Several challenges are associated with the characterization of low permeability reservoirs, most significantly for the enhance oil recovery operations. The scope of this work presents the integration of petrophysics data and its application in selection of the Microfrac intervals to measure downhole fracture-initiation pressures in multiple carbonate reservoirs located onshore about 50 km from Abu Dhabi city. The objective of characterizing formation breakdown across several reservoirs is to quantify the maximum gas and CO2 injection capacity on each reservoir layer for pressure maintenance and enhance oil recovery operations. This study also acquires pore pressure and fracture closure pressure measurements for calibrating the geomechanical in-situ stress model and far-field lateral strain boundary conditions. The case study concentrates on the multiple carbonate reservoirs that consists of a succession of clean limestone and intermittent dolomitic limestone. The complex carbonate lithology and fabric combined with low permeability presents a challenge to conventional logs and evaluation. Detailed integration of advanced and conventional logs (resistivity, neutron/density, advanced acoustic logs, Dielectric, NMR, Borehole image), Pressure testing & Sampling, Microfrac in-situ stress measurements and analysis plays a critical role in characterizing the reservoir properties and enhance oil recovery operations. Extensive data gathering is conducted with wireline suite, which covered Advanced Straddle Packer/Pressure Test & Sampling - Resistivity/Density/Neutron/Spectral GR – Acoustic logs – Resistivity Image – NMR – Dielectric technologies for reservoir properties of multiple carbonate reservoirs. The advanced acoustic analysis is performed in order to study elastic properties of the formation along with identifying transverse and azimuthal anisotropic intervals. The Geomechanical modeling is performed and stress profile is calculated to identify intervals with a stress contrast, which is important for the following stress measurement interval selection. The Microfrac in-situ stress measurements provide critical subsurface information to accurately predict wellbore stability, hydraulic fracture containment and CO2 injection capacity for effective enhance oil recovery within these reservoirs. The conventional logs, advanced logs, and Microfrac in-situ measurements and analysis enabled reservoir characterization and development plans for enhance oil recovery operations. The NMR technology provided lithology independent total porosity, permeability estimations and reservoir rock quality. Advanced multifrequency Dielectric measurement provided the fluid saturation in the invaded zone and textural parameters. Advanced Acoustic and image logs provided the geomechanical properties that enable to choose the best intervals for the following Microfrac stress measurement. Geomechanical workflow allowed identifying stress measurement intervals with a good stress contrast in multiple carbonate reservoir intervals. The data integration work illustrated in the paper is a key for any reservoir characterization that enabled property evaluation and successful Microfrac stress measurement. These measurements provide critical subsurface information to accurately predict wellbore stability, hydraulic fracture containment and CO2 injection capacity for effective enhance oil recovery within these reservoirs. This in-situ stress wellbore data represents the first of its kind in the field allowing petroleum and reservoir engineers to optimize the subsurface injection plans for efficient field developing.

The paper is continuation of our previous work published in the SPE-192896. This work illustrates horizontal well placement sensitivity analysis that was conducted on a complex Valanginian (Cretaceous) unsaturated oil carbonate reservoir with strong water drive. Existing producer wells are 80% horizontal and the remaining 20% are vertical to deviated producers. The production history is the approximately 20 years and currently a peripheral water injection is implemented, all injector wells are horizontals. The well placement is very challenging due to the presence of some thin high permeability streaks intervals with permeability value of up to 1 Darcy. Early water breakthrough encountered in the existing oil producers is a serious problem which results in lower recovery factor and costly lifting treatment. In addition, premature breakthrough would leave behind the potential oil accumulation. Therefore defining the optimum placement location of the producers is a crucial decision to be decided during well plan and field development. In this paper we applied novel approach for stochastically modeling complex carbonate reservoir lithofacies and properties distribution using a pre-defined High Resolution Sequence Stratigraphy (HRSS) model subzonation. The key static geological elements that must be well defined are HRSS framework, lithofacies architecture, and field wide rock properties. In this study, we apply integrated geosciences, geostatistical, and flow simulations to assess options for well placement. This new holistic approach has recently been successfully implemented in the studied field. The resulted geostatistical model was able to explain pressure depletion and production rate as shown in historical production data of the field. The resulting dynamic model will hence provide reliable production forecast and reservoirs development plan which will eventually allow accomplishing the mandate recovery target. Flow simulation was used to analyze the performance of the well considering horizontal the well azimuth, well inclination, wells length, wells position relative to the sequence stratigraphic zonation, and well position relative to the water contact. In addition, multi-scenarios of well placement were created to see the impact on the oil rate, plateau, and water breakthrough time. Some producers in the studied reservoirs have been drilled using the multidiscipline study recommendation. Actual property and rate derived from the newly drilled wells displayed a very reasonable match to the expected property from the model.

This paper described the novel approach for stochastically modeling complex carbonate reservoir lithofacies and properties distribution within a High Resolution Sequence Stratigraphy (HRSS) framework. The carbonate lithofacies discussed in this paper contains heterogeneous pore types and properties. The reservoir displays an extensive range of geologic and petrophysical properties that make the efficient recovery of hydrocarbons is a challenging task. Hence one of the key steps in improving the recovery factor is by defining the three dimensional variability patterns in the reservoir in the form of fine geocellular static model. The key static geological elements that must be well defined are HRSS framework, lithofacies architecture, and field wide rock properties. Subsurface analysis was done by examining 600 feet core footage from more than 15 wells, conventional logs from more than 50 wells, and more than 350 thin sections. The reservoir section averages 35 feet that can be subdivided into 6 high-frequency sequences. The reservoir consists of lagoonal packstone-rudstone, grain rich ooid-peloid shoal, and rudstone-boundstone mid-ramp. The shoal deposits exhibit the best permeability and oil saturation and it consists of discontinuous lithofacies body that depicts locally excellent porosity and permeability characteristics. Lithofacies geometry and properties studies must form a fundamental basis for characterizing and modeling HRSS framework and lithofacies architecture variability through the reservoir. Combined with wireline-log data, they provide a basis for defining both reservoir framework and rock attribute distributions. Complex lithofacies geometries and transitions, both vertically and laterally between the mound and discontinuous grain-rich ooid-peloid shoal lithofacies together with the continuous and sequential lagoonal and mid-ramp lithofacies does not allow to simulate these sorts of lithofacies assemblage using single lithofacies model algorithm. Hence a new holistic approach was implemented. A combination of Object Based (OB) algorithm and Truncated Gaussian Simulation (TGS) algorithm was employed to handle the complex lithofacies transition. This enables generating multiple realistic field wide lithofacies distribution and relationship which aligns with data trend, subsurface analog in the nearby fields, as well as that is from the outcrop exposure. The established lithofacies distribution within HRSS framework was then used to constrain field-wide properties and diagenetic trend and distribution in the reservoir. This new holistic approach has recently been successfully implemented in the studied field. The resulted geostatistical model was able to explain pressure depletion and production rate as shown in historical production data of the field. The resulting dynamic model will hence provide reliable production forecast and reservoirs development plan which will eventually allow accomplishing the mandate recovery target.