Connectivity represents one of the fundamental properties of a reservoir that directly affects recovery. If a portion of the reservoir is not connected to a well, it cannot be drained. Geobody or sandbody connectivity is defined as the percentage of the reservoir that is connected, and reservoir connectivity is defined as the percentage of the reservoir that is connected to wells. Previous studies have mostly considered mathematical, physical and engineering aspects of connectivity. In the current study, the stratigraphy of connectivity is characterized using simple, 3D geostatistical models. Based on these modelling studies, stratigraphic connectivity is good, usually greater than 90%, if the net: gross ratio, or sand fraction, is greater than about 30%. At net: gross values less than 30%, there is a rapid diminishment of connectivity as a function of net: gross. This behaviour between net: gross and connectivity defines a characteristic ‘S-curve’, in which the connectivity is high for net: gross values above 30%, then diminishes rapidly and approaches 0. Well configuration factors that can influence reservoir connectivity are well density, well orientation (vertical or horizontal; horizontal parallel to channels or perpendicular) and length of completion zones. Reservoir connectivity as a function of net: gross can be improved by several factors: presence of overbank sandy facies, deposition of channels in a channel belt, deposition of channels with high width/thickness ratios, and deposition of channels during variable floodplain aggradation rates. Connectivity can be reduced substantially in two-dimensional reservoirs, in map view or in cross-section, by volume support effects and by stratigraphic heterogeneities. It is well known that in two dimensions, the cascade zone for the ‘S-curve’ of net: gross plotted against connectivity occurs at about 60% net: gross. Generalizing this knowledge, any time that a reservoir can be regarded as ‘two-dimensional’, connectivity should follow the 2D ‘S-curve’. For channelized reservoirs in map view, this occurs with straight, parallel channels. This 2D effect can also occur in layered reservoirs, where thin channelized sheets are separated vertically by sealing mudstone horizons. Evidence of transitional 2D to 3D behaviour is presented in this study. As the gross rock volume of a reservoir is reduced (for example, by fault compartmentalization) relative to the size of the depositional element (for example, the channel body), there are fewer potential connecting pathways. Lack of support volume creates additional uncertainty in connectivity and may substantially reduce connectivity. Connectivity can also be reduced by continuous mudstone drapes along the base of channel surfaces, by mudstone beds that are continuous within channel deposits, or muddy inclined heterolithic stratification. Finally, connectivity can be reduced by ‘compensational’ stacking of channel deposits, in which channels avoid amalgamating with other channel deposits. Other factors have been studied to address impact on connectivity, including modelling program type, presence of shale-filled channels and nested hierarchical modelling. Most of the stratigraphic factors that affect reservoir connectivity can be addressed by careful geological studies of available core, well log and seismic data. Remaining uncertainty can be addressed by constructing 3D geological models.
Static descriptive measures can be used to quantify characteristics of a 3D reservoir model. These static measures may have implications for the prediction or interpretation of dynamic performance and can draw attention to geological uncertainties that may impact flow behaviours. This study reviews, modifies and introduces techniques to characterize the spatial distribution of permeability in reservoir models, with emphasis placed on connectivity and continuity analysis. Topics include: the relationship between connectivity and percolation theory; definition of types of reservoir connectivity; methods of measuring connectivity; connectivity as a function of distance; connectivity maps; categorical classifications of connectivity; types of reservoir path lengths; and continuity lines. The key factors controlling reservoir connectivity are identified. Static measures can be used to locate regions of higher sweep efficiency and lower tortuosity that are connected to the wells.
To address uncertainty, models created for appraisal and development studies try to capture the full range of possible rock and fluid properties, and reservoir and structural architecture. Using experimental designs, each parameter can be varied to indicate how uncertainty for the parameter affects the outcome (for example, recovery after 30 years). In numerous models in appraisal and development studies, stratigraphic or reservoir architecture is not recognized as a significant uncertainty. This is a concern for two reasons. First, reservoir architecture is known to be an important parameter influencing oil production. It is puzzling that experimental design studies indicate it is not a significant uncertainty. Second, building geologically realistic earth models can involve months of time and can impact timelines for development projects. If reservoir architecture is in fact a non-significant uncertainty, perhaps detailed modelling could be postponed. The current study addresses in what situations reservoir architecture is important in appraisal and development studies. Reservoir architecture characteristics considered are net to gross, channel orientation, channel stacking pattern, channel sinuosity, channel width/thickness, type of architectural element, influence of shale units within channel fills, influence of channel drapes at the base of channels, presence of other facies, influence of valley fills, and sheet geometries. Two field characterizations were studied using the same workflow, and results are compared with results of conceptual modelling studies.For studies of recovery uncertainty, it is shown here that models that look to be very different may have similar dynamic performances because of similar reservoir connectivities and path lengths. Moreover, it is shown that the elements of reservoir architecture investigated (channel width/thickness ratio, sinuosity, orientation, thickness, element type) do not control recovery efficiency to a large degree unless reservoir connectivity is impacted. Reservoir architecture may not be an important uncertainty in appraisal and development studies unless reservoir connectivity or tortuosity are affected. Although reservoir architecture may not represent a key uncertainty in appraisal and development studies, it may well be a significant uncertainty for well planning in mature fields.
The connectivity of a reservoir to a well-bore represents a fundamental initial condition for drainage of an oil or gas field. The size of the static connected volume is a function of the stratigraphic and structural architecture of the reservoir. The most important stratigraphic factor affecting connectivity is a net-to-gross threshold which determines whether a reservoir is highly or poorly connected. Other stratigraphic factors affecting connectivity are those that impact the reservoir dimensionality (for example, compartmentalizing continuous mudstones or parallel channel deposits) and the size of geobodies relative to the total reservoir size. Structural compartmentalization may cause fault compartments that are too small in volume to support reservoir connectivity: as the size of the geobodies approaches compartment size, connectivity is typically less predictable. Static connected volumes alone do not predict flow performance, but are a component in predicting flow performance. To more completely address predictions of flow performance, dynamic connectivity is sometimes considered. However, dynamic connectivity, which is dependent on fluid type, permeability heterogeneity, time and other factors, confuses connectivity with tortuosity and sweep- and displacement-efficiency and is probably best avoided. Finally a connectivity flow diagram is proposed as a guide to help formulate key questions concerning uncertain reservoir parameters affecting reservoir connectivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.