The studied Fields cover about 1900 sq km covering fourteen wells in Abu Dhabi, UAE. It was discovered in 1962 and developed by Abu Dhabi Petroleum Company. The objective of the current study is to illustrate the comparison between prestack stochastic & prestack deterministic seismic inversion results to better understand vertical and lateral heterogeneities of upper Jurassic reservoirs and their impact on property distribution during static modelling and further into dynamic model construction.

Abstract

Sandstone reservoirs of the South Caspian basin in Turkmenistan are currently undergoing further development—with the addition of deviated wells. The localized depletion occurring in some of the offshore fields in this area has thus far triggered a host of geomechanics-related challenges—including wellbore instabilities and poor hole quality. In anticipation of further depletion over the remaining fields life, geomechanics effects will become more pronounced and the associated technical and economic challenges facing these fields may increase. To assist in future well planning and field development, and to diagnose the problems already encountered in the existing vertical wells, 3D seismic-driven mechanical earth models (MEMs) were built. These covered the main sandstone reservoirs as well as the shaley formations. This integration of data from drilling operations, open hole logs, core, seismic and formation pressure measurements provided a constrained and consistent description of the prevailing in-situ state of stress, pore pressures and rock mechanical properties. These geomechanical models were further improved by accounting for historical depletion in the fields considered. The depletion modelling was performed numerically using a simulator performing finite difference fluid-flow calculations. The results obtained and understanding gained were then considered in the analyses of wellbore stability for future wells. This paper describes these geomechanical analyses and modelling—including the data integration to assess wellbore stability at the current level of depletion.

This study summarizes the efforts taken to provide reliable reservoir characterizations products to mitigate seismic interpretation challenges and delineation of the reservoirs. ADNOC has conducted seismic exploration activities to assess Miocene to Upper Cretaceous aged reservoirs in East Onshore Abu Dhabi. The Oligo-Miocene section comprises of interbedded salt (mainly halite), anhydrite, limestones and marls. Deposited in the foreland basin related to the Oman thrust-belt. Ranging in thickness from nearly 1.5 km in the depocenter to almost nil on the forebulge located to the west of the studied area. The well data based geological model suggests that initially porous rocks (presumably grain-supported carbonates) encompassed polyphase sulfate cementation during recurrent subaerial exposure in which pores and grains were recrystallized sometimes completely too massive, tight anhydrite beds. This heterogeneity of the complex shallow section showing high variation of velocity impact seismic imaging, and interpretation to model the stratigraphic/structural framework and link it with reservoir characterization. Hence, ADNOC decided to conduct a trial on state-of-art technique Litho-Petro-Elastic (LPE) AVA Inversion to mitigate the seismic interpretation challenges and delineate the reservoirs. The LPE AVA inversion provides a single-loop approach to reservoir characterization based on rock physics models and compaction trends, reducing the dependency on a detailed prior the low frequency model, Where the rock modelling and lithology classification are not separate steps but interact directly with the seismic AVO inversion for optimal estimates of lithologies and elastic properties. The LPE inversion scope requires seismic data conditioning such as CMP gathers de-noising, de-multiple, flattening and amplitude preservation, in addition to detailed log conditioning, petro-elastic and rock physics analysis to maximize the quality and value of the results. The study proved that the LPE AVA Inversion can be used to guide seismic interpreters in mapping the structural framework in challenging seismic data, as it managed to improve the prospect evaluation.

Objectives & Scope The objectives of this study are to determine new sweet spots & fluid content of the current discovery. Where, the Lower cretaceous carbonate reservoir units (Thamama) are among the most important hydrocarbon producing reservoirs in onshore Abu Dhabi. However, the studied field is considered as a marginal field, where the several cycles which affect the oil industry have emphasized the role for full integrated control of technical solutions for the development of such fields. Thus, an integrated feasibility study has been carried out to investigate the adding value of the seismic inversion and reservoir characterization. The area of study is located in southeast onshore Abu Dhabi. The studied field has been discovered and tested oil in Thamama carbonate units and is currently preparing for the first oil production. Challenges & Procedures Carbonates rocks are strongly modified by diagenetic process which influence the petrophysical properties to varying degrees. In carbonates, the influence of geological attributes is biased towards depositional properties in case of the use of texture and towards diagenetic attribute when using pore type. The main challenge is to locate new save optimized candidates for infill wells securing the production plateau and minimizing the risks behind the reservoir facies/quality and seismic resolution. To meet the objective, an integrated seismic reservoir characterization study was carried out by first a careful conditioning of the well logs and the seismic gathers data, followed by preserved AVO angle stack generation. Then, the rockphysics, fluid substitution, and wavelets estimation. The information was then used to conduct pre-stack AVO simultaneous inversion to generate several elastic attributes such as Acoustic & Shear Impedances, VpVs, and density. This was followed by detailed Litho-Porosity prediction as well as water saturation.