A recently introduced azimuthal resistivity LWD imaging tool has been upgraded with advanced high resolution sensors that are capable of differentiating reservoir and borehole features down to a size of 0.4 in. when drilling in well consolidated formations. The high vertical and azimuthal resolution, along with 100% borehole coverage, yield an image quality comparable to that of wireline service for applications that include fracture characterization and formation evaluation. This paper describes a field test of the high resolution tool in 5 7/8" and 8 3/8" holes in Saudi Arabia and shows the application of LWD images for estimating carbonate reservoir producibility involving the characterization of secondary porosity. The LWD imager provides significant economic and logistic benefits, especially in slim horizontal sections; in addition, it can identify fractured zones with mud loss potential shortly after penetration. The real-time resistivity provides a good basis for accurate dip calculation and geosteering in general. In its default configuration, the high resolution tool is equipped with six high resolution sensors arranged in two rows. One of the benefits of the multi-sensor configuration, demonstrated by the field test, is the ability to validate the image quality by comparing data from various sensors. Another benefit is the depth correction achieved by correlating images from identical sensors located at various depths. The paper also discusses the fundamental principles behind high resolution resistivity imaging in conductive mud and makes extensive use of modeling techniques to characterize the sensor performance in various practical situations.

Understanding and management of subsurface uncertainties has become increasingly important for oil and gas companies to optimize reserve portfolios, make better field development decisions and improve day-to-day technical operations such as well planning. In this paper, the authors developed models, workflows and methodologies for multiple development scenarios that span the range of uncertainties for all stages of reservoir description and simulation for two fields (Field A and Field B) in Saudi Arabia. These processes are based on responses to uncertainty parameters in order to capture and quantify uncertainties. Uncertainty quantification for the two reservoirs was performed using experimental design (ED) approach taking into account seismic interpretation, geological uncertainty, and dynamic data. ED is an intelligent way of sampling parameter space by selecting combination of predefined variables to minimize the number of "experiments" to characterize the behaviour of a system, and to limit the number of models to be run. As a result, robust and responsive reservoir models were constructed to predict the field performance as well as to evaluate various future development strategies alongside better risk-assessments.