Studies of Quaternary extensional faults indicate that they have instantaneous amounts of throw (0AE4 to 4 m), average slip rates (0AE05 to 2AE8 m kyr )1 ) and frequency of recurrence (<40 000 years) accounting for the accommodation space required for the accumulation of peritidal carbonate parasequences (PCPs). Hangingwall sites and graben are characterized by fault downdropping together with regional subsidence, and footwall sites and horsts by fault-related uplift alternating with periods of regional subsidence. The relative sea-level curves generated by these processes operating in a maritime rift setting are used as inputs to a forward stratigraphic modelling program SedTec2000 to simulate how fault-related changes in accommodation space can account for high-frequency PCP formation. Each instantaneous fault slip generates a flooding surface or aggradation in hangingwall and graben settings. High-frequency cycles in hangingwall sites are either symmetric (deepening then shallowing upward) or asymmetric (shallowing-upward). The major factor controlling cycle types is the balance between rates of carbonate accumulation and generation of accomodation space. High-frequency cycles in footwall sites and horsts comprise shallow subtidal facies, with no distinctive bathymetric trends, capped by erosional boundaries generated by footwall uplift. The modelled cycles are of the same thickness, with bathymetric trends and frequency to cycles commonly interpreted to be due to orbitally driven eustatic sea-level changes or autocyclic processes. These numerical experiments demonstrate that high-frequency PCPs can be generated by tectonic, fault-related processes, a hypothesis that is frequently discounted.

A Lower Cretaceous reservoir in one of the Abu Dhabi onshore oilfields is the focus of this study aimed 1) to understand, predict and distribute the impact of diagenesis on the reservoir quality, and 2) to define the reservoir Static Rock Types (SRT). This will eventually help to define and predict the reservoir flow units to better frame strategies and choices for reservoir static and dynamic modelling, and to support the decision-making process for the oilfield business plan. A fully integrated geological-petrophysical approach was used to carry out the study. Nine geological facies are recognized in the reservoir and grouped in four main reservoir facies categories: 1) rudist-bearing facies, 2) grain-supported skeletal and Orbitolinid facies, 3) Bacinella/Lithocodium-coral facies, and 4) mudstone-supported facies. Rudist-bearing and Bacinella/Lithocodium-coral facies represent the best reservoir facies. Rudist deposits mainly formed stacked patches- or sheet-like accumulations of reworked skeletal debris on platform top settings in the northeast of the field. In the main reservoir section, geological facies distribution mainly follows the hydrodynamic trend of the depositional settings. Rudist facies properties primarily depend on the depositional texture and the original shell mineralogy and structure (e.g. Caprinids vs. Caprotinids-Requienids). Bacinella/Lithocodium-coral deposits form stacked shallowing-up peritidal cycles, representing the genetic units of the lower section of the reservoir. Evidences of epikarst in the uppermost cycles indicate the location of a major sequence boundary correlatable also to neighboring fields. The impact of diagenesis appears strongly driven by the depositional facies characteristics, and a paragenetic sequence is proposed for this reservoir. A link between geological facies features, including original grain mineralogy and depositional settings, and reservoir quality parameters is established, allowing the prediction and distribution of reservoir properties in the reservoir laterally and stratigraphically. Seven SRTs are identified by integrating geological observations and the result of the petrophysical synthesis. SRTs definition closely follows the reservoir stratigraphic framework, allowing creating a two-fold scheme: two SRTs characterize the cyclic peritidal deposits of the Bacinella/Lithocodium-coral section, and five SRTs are identified in the upper rudist-rich section. Petrophysical evidences from MICP data also strongly support this approach. A refined geological concept and stratigraphic framework is proposed for the reservoir to integrate the results of the sedimentological/petrographic analysis and petrophysical synthesis. Through linking geology and petrophysics, a new robust scheme of SRTs is created to enhance the identification and prediction of the reservoir flow units.

The Lower Cretaceous carbonates of the Shuaiba Formation forms one of the most prolific carbonate reservoirs in the region. These carbonates were deposited on a shallow epeiric carbonate platform during the Aptian. In addition, intra-shelf basins formed on this vast platform where deeper and more restricted carbonates were deposited. As a result of a long term relative sea-level fall these carbonates started to prograde into the intra-shelfal Bab Basin. The platform ultimately diminished during exposure of the Shuaiba platform and subsequent flooding and the deposition of deeper water carbonates and clastics of the Nahr Umr Formation. The observations described here concentrate on the sequence stratigraphy of the shallow carbonate platform top carbonates in outcrop and the subsurface. The internal succession of the Shuaiba Formation can be briefly described in core and outcrop as follows: The Shuaiba Formation has been deposited on top of the deeper-water carbonates of the Hawar member, which terminated the Kharaib platform. Based on core evidence from several Abu Dhabi oilfields, the Lower Shuaiba Fm. is composed of two depositional cycles composed of Orbitolina wackestones shallowing upward into Lithocodium/Bacinella floatstones (Aptian 1). The succession is overlain by deeper water Orbitolina and foraminiferal wackestones/packstones and in parts contains planktonic foraminifera. Overlying this succession are shallowing-upward sequences with Lithocodium/Bacinella floatstones passing to Lithocodium/Bacinella rudstones or bindstones with stromatoporoids and corals (Aptian 2). The Aptian 2 section is bound by a prominent breccia that can be mapped in the subsurface around the Bab basin. The breccia shows angular clasts, vugs, and in places late stage calcite and dolomite cement rimming (or filling) the pore space. In parts, breccia clasts have been incrusted by stromatoporoids and Lithocodium/Bacinella after renewed flooding. This breccia has all the characteristics of a solution collapse breccia and is the result of a major drop in relative sea-level on the platform. In outcrop (400 km away from the subsurface analogue) an intraclast breccia is observed at the same stratigraphic position and can be traced kilometers along the mountain front in some wadis in the northern emirate of Ras Al Khaimah. This unit displays evidence of exposure and reworking and in areas intense pervasive later cementation. Overlying the Aptian 2 sequence boundary, the Aptian 3 succession has dominant Lithocodium/Bacinella floatstones and locally intercalated rudist floatstones suggesting a renewed deepening. Above, the section passes to massive rudist floatstones and rudstones containing mainly Caprinid, Myophorid and Caprotinid rudists and downlapping in outcrop onto the Lithocodium/Bacinella section (Aptian 3). At the base of the massive rudist section another breccia is exposed incorporating clasts of the underlying and overlying material. In contrast to the first breccia, this breccia displays evidence of mechanical effects involving fluidization, pressure containment/release, and development of pipe-shaped features connected to the parent bed. Internal clasts display angularity with variably weak to strong lithification. The top of the rudist section is represented by a sequence boundary characterized by significant stylolitization and sharp facies change. The upper part of the section is characterized by an alternation of skeletal, peloidal, Orbitolina, algal and rudist floatstones with intercalated mudstones (Aptian 4 and Aptian 5). Close to the contact to the Nahr Umr borings and pyrite nodules are prominent suggesting multiple stacked exposure surfaces leading to the ultimate unconformity on the top of the Shuaiba Platform. Establishing a sequence stratigraphic framework on shallow carbonate platforms heavily relies on identifying sequence boundaries (SBs), which are the best preserved surfaces recognized in these platform settings. Deposits as a result of maximum flooding surfaces are often not distinct since bathymetry was never deep enough on shallow-water platforms to deposit deep water carbonate mudstones and shales. The two most recognizable sequence boundaries for the Shuaiba Fm., indicating widespread regional exposure, are: the solution collapse breccia on top of the Aptian 2 algal section; and at the top of the Shuaiba formation at the contact with the Albian-aged Nahr Umr Formation. Both can be correlated basin-scale over 100s of kilometers between the subsurface and outcrop. More subtle SBs are defined by abrupt facies shifts at the contact of shallowing upward trends and overlain by deeper water deposits. These are positioned in the lower Shuaiba at the top of the two - Orbitolina-algal floatstone cycles, and in the Upper Shuaiba on top of the rudist section. Maximum flooding surfaces are more subtle and have been placed where we have indication of either significant deeper-water deposition in the lower Shuaiba (e.g. Orbitolina and foraminiferal wackestones/packstones with planktonics) or at the contact of slightly deeper facies (algal) to shallower facies (rudist). This interpretation follows common sequence stratigraphic rules and helps to better understand the laterally extensive water break-through zones in producing fields. Consequently, some of the previous interpretations on the Shuaiba shallow platform top carbonates require reconsideration.

The aim of this study is to demonstrate the value of a fully integrated ensemble-based modeling approach for an onshore field in Abu Dhabi. Model uncertainties are included in both static and dynamic domains and valuable insights are achieved in record time of nine-weeks with very promising results. Workflows are established to honor the recommended static and dynamic modeling processes suited to the complexity of the field. Realistic sedimentological, structural and dynamic reservoir parameter uncertainties are identified and propagated to obtain realistic variability in the reservoir simulator response. These integrated workflows are used to generate an ensemble of equi-probable reservoir models. All realizations in the ensemble are then history-matched simultaneously before carrying out the production predictions using the entire ensemble. Analysis of the updates made during the history-matching process demonstrates valuable insights to the reservoir such as the presence of enhanced permeability streaks. These represent a challenge in the explicit modeling process due to the complex responses on the well log profiles. However, results analysis of the history matched ensemble shows that the location of high permeability updates generated by the history matching process is consistent with geological observations of enhanced permeability streaks in cores and the sequence stratigraphic framework. Additionally, post processing of available PLT data as a blind test show trends of fluid flow along horizontal wells are well captured, increasing confidence in the geologic consistency of the ensemble of models. This modeling approach provides an ensemble of history- matched reservoir models having an excellent match for both field and individual wells’ observed field production data. Furthermore, with the recommended modeling workflows, the generated models are geologically consistent and honor inherent correlations in the input data. Forecast of this ensemble of models enables realistic uncertainties in dynamic responses to be quantified, providing insights for informed reservoir management decisions and risk mitigation. Analysis of forecasted ensemble dynamic responses help evaluating performance of existing infill targets and delineate new infill targets while understanding the associated risks under both static and dynamic uncertainty. Repeatable workflows allow incorporation of new data in a robust manner and accelerates time from model building to decision making.

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