrop, and stratigraphic studies) associated with relative changes in sea level can also be used to constrain the deepwater-reservoir-element statistics. Based on these geomorphic and stratigraphic constraints, deepwater-reservoir elements (channels, lobes) are built into the model sequentially (in stratigraphic order). Integration of realistic geological and engineering attributes into deepwater-reservoir models is vital for optimal reservoir management. This approach is unique in that it is more directly constrained to geomorphic and stratigraphic parameters than traditional object- or surface-based techniques for stochastic deepwater-reservoir modeling.

Deepwater Reservoir Modeling Using Sequence-Stratigraphic and Geomorphic Constraints

In deepwater-reservoir modeling, it is important to properly represent the spatial distribution of architectural elements to account for pore-volume distribution and the connectivity of reservoir sand bodies. This is especially critical for rock and fluid-volume estimates, reservoirperformance predictions, and development-well planning. This new integrated stochastic reservoirmodeling approach accounts for stratigraphic and geomorphic controls to generate the reservoir architecture. Information on stratal-package evolution and sediment provenance can be integrated into the reservoir-modeling process. A slope-area analytical approach is implemented to account for topographical constraints on channel and sheet-form reservoir architectures and their distribution. Inferred paleochannel direction statistics (from outcrop and stratigraphic studies) and simulated high-frequency eustatic sea-level curves are also used to constrain the architectural-element statistics. Based on these geomorphic and sedimentological constraints, architectural elements (channels, lobes, sheets) are built into the model sequentially (in age order). Integration of realistic geological and engineering attributes into numerical reservoir models is vital for optimal reservoir management. This approach is unique in that it is constrained more directly to geomorphic and sedimentological parameters than traditional object-based or surface-based techniques for stochastic deepwater reservoir modeling. Introduction Our understanding of the reservoir architecture of deepwater systems has improved with recent advances in imaging of the shallow and deep subsurface and through characterization with outcrop analogs. However, we do not have a complete knowledge of the subsurface environment, so a high degree of uncertainty remains when building deepwater-reservoir models. Stochasticmodeling approaches are useful because they provide a means of quantifying uncertainty through generation of multiple realizations of reservoir-property models. A number of stochastic modeling techniques are presently available for building deepwater reservoir models that can be broadly classified into three categories: (1) cellbased approaches that primarily implement two-point geostatistics, and more recently multipoint geostatistical concepts; (2) object-based or Boolean approaches have been used to build more geologically realistic reservoir models that incorporate nonlinear features. The geologic objects are conditioned to hard data (e.g. wells) and also honor stratigraphic relationships and interpretations; (3) stochastic surface-based techniques have been used to capture the compensational stacking tendency of flow-event deposits within deepwater lobes. In contrast to stochastic methods, processbased methods attempt to simulate fundamental geological processes to produce a numerical representation of the reservoir geology. These approaches include the rigor of the physics of sedimentation and depositional processes. However, enormous difficulties arise when it comes to conditioning process-based models to existing data (e.g., honoring well and seismic data). We introduce a novel approach to deepwater reservoir modeling that has aspects of process-based techniques but is also related to stochastic surfacebased methods. A combination of concepts is adopted in this approach to honor geomorphic and stratigraphic constraints. In this paper, geomorphic refers to bathymetry and parameters derived from bathymetry. To identify flow paths for deepwater channels and lobes, concepts from hypsometric analysis of channelized flow are incorporated. The spatial variability in deepwater architecture that is common within a sequencestratigraphic framework is incorporated through inputs SPE 95952 Deepwater Reservoir Modeling Using Sequence-Stratigraphic and Geomorphic Constraints M.J. Pranter, SPE, Z.A. Reza, SPE, and P. Weimer, U. of Colorado

Fluvial architecture of the Burro Canyon Formation using UAV-based photogrammetry and outcrop-based modeling: implications for reservoir performance, Rattlesnake Canyon, southwestern Piceance Basin, Colorado

The stratigraphic variability of fluvial architectural elements and their internal lithological and petrophysical heterogeneity influence static connectivity and fluid flow. Analysis of the fluvial architecture and facies heterogeneity of the Lower Cretaceous Burro Canyon Formation provides insight regarding their impact on reservoir performance. The Burro Canyon Formation as exposed in Rattlesnake Canyon, Colorado, forms stacked amalgamated and semi-amalgamated channel complexes that consist of amalgamated and isolated fluvial-bar channel deposits and floodplain fines, and represents a perennial, braidedfluvial system. Detailed two(2-D) and three-dimensional (3-D) static and dynamic reservoir models are constrained using stratigraphic measured sections, outcrop gamma-ray measurements, and Unmanned Aerial Vehicle (UAV)-based photogrammetry. Resulting breakthrough time and sweep efficiency suggest subsurface reservoir performance is most effective perpendicular to paleoflow direction in amalgamated channels. Perpendicular to paleoflow, breakthrough time is 9% shorter than parallel to the paleoflow and sweep efficiency is, on average, 16% greater due to greater sandstone connectivity in this orientation. Variability of preserved channels and lateral pitchouts results in lower recovery efficiency. Facies heterogeneity can account for 50% variation in breakthrough time and slightly lower recovery efficiency (5%). Cemented conglomerates that form channel lags above basal scour surfaces can also create fluid-flow barriers that increase breakthrough time and decrease sweep efficiency (25%) and recovery efficiency (22%).