3rd EAGE/SPE Geosteering Workshop

The Aptian Burgan reservoir, located in the Minagish Field of Kuwait, consists of a thick sequence of amalgamated channel sands providing good lateral connectivity; however, a fault network connecting the sands to the aquifer could potentially allow a premature water breakthrough. Moreover, several producers were drilled in the area, affecting the position of the OWC, because of a significant water rise in proximity of horizontal and vertical producers. The Burgan reservoir is, therefore, a challenging environment for the placing and completion of horizontal wells, requiring the accurate knowledge of the position of the OWC for optimal wellbore placement and completion planning. Kuwait Oil Company decided, therefore, to run a slim-hole BHA including a conventional azimuthal propagation resistivity tool in combination with an extra-deep azimuthal resistivity tool and multicomponent resistivity inversion modelling for the drilling of a new horizontal drain hole. This choice allowed both to successfully map the OWC and place the wellbore at the required position within the reservoir for the entire extension of the lateral section.

Well placement operations, in which ultra-deep electromagnetic (EM) tools are deployed have relied on 1D and 2D inversion algorithms, to generate geological models displaying the distribution of formation and fluid boundaries as defined by variations in resistivity above and below the well bore. Well placement optimization has focussed on changes to a wells TVD or inclination based on analysis of the resultant models. Where geology is complex, due to the depositional environment and post depositional deformation of the reservoir, in additional to vertical changes, there can be major lateral changes in the position of resistivity boundaries. In wells targeting these reservoirs, treating well optimization as simply an up/down problem severely limits the potential for successful well placement. Recent advances in inversion technology into 2.5D and 3D allow an assessment of this lateral resistivity variability. When deployed real time these tools introduce the option of azimuthal corrections to a well path in response to analysis of lateral changes in the EM field to optimize the wells position within the target reservoir. This presentation examines the practicalities of identifying changes in the position of formation/fluid boundaries in 3D and what needs to be considered when attempting well placement optimization under these circumstances.

Modern drilling and well placement operations utilizing Electromagnetic (EM) inversion require high performance computational environments. These can be either on-premise as a high performance computer (HPC) or on the cloud as a collection of virtual machines. This presentation discusses some of the current uses of High - Performance and Cloud computing, the benefits this brings to well placement operations and how this can be used efficiently.

In addition, the presentation addresses the stability of the system. Uninterrupted services are a mainstay of real time drilling operations, fast, reliable data connections are required to transmit and receive data from the cloud. It is often discussed as an ephemeral resource but requires physical infrastructure. It is vulnerable to service interruptions, these can be anticipated, and contingencies put in place to limit their impact, but they need to be identified and understood prior to commencement of operations.

Computational resources need to be deployed efficiently to limit or exclude unnecessary costs. As this technology develops well placement software needs to remain agile to benefit from these advances. This will become more critical with the development of automated geosteering workflows and the associated increases in processing power required.

Ultra-deep 3D EM inversion provides high-resolution 3D reservoir imaging that can be used for real-time operational decision making and as a complementary tool for reservoir modelling and geophysical surveillance. Subtle, fine scale mapping of internal reservoir architectural elements is now possible. Significant improvements in overall imaging quality compared to 1D and 2D inversion canvases can be observed in dipping stratigraphy or where there is some degree of reservoir complexity. The real-time functionality also provides this 3D data in time to support completions optimization decisions where required.

Correlation of multiwell 3D EM datasets against 3D seismic provides the basis for a consistent geological interpretation at field scale. Reservoir characteristics and mechanisms such as compensational stacking and lateral channel migration could previously only be inferred from reservoir modelling studies but now can be directly imaged in real-time.

The longwall-mining method is a continuous mining system that was developed for mining coal deposits (uniform in thickness and slope), where the overburden pressures may crush support pillars and for improving productivity. This method relies on the complete extraction of the coal in a designated area referred to as a panel (of solid coal). As the panel is mined, complete subsidence or caving of the overlying rock strata occurs into the mined-out area behind the working mine face. Prior to mining the panel, degasification is a mandatory process to extract gas in the coal seams. In order to maximize the coal seam understanding and minimize the number of side-tracks, anovel methodology in the mining industry has been implemented - utilising azimuthal propagation resistivity (APR), multi-layer inversion with uncertainty analysis and real-time 3D structural reservoir modelling.

The bed boundary mapping also allows for the future development of automated long wall mining. The automated system uses specialized remote guidance technology to continuously steer the longwall equipment by plotting its position in three dimensions, removing personnel directly from hazards and thereby increasing the safety of the process.

Retrofit multilateral application has been applied for the first time in Barents Sea and on Norwegian continental shelf. This technology has unlocked potential, enabled fast track drilling (reduced time to market) and reduced capex in otherwise sub-economic targets. The conversion of single producers in multilateral, as retrofit application, allowed to accelerate production with limited additional required sub sea material.

The integration of Ultra Deep Azimuthal Electro-Magnetic tool with standard LWD technologies has helped the landing of the wells in the reservoir sections and has delivered the valuable geological information to successfully guide the navigation of the oil producers through the reservoir layers.

The presented two case studies are focusing on the operations while drilling, infill well results, main lessons learned and the way forward for the application of multilateral retrofit technology in other assets.

The “Giant Oil Field” has been on production for 29 years and is currently developed using waterflood and more than 350 ERD horizontal wells, spread over 8 different reservoirs. Amongst the complexities of the drilling in a carbonate reservoir, the brown field nature of this mature field, adds a dimension to the difficulties associated with profitable oil extraction.

Developing optimally and understanding those reservoirs present multiple challenges, requiring a multidisciplinary approach to address them.

Therefore, a novel data acquisition plan based on Reservoir Mapping While Drilling Service (RMWD) allowed to bridge the gap and join the reservoir scale information (Surface Seismic, 4D Seismic and Production model) with near-by wellbore information (conventional LWD logs, core and cutting analysis for facies identification).

A probabilistic decision support system for geosteering coupled with automated data assimilation techniques has been shown to outperform many humans at least in sandbox 2D experiments. Utilizing probabilistic decision support for optimal positioning of real wells requires a 3D probabilistic earth model compatible with standard tools, and rapid generation of synthetic logs of extra-deep measurements.

We introduce a method for representing a 3D earth model with depth uncertainty in stratigraphic surfaces. The surfaces are parameterized using a multi-scale technique, capturing correlations and uncertainties on both large and small scales. The probabilistic earth model is updated by an ensemble-based method that assimilates extra-deep EM measurements acquired while drilling. A recently developed Deep Neural Network model ensures rapid simulation of extra-deep EM measurements. However, the model assumes local layer-cake geology and thus can only interpret 1D sensitivity for each measurement position.

The proposed method is applied to a synthetic study based on geosteering in the Goliat field. The results demonstrate that data assimilation of the extra-deep EM measurements successfully reduces uncertainty in the 3D model and updates it towards the truth. Moreover, we demonstrate 3D visualization of the probabilistic model compatible with standard geo-modelling tools, useful for decision support.

Directional wellbore trajectory is a critical aspect of early well planning. Planning the optimum directional wellbore trajectory requires drilling engineers to integrate cross-domain inputs from geologists, geophysicists, and reservoir engineers.

In this paper, we introduce a system to optimize the wellbore trajectory during the planning phase of the well construction. The system will capitalize on early optimization by integrating cross-disciplinary data prior to drilling, allowing for higher spatial correction. The integration will produce a drilling hazard seismic attribute (DHSA) that correlates geologically induced drilling nonproductive time (NPT) from all offset wells per specific field and formation.

Through its cross-disciplinary approach of utilizing historical, geophysical, and drilling engineering, this system drives the full integration and automation process of the well trajectory evaluation. This process is centered on minimizing drilling risks, delivering the optimum well trajectory from the planning stage, and allow engineers to better understand the structural geology and geohazards from the surface to total depth (TD).