Abstract Channel stacking pattern in deepwater reservoirs has a significant impact on reservoir producibility. These stacking patterns are the result of feedbacks between turbidity currents and associated supply variations and the evolution and aggradation of slope physiography. Turbidite flow events that leave significant physiographic relief due to underfilled within-channel deposition or local erosion tend to have greater influence on subsequent flow events, resulting in organized channel stacking patterns. Turbidite flow events that fill their channels do not confine subsequent flows and result in disorganized channel stacking patterns. High rates of system aggradation result in a greater degree of inter-element disconnection, low rates result in amalgamated elements. Event-based models are amenable to the integration of expert rules related to the influence of channel fill (fraction of active channel fill) and aggradation rate on channel stacking pattern. The event-based approach is part of a new subset of geostatistical modeling that focuses on greater integration of stratigraphic concepts and sedimentological process. In the event-based method stochastic models are constructed as a sequence of depositional events. The sedimentological process and allogenic forcing are approximated as a set of empirical and predictive rules. The resulting numerical laboratory efficiently constructs high-resolution reservoir models and allows calibration of model response to changes in input values. Event-based models are constructed based in part on outcrop examples with various channel stacking patterns. The resulting models are used to explore the relationship between stacking pattern, preservation potential of axis, off-axis and margin facies assemblages and reservoir producibility. In addition, these models can be used to illustrate hierarchical relationships, explore larger issues related to the value of architectural information and to aid in the discovery of new rules by induction combining outcrop observations and models results.

Abstract Studies of turbidite channel complexes in outcrops, wells, and 3D seismic-reflection data suggest a general model of turbidite channel behavior related to three critical measures: (1) the thickness of channel elements; (2)the thickness of abandonment facies within each element; and (3) the thickness of overbank aggradation. These measures constrain channel stacking pattern and can be integrated into event-based geostatistical reservoir models that provide probabilistic predictions of net reservoir volume and element stacking pattern. Although channel and overbank thicknesses are measured routinely, this model provides a predictive framework that also emphasizes the importance of recognizing the presence and thickness of shale-rich abandonment facies at the top of sand-rich channel elements in outcrops. For a given flow composition, the deposits of thick channel elements (thickness of active fill plus abandonment facies) tend to have relatively low sand percentage, abundant bypass facies, and thick abandonment facies (underfilled channels). Underfilled channel elements with high topographic relief, from levee crest to channel thalweg, at the time of abandonment influence the location of subsequent elements, resulting in an organized channel stacking pattern. The deposits of relatively thin channel elements tend to have higher sand percentage, small volumes of bypass facies and thin/absent abandonment facies. Filled channel elements with low topographic relief at the time of abandonment had little influence on the location of subsequent elements, which resulted in a disorganized channel stacking pattern. Channel ‘‘relief ’’ corresponds to the depth of erosion plus the height of the levee crest above the initial sea floor. We observe that erosion relief can correlate strongly with downslope gradient. Flow composition also is critical because the rate of overbank aggradation is strongly influenced by mud volume. Muddy flows tend to produce thick overbank aggradation, high confinement, and under-filled channels with an organized stacking pattern. Sand-rich flows tend to produce relatively low overbank aggradation, low confinement (unless erosion relief is high), and filled channels with a disorganized stacking pattern.

Abstract Geostatistics is often used to build multiple models of reservoir geological heterogeneity for the probabilistic assessment of reservoir flow response. Current geostatistical algorithms, object-based or pixel-based, using semivariograms or training images, enable the reproduction of spatial statistics inferred from available conditioning data and analogs but rarely integrate information related to depositional processes. Indeed, because conventional geostatistical models are constructed without any concept of time or depositional sequence, their ability to incorporate sedimentological rules, which explain facies geobodies interactions and intra-body porosity/permeability heterogeneity, is quite limited. One consequence of such a limitation is that, unless spatial constraints tediously derived from alternative depositional interpretations are explicitly imposed to the simulation, conventional geostatistical methods only generate stationary statistical models that may not be representative of the full range of actual reservoir heterogeneity uncertainty. Recently, the event-based approach has been introduced recently as a new branch of geostatistics, in which stochastic models are constructed as a sequence of depositional events. The sedimentological process is incorporated as a set of numerical rules that control architectural element geometry and the sequence of events through the occurrence of avulsion, meander migration, progradation, retrogradation, and aggradation. In addition, event-based models can be conditioned to sparse well data and soft data (seismic), typically available in deep-water systems. The integration of sedimentological process into geostatistical modeling may provide a more geologically realistic representation of reservoir heterogeneity and help better assess reservoir flow response. Also, event-based geostatistics may be applied as a new framework to test distilled sedimentological rules and analyze their impact on reservoir heterogeneity.

Abstract Analysis of modern depositional systems, high-resolution seismic and outcrop data reveal a significant degree of complexity in the heterogeneity associated with deep water distributary lobes. These heterogeneities commonly have a significant influence on reservoir performance. This complexity is the result of variations in sand body architectures related to varying depositional and erosional processes. The translation of these processes into quantitative rules is a powerful exercise for the purpose of testing our understanding of deposi-tional processes and hence forming predictive geologic models. Yet, the influence of coupled rules is difficult to assess a priori due to feedbacks and interference. A computationally efficient and intuitive quantitative framework is, therefore, a valuable means to explore potential rules and their associated interactions. In the event-based framework, architectural elements are assigned to forward-simulated flow-event paths that obey simple geologic rules. The geologic rules qualitatively relate to sedimentary processes and constrain the geometry and location of architectural elements given the current state of the model for any time step. Rules may be coded to model allogenic and autogenic sedimentary processes such as avulsion, aggradation, progradation, retrogradation, and meander migration, along with the evolving influence of gradient and accommodation. Thus, event-based models can aid in the empirical testing of quantitative rules. This exercise leads to an improved quantitative understanding of process and the construction of more accurate geologic models that may better predict reservoir performance of these often economically challenging developments.