Challenges and Key Learning for Developing Tight Carbonate Reservoirs

Abstract

Fast track development projects, with timely data acquisition plans for development optimization, are very challenging for tight and heterogeneous carbonate reservoirs. This paper presents the challenges and key learning from initial stages of reservoir development with limited available data. Focus of this study is several stacked carbonate reservoirs in a giant field located in onshore Abu Dhabi. These undeveloped lower cretaceous reservoirs consist of porous sediments inter-bedded with dense layers deposited in a near shore lagoonal environment. The average permeability of these reservoirs is in the range of 0.5-5 md. Mapping the static properties of these reservoirs is difficult since they are not resolved on seismic due to the low acoustic impedance contrast with adjacent dense layers. Petrophysical evaluation of thin porous bodies inter-bedded with dense layers in highly deviated wells pose significant challenges. Laterolog type LWD resistivity measurements which are less affected by environmental effects, offer more accurate formation resistivity compared to propagation type measurements. With limited suite of logs, some of the zones with complex lithology had to be evaluated innovatively as detailed in the paper. Integrated studies are initiated to improve reservoir description by carrying out accurate permeability mapping, SCAL, geomechanical and diagenesis & rock typing studies. Significant challenges exist regarding the development of thin, tight and highly heterogeneous reservoirs, in terms of recovery mechanism, well architecture, well count, drilling, well completion and economics. Static and dynamic models were used extensively to evaluate different development scenarios and conduct sensitivity studies to bracket uncertainties. Various geo-steering options were discussed and the paper also details maximizing the reservoir productivity using long reach MRC (Maximum Reservoir Contact) wells. Tight and heterogeneous reservoirs call for extensive and real time reservoir surveillance activities to assess well performance and reservoir connectivity. This paper highlights how these challenges are overcome through upfront surveillance planning and proactive well completion strategy.

Application of improved data-driven diagnostics workflow based on coupled hydro-mechanical model for stimulation candidate selection in a complex carbonate reservoir

“…(9) which is governed by porosity coupled with stresses or strains [Eqs. (5)(6)(7)(8)]. Thus, CFDI plot is a dynamic scatter plot that takes into account the stress changes during the reservoir production and the associated permeability changes of each well during its production time.…”

“…Also in recent years, exploration and development companies have gained more interest in development of deep carbonates with more complexities in reservoir rock and fluid behavior and application of improved oil recovery (IOR) techniques such as stimulation to tackle productivity issues [4]. Uncertainties in microfracture network distribution and fluid behavior heterogeneities are some of the complexity elements that impose challenges to the IOR candidate selection and make the use of simulation models as the main way of data integration limited [5]. Therefore, the importance of surveillance data-driven analytics integrated with the hydro-mechanical modeling for the IOR decision-making process such as formation damage removal is highlighted [4].…”