Acquisition of high-resolution images for reservoir characterization from logging-while-drilling (LWD) technologies has historically been limited to water-based mud (WBM) applications. The introduction of LWD ultrasonic technologies means high-resolution images and the associated analysis are now available in both WBM and oil-based mud (OBM) applications. This paper details the first deployments of a 4¾-in. LWD ultrasonic imaging service in a mature field, offshore Abu Dhabi, and the assessment of images in both WBM and OBM wells. The 4¾-in. ultrasonic tool combines both borehole size and shape measurements with high-resolution radius and reflection amplitude images. The ultrasonic sensor uses four transducers that operate in a pulse-echo mode. By firing simultaneously, the transducers provide a total of 2,000 travel time and reflection amplitude measurements each second, enabling the creation of high-resolution images, even at high-logging speeds. The methodology described was used to evaluate the suitability of the LWD ultrasonic measurements to enhance reservoir understanding, along with LWD azimuthal formation density and azimuthal high-resolution resistivity image measurements in WBM applications. The 4¾-in. ultrasonic borehole imaging technology was deployed while drilling with OBM/WBM to acquire ultrasonic images to capture the subtle geological features that often control the reservoir properties, but whose characterization was challenging previously due to technology limitations. The long lateral was logged with ultra-sonic imaging while drilling through Cretaceous carbonates, traversing through different layers going up and down in stratigraphy; showcasing subtle variations with complementing images that helped understand the vug distribution, bioturbation, faults, and dissolution seams, in addition to the bedding boundaries. High-resolution borehole shape analysis was performed to understand the impact of stresses on the well trajectory, made possible with the high-definition, multisector images. The resolution of the reflection amplitude images, in particular, enables identification of drilling-induced features on the surface of the borehole, highlighting the measurement's value in understanding the impact of the bottom hole assembly (BHA) on the quality of the wellbore. The travel time measurements provide detailed evaluation of the borehole size and shape, with the three-dimensional (3D) visualization of the wellbore illustrating the ability of the service to identify borehole enlargement and breakout. These findings demonstrate the suitability of the service to address wellbore stability issues in real time. This paper details the first use of the ultrasonic service in Abu Dhabi. Comparison of images from the new ultrasonic imaging service with established LWD technologies highlights the suitability of the radius and reflection amplitude images to provide enhanced formation evaluation analysis in both WBM and OBM applications. Log examples show the high-resolution images are able to identify bedding features and fractures and provide assessment of borehole size and shape for wellbore stability evaluation.
When drilling in mature reservoirs, conventional formation evaluation is not enough. Characterizing these formations properly becomes essential in ensuring longer and sustainable oil producing boreholes. Understanding the geological complexities, permeability drivers and pressure potential is important since they control fluid flow. This work presents the first ever case study from the Abu Dhabi Carbonates where an innovative multi-measurement borehole imager was deployed, providing a comprehensive and integrated formation evaluation not used before in the industry. A campaign of five extended reach wells was planned in one field offshore of Abu Dhabi. A 15-ft long borehole imager was added to the drilling bottom-hole assembly (BHA) to acquire apparent resistivity and ultrasonic images simultaneously to characterize the often not-observed geological features that control reservoir properties. These complementing images helped in characterizing vug distributions, bioturbation, faults and dissolution seams in addition to the bed boundaries. Around 13,000ft of lateral was logged while drilling, using this data in real time in oil-based mud to target the most permeable and thinnest layers for the first time in the middle east. Core analysis had defined the 2ft thick most permeable layer of the reservoir where the lateral needed to be exposed for better production. Multi bed boundary detection for waterfront identification was integrated with mobility pretests points along with surface mud gas fluid sampling for Gas Oil Ratio (GOR) determination and the innovative dual imager. For the first time, acquiring a high resolution apparent resistivity image in real time in OBM, made the restriction of placing the lateral in a thin layer possible. Findings redefined the understanding of the geology and the drivers behind the fluid flow within this reservoir. With the new high definition ultrasonic image, vugs that tend to control the permeability in many facies were discovered. This led to the computation of a vug density curve derived from the images which characterized the key-intervals. Qualitative trends were validated with mobility estimated from independent LWD measurement, providing much-needed confidence in the new imaging technology. Completion was re-designed based on the new brought-in information. Sections were isolated based on the high-water saturation zones mapped with the multi bed boundary detection technology and higher gas oil ratio from surface fluid sampling. Completion was then optimized around high vug density/ mobility intervals. This first-ever case study provides a plethora of new information for model update whether it be the geology or the reservoir model that was hitherto unavailable for some reservoirs where development wells were drilled with OBM. For challenging wells planned in highly constrained environments from structure, petrophysics and reservoir maturity aspects, this new technology cleverly combined with others, opened the door to boost production from otherwise, a highly matured reservoir.
Overburden (shallow) anomalies such as channels, sink holes, or karst features pose challenges for seismic time imaging, resulting in an obscured image below the anomalies i.e. pull-ups or push-downs. These anomalies can propagate down to the reservoir masking the image and create structural uncertainties. These relatively small scale (< 1 – 2 km) overburden anomalies cannot be resolved with conventional depth imaging usually, based on migration velocity analysis and residual move out (RMO) minimization only. This paper proposes the application of dip-constrained tomography, in combination with RMO tomography to help resolve these shallow anomalies. Although the method has been widely used elsewhere e.g. in offshore Brazil and North Sea (Chen et al., 2012, Guillaume et al., 2013, Carotti et al., 2015 and Hollingworth et al., 2015), this is the first time it has been applied in a carbonate oilfield in offshore Abu Dhabi. An accurate velocity model is required for seismic depth imaging. The velocity model is optimized using a tomographic technique which is a non-linear optimization process with relevant constraints imposed. The data are migrated using an initial velocity model and common image gathers are obtained. RMO is defined in a cost function and non-linear tomography finds a velocity model minimizing the cost function. An additional structural constraint in the form of an offset-dependent dip constraint is introduced in the cost function for minimizing the misfit between the offset-dependent dip of the events and the expected dip. Dip-constrained tomography was able to obtain a high resolution velocity model in the overburden and provided a robust seismic image essentially free of pull-up and push-down effects in the reservoir. The structural uncertainty in the reservoir was subsequently reduced. Inverting the dip term together with RMO term can potentially correct image distortions e.g. pull-ups and push-downs and focus the image simultaneously. The refined subsurface image can help optimize the reservoir model with less structure uncertainty and can enhance the production profile by providing more flexibility in well design and planning. The methodology was applied on a pilot area which gave quite encouraging results and leads to extend the pre-stack depth imaging to a full-field application.
This paper present the successful deployment of the ultra-deep EM tool in a mature carbonate reservoirs to reduce the uncertainty associated with fluid movement for horizontal/ MRC well-placement optimization and enable precise geosteering to maintain distance from fluid boundaries and mapping of nearby reservoirs for future reservoir development. In addition, the EM tool can facilitate to optimise lower completion design liner (blank pipe length, PPL, ICD and swellable packer depth). The high heterogeneity of reservoir qualities increase uncertainty in fluid distribution and make drilling long horizontal, oil producer wells in offshore mature giant carbonate fields very challenging. The usual plan is to drill a pilot hole crossing the reservoir sections, evaluate log saturation, and then re-optimize horizontal sections accordingly. To study the possibility of eliminating pilot holes, an ultra-deep electromagnetic (EM) tool was deployed. The first objective was to detect reservoir boundaries and predict resistivity of the target before penetrating it (Geostopping). The second objective was to optimize the horizontal drain (Geosteering), and map resistivity of adjacent reservoirs for well completion and future well optimisation (Geomapping). Pre-well inversion modeling was conducted to optimize the spacing and firing frequency selection in order to facilitate early real-time geosteering and geostopping decisions. The plan was to run the ultra-deep resistivity tool in conjunction with shallow propagation resistivity and density-neutron porosity while drilling the 8½ in landing section. The objective was to be able to detect the lithology boundary early and predict the resistivity of the reservoir before penetrating, facilitating geostopping decisions. This would allow optimization of the horizontal section to geosteer the well in an oil-saturated layer 4-6 feet from top boundary while geomapping the surrounding reservoirs’ resistivity. The EM tool delivered accurate mapping of thin reservoir layers while drilling the 8½ in section, as well as enhanced mapping of low resistivity zones up to 85 feet true vertical thickness in a challenging low-resistivity environment. Comparison to recorded open-hole logs for validation showed good results, enabling identification of the optimal geostopping point in the 8½ in. section. The EM tool is able to save up to five rig days in the future by eliminating pilot holes. The 6 inch horizontal section was successfully geosteered and placed 4-6 feet from top boundary. The EM tool was able to map reservoir resistivity 30 feet TVD below the wellbore and the completion design was designed accordingly. Additionally, the EM inversion for the nearby reservoirs helped to modify the plans for nearby future wells.
Today, the major challenge in reservoir management is improving reservoir characterization to better understand variations in rock properties and distribution of fluids away from the wells. A further challenge is the proper characterziation of thin multi-layered heterogeneous reservoirs. In this paper we present a new workflow to delineate reservoirs at and below seismic resolution. A reservoir characterization study is performed for the Reservoir Z of the Giant field. The reservoir seqeuce consists of multiple reservoir units (1, 2, and 3) with variable average porosities between 11 and 28%. The study attempts to delineate separate units through an innovative Bayesian inversion technique that jointly solves for impedances and facies (Kemper and Gunning, 2014). Four different seismic facies were determined through an inversion feasibility study from variations in mineralogy and porosity. Elastic property trends as a function of time were built from the petrophysics of two wells. The low frequency component was driven by these trends and prior facies distributions were specified to constrain the results to be geologically reasonable. Three angle stacks were simultaneously inverted using extracted wavelets, each with specified noise estimates. An inversion was run using this technique on post stack data, as well as a coloured inversion for comparison. Despite varaible data quality, the pre-stack facies based Bayesian inversion was able to invert for three separate layers of high porosity in the reservoir sequence in a number of blind wells. This was a noteable improvement on both the coloured inversion and post-stack inversion. It was concluded that the higher frequenices in the near stack data combined with increased rock physics contraints of the inversion resulted in better thin layer detection.
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