As the demand for natural gas is increasing, the exploration and appraisal activities for unconventional gas resources is expanding and becoming significant to fulfill the global demand. These Unconventional resources are known to have complex geochemistry and rock physics. Understanding the complex nature of unconventional rocks is challenging and requires comprehensive integration with an advanced reservoir characterization approach. In this study, a comprehensive integrated rock characterization workflow was designed to understand the challenges and uncertainties associated with the Diyab Formation unconventional rocks. More than 800 ft of unconventional cores were analyzed to characterize the Jurassic carbonate succession of Jubaila, Hanifa and Tuwaiq Mountain Formations through an integrated workflow. The workflow includes core and OH logs based initial rock classification through machine learning known as "Heterogeneous Rock Analysis" (HRA). Based on HRA, the samples selection for Unconventional and advanced Geomechanical core analysis was applied, followed by core data interpretation, core to logs integration and refining reservoir quality. Unconventional and advanced core analysis in this workflow include but not limited to following types, liquid TRA, TOC, HAWK, Vitrinite Reflectance (VR), Core-NMR T2, MICP, 2D/3D SEM, Dean Stark, XRD/XRF, Geomechanics (Brazil Tensile Strength, Unconfined Compression (UCS), Single (TXC) and Multi Stage Triaxial (MTXC), Multi-Stress Compression (MSC), Biot coefficient test), etc. Core analysis results were interpreted and integrated with the logs to better understand and characterize the unconventional reservoir qualities. Sample selection was performed using all available data, to capture the variations in petrophysics as well as geomechanics and geochemistry, particularly organic matter content, and mineralogy within each identified petrophysical rock class. Core logs, plug analysis, and wireline data have been integrated and generally showed excellent agreement within the range of associated uncertainties, which can be attributed to rock tightness and resolution variations. Geochemistry (TOC, HAWK & VR) shows high concentration of kerogen, initially of type IIS but presently with low HI in which maturity reflects the dry gas window and possible condensate. Porosity ranges from 2.7% to 8% with a maximum reading reported from MICP data. The 2D & 3D SEM images provided some key findings, associated with different porosities either connected, isolated and/or organic matter porosity systems in given samples. These complex porosities systems cannot be captured by only conventional methods. The organic type of porosity is important as it provides further support to matrix porosity connectivity. Integrating this knowledge with logs, geochemistry, petrophysics and mineralogy helped to refine the initial characterized rock properties. In addition, the geomechanical understanding took the integration step further to identify potential zones for fracking and testing based on the classified stress regime.

The development of unconventional target in the Shilaif formation is in line with the Unconventional objective towards adding to ADNOC reserves. For future optimization of development plans, it is of utmost importance to understand and test and therefore prove the productivity of the future Unconventional Horizontal Oil wells. The Shilaif formation was deposited in a deeper water intrashelf basin with thicknesses varying from 600 to 800 ft from deep basin to slope respectively. The formation is subdivided into 3 main composite sequences each with separate source and clean tight carbonates. The well under consideration (Well A-V for the vertical pilot and Well A-H for the horizontal wellbore) was drilled on purpose in a deep synclinal area to access the best possible oil generation and maturity in these shale Oil plays. Due to the stacked nature of these thick high-quality reservoirs, a pilot well is drilled to perform reservoir characterization and test hydrocarbon type and potential from each bench. Fracturing and testing are performed in each reservoir layer for the primary purpose to evaluate and collect key fracturing and reservoir parameter required to calibrate petrophysical and geomechanical model, landing target optimization and ultimately for the design of the development plan of this stacked play. Frac height, reservoir fluid composition and deliverability, pore pressure are among key data collected. The landing point selected based on the comprehensive unconventional core analysis integrated with petrophysical and geomechanical outcomes using post vertical frac and test results. Well A-H was drilled as a sidetrack from the pilot hole Well A-V. This lateral section was logged with LWD Triple Combo while Resistivity Image was acquired on WL. Based on the logging data the well stayed in the target Layer / formation, cutting analysis data for XRD and TOC was integrated with the petrophysical results in A-H well. Production test results from subject were among the highest rate seen during exploration and appraisal of this unconventional oil plays and compete with the current commercial top tier analog unconventional oil plays. Achieving those results in such early exploration phases is huge milestone for ADNOC unconventional exploration journey in UAE and sign of promising future development.

Bedding-plane slip effects during hydraulic fracturing have recently gained interest in unconventional plays due to their influence in hydraulic fracture growth in vertical and horizontal directions. However, most of the current workflows cannot fully model field-scale sub-horizontal orientation of bedding planes because of complications with gridding techniques, or due to simplifications related to the use of 2D models. These challenges have motivated the assessment of 3D bedding plane interactions on well performance using the embedded discrete fracture model (EDFM) technology for field case scenarios. An efficient hydraulic fracture propagation model is used to model hydraulic fracture growth in the presence of bedding layers. The model captures shear slippage at the bedding layer interfaces and corrects the calculated stress intensity factor to account for height containment. A hydraulic fracture model, constrained by geomechanical information, is built in a corner point grid. Resulting hydraulic fracture geometries and identified bedding layer fractures are transferred to EDFM by using a 3D bedding plane generator, which places sub-horizontal polygons across the well trajectory, honoring its orientation and geometry. To locate the spatial position of bedding layers, geostatistical constrains, core analysis and petrophysical interpretations – including well image logs – can be taken into account. Lastly, a reservoir simulation model is built to evaluate the effects of bedding planes on well performance. 3D effects of bedding planes in a shale gas reservoir were captured in a field case scenario using numerical models. Higher contribution to production was observed in the results of this study. The main reasons are larger fracture lengths generated along the pay zone caused by bedding plane influence in the fracture propagation process and shear slippage along bedding plane fractures, which create a larger effective conductive surface area. When modeling bedding planes, computational efficiency is substantial due to the EDFM method, preserving spatial orientation and geometry of each bedding plane. Direct assessment of bedding plane properties is provided, which highlights the importance of capturing their interactions with hydraulic fracture growth and well performance. A seamless integration of bedding plane models can be achieved in an efficient workflow that provides key lessons for future fracture design and well spacing optimization.

Multi-stage hydraulic fracturing has recently gained strong interest in unconventional plays in the Middle East due to high natural gas production potential. However, prevalent characteristics of the area, including high-pressure / high-temperature (HPHT) conditions and presence of complex natural fracture networks, pose significant challenges to reservoir characterization. These challenges have motivated the development of an integrated workflow using microseismic data for the characterization of reservoir properties resulting from the interaction between natural and hydraulic fractures. This study proposes a reliable method for modeling hydraulic fractures from scarce microseismic data. Initially, a microseismic model—based on field records of microseismic data and natural fracture spatial characterization—was developed. Issues related to limited microseismic data availability were tackled through combination of a probabilistic algorithm, Gaussian Mixture Model, and a DFN model. Then, the resulting synthetic microseismic events enabled the generation of a hydraulic fracture model using the embedded discrete fracture model (EDFM) and an in-house microseismic spatial density algorithm that captured major hydraulic fracture growth tendencies. Next, the created hydraulic fracture geometries were validated against a physics-based hydraulic fracture propagation model. Lastly, a single-well sector model—based on a corner point grid that honored the original 3D discrete fracture network (DFN)—was history matched, confirming the successful application of the proposed methodology.

ADCO started its unconventional exploration campaign in 2012 targeting the tight carbonate sequences known as Wasia Group, onshore Abu Dhabi. A front-end loaded data gathering strategy was employed to acquire extensive latest generation logging data tailored for unconventional reservoirs. In a number of wells the entire reservoir section was cored, often up to 800 ft per well, leading to more than 3000 ft of core retrieved to date. ADCO applied unconventional core analysis technologies, such as retort analysis, to generate the optimal core results. Key parameters such as effective porosity, pore size distribution, TOC, source rock maturity, mineral compositions and fluid saturations were determined from logs and core data (where available). This paper will focus on the petrophysical challenges during the evaluation of the Wasia Group. We will demonstrate that conventional core analysis techniques have only limited applicability, whereas core analysis techniques designed specifically for unconventionals provide more relevant results. A log analysis methodology centered on the application and importance of NMR in unconventional liquid plays is presented. Porosity data measured through retort analysis provide an excellent fit to NMR log-based porosity measurements. Conventional core analysis results generated a poor fit to log porosity, and the resulting values exhibited scatter with a large standard deviation. T2 distribution from NMR log data suggests the presence of large pores with good fluid mobility, which requires confirmation through formation testing or production. Log data-derived rock typing was performed. It is based on principal component analysis of the reservoir section. Rock classification may help in selecting suitable zones for hydraulic fracture initiation. Lessons learned from the initial wells for core recovery and analysis techniques are summarized below and have been implemented in later wells: –Preserve part of the core for robust saturation measurements.–Stop acquisition of conventional poro-perm data–Focus on unconventional-specific retort-based techniques for core petrophysics–Focus on pulse decay permeabilities–Use scratch test to aid in core analysis sample selection process, especially for rock mechanics–Add core T1/T2 NMR and MICP to future core analysis programs The complete integration of core and log data has allowed for a thorough assessment of the unconventional hydrocarbon potential within the ADCO concession.