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 objective of this paper is to present a unique Petrophysical Grouping (PG) approach in a carbonate reservoir located in transition zone. It is very challenging, especially in Carbonate reservoirs, exist in transition zone, to establish PG definitions due to the complexities result from reservoir heterogeneities and diagenesis. Consequently establishing a suitable Saturation Height Function to match the Log derived Saturation is another challenge. In addition, the limited coverage of Mercury Injection based Capillary Pressure data (MICP) as compared to Routine Core analysis (RCA) data provides difficulties in establishing appropriate PG definition. In first step the MICP data was used together with porosity/permeability to define distinctive groups. The PGs were further up-scaled using deterministic and Neural Network (NN) approaches. The best method was chosen by performing a test that compares the Washburn Pore Throat Radius (PTR) with the predicted PTR. To estimate a most representative log based permeability model, independent of water saturation a NN and Self-Organization Map methodologies were adapted. The limitations of MICP samples were handled by using an analog of a larger field with 100s of MICP samples. This was used to propagate the PGs to log domain by utilizing the permeability model. Five PGs were defined using deterministic approach in which the best one is characterized having low displacement pressure, low irreducible water saturation, high pore throat radius and high porosity and permeability responses. Winland was shortlisted after testing other methods as the most applicable PG method in the reservoir as it provides the best correlation with lab PTR (94%) and the shape of WR35, consequently provides good match with computed Sw log and the shape of the PRT curve (Gunter, 2017). Regardless of the good response of NN approach the method was not chosen due to limitation of MICP data. A good relationship of Winland based PGs were found with geology and associated facies indicate strong affinity with the depositional environment and diagenetic overprints on each existing facie associations, hence a permeability model is depicted with confidence. The permeability model was executed for two geographic sectors using density, neutron porosity and GR as main inputs. SOM and NN Permeability were blind tested which resulted in more than 80% match. The predicted Sw matches with log based Sw over the entire field thus the PGs definition and propagation to log domain are considered valid.