Variable reservoir thickness, heterogeneity, and presence of geological truncations are some of the challenges inherent in draining complex reservoirs. These challenges affect the depth of detection of some formation evaluation tools, the ability to optimally place the well in the target horizon, and the ability to remain in the sweet spot throughout the drain length. To mitigate these challenges, reservoir navigation service with fit-for-purpose tools and robust software is required. This paper is a case study of the application of the VisiTrak™ tool and Multi-Component-While-Drilling (MCWD) inversion software (Sviridov et. Al., 2014) in the geosteering of Well-X. VisiTrak is an extra deep-reading azimuthal propagation resistivity tool. MCWD is software that essentially creates a geological earth model from the readings of azimuthal propagation tools. It is multi-layer inversion software. Well-X is located in offshore Niger Delta and the target reservoir consists of several individual turbidite complexes and stacked channels. The successes recorded in this geosteering case include accurate subsurface structural interpretation, reservoir characterization, and achieving well objective in terms of net sand drilled. This paper demonstrates the importance of reservoir navigation in accurate well placement, the benefits fit-for-purpose tools bring to geosteering complex reservoirs in the Niger Delta and shows the value of data integration in reservoir navigation service.

Understanding of rock strength, and its variability along the length of the well, is essential for building an efficient well trajectory during geosteering operations. Traditionally, drill cuttings, surface gas analysis, measurements while drilling (MWD) data and Logging While Drilling (LWD) measurements have been used to optimize trajectories. Rock mechanical properties, derived from petrophysical well logs are key to drilling, production and recovery potential of the well: However, in a vast majority of geosteered wells, LWD data and the derived rock properties are not available thus conforming to the given well trajectory and successful Geosteering is difficult. In comparison, real-time downhole drilling data is usually available but rarely used. An innovative, reliable and robust method is presented which capitalizes on downhole MWD and LWD data. This method uses downhole weight-on-bit (WOB), rotational speed (RPM), downhole torque (TOR), and rate-of-penetration (ROP), to characterize the mechanical specific energy (MSE) consumed in the drilling process. The specific bit diameter (D), mud-weight (MW) and depth (TVD) of drilling are also used in the model. If the task is to optimize drilling parameters for a new formation (e.g. drill-off-test), then "minimum" MSE is captured. However, if the task is continuous drilling, geosteering, and creating a stable well for its subsequent stage and cluster-wise hydraulic fracture design, then "instantaneous" MSE is used to infer strength of the rocks and their variation along the length of the well. An offshore well from the North Sea was initially selected to apply the concept of the above technology on several post well data analyses using downhole drilling data together with average ROP and RPM. Further, the same concept was used in a real-time application with downhole drilling data. The gamma-ray, neutron porosity, density and resistivity were analyzed and compared with the MSE obtained. Drilling efficiency was assumed based on prescribed industry standards for calculating confined compressive strength (CCS), Internal Friction Angle (IFA), and unconfined compressive strength (UCS). The UCS estimated at a scale of 1.0-1.5″ scale versus depth-of-cut (scale of 0.1-0.5″) resolution matched well with log based UCS from density, porosity and acoustic logs. Calculated results are compared with lab-based core test data where available. The details of these calculations and successful application to Geosteering are presented. These strength estimates are of benefit to directional drilling engineers for safe and economic well placement along optimum well trajectory, better well production and economic recovery from successive multi-stage and stage-and-cluster hydraulic fracturing designs. An ‘Efficiency’ Factor’ used in the process is discussed which originates from strengthening of rocks due to friction, chip-hold-down effect on cuttings, strengthening due to dilatancy, and cuttings-extrusion like behavior prevalent in drilling.

Today's complex and challenging reservoirs are now accessible using state-of-the-art technology in drilling and logging-while-drilling (LWD). The drive for advanced, capable technologies to explore the full production potential of these reserves cannot be overemphasized. In addition to the drive for increased production from existing fields, there is an increased focus on precisely placed horizontal wells in the best part of the reservoirs. The drilling is carried out by using the existing well stock and employing re-entry techniques. The dramatic adjustment in the crude oil price has made cost-effective drilling and geosteering solutions increasingly critical for delivering efficient, economic wells. Reservoir navigation services involve predicting the geology ahead of the bit to optimize the placement and drilling of a horizontal wellbore in a complex reservoir. These predictions are based on formation evaluation data gathered while drilling using deep-reading azimuthal resistivity LWD tools and innovative interpretation techniques to update the geologic model in real time. Adjustments to the well trajectory based on the updated geologic model are enabled by downhole systems that have good directional control and use continuous proportional steering technology to steer the bit. Well QH is a 3D complex well located in the Adanga Field of the Niger Delta Basin, offshore Nigeria. The well is drilled to a total hole depth of 9,512 ft MD. The Q reservoir is shallow, at approximately 3,600 ft true vertical depth (TVD), and it required complex 3D well planning to precisely land and drill a horizontal well in the thin, intercalated sand and shale sequence. There are other directional challenges inherent in a brown field development when drilling from a complex multiple slot platforms with existing producing and suspended wells. This paper discusses the well QH as a case study, showcasing how reservoir navigation services with fit-for-purpose LWD data can result in increased net lateral production in a complex, thin multilayered reservoir. The case study highlights how the uncertainties encountered during planning stage and challenges in the execution stage were turned into a success story. This paper also discuss the application of well placement through advanced, user-friendly software, grounded on the state-of–the-art LWD and rotary steerable technology and their significant impact on the project, challenges and lessons learned.

The Troll oil field has been one of the largest oil producers on the Norwegian continental shelf for the last 25 years and is now moving into late life. The remaining oil column is thin, and the fluid contacts vary due to production effects. To extend field lifetime and secure the last reserves, enhanced well placement and increased drilling efficiency is needed to reduce cost and increase recovery in the long multilateral horizontal wells. Due to thin oil column and low reserves number, every meter correctly placed in the reservoir counts. To investigate these challenges a technology development project was initiated between Equinor and Baker Hughes to develop automatic interpretation of the oil-water contact (OWC) based on inversions, and automatic steering advice for taking faster geosteering (RNS) and downlink decisions placing the wellbores at the optimal distance to the OWC. Automating log interpretation is a complex task, but solvable given a known environment. As an engineering problem it must be split up into multiple smaller tasks that can be independently solved and when combined, solve the greater task. Logging while drilling (LWD) deep azimuthal resistivity data is run through inversion processing which provides a resistivity profile from which the OWC position is identified. The inversion input model constraints are set based on field/area specific data and is run automatically as drilling progresses. To assess the quality and validity of these results, several flag curves are computed and used. This automatic quality control of the OWC points enables the creation of a forward projection of this boundary. A steering advice is calculated, giving a recommendation on how to achieve the desired stand-off and inclination above the OWC as efficiently as possible. All the output from the automatic interpretation is published to a central datastore and is immediately available for the geoscientists to optimize operational decisions. Close co-operation between the operator and the vendor during the development and testing of the service has proven beneficial for identifying areas for further improvements. The service has been tested for well placement in actual producers. Several loops have been made in the development between the different tests and the learning curve has been steep in both companies. Based on the experiences and results from the actual wells, the project has moved into a new phase for further optimization of the steering advice and linking the automated steering advice to an Automatic Drilling Control (ADC) system to deliver a more automated closed loop service.

The benefits of geosteering for accurate wellbore placement in reservoirs are well documented, with an emphasis on comprehensive reservoir mapping capabilities and related well path adjustments. Similarly, drilling-related processes such as well re-design, proximity scanning, and downlinking are important. The integration of geosteering and drilling processes adds complexity and challenges to designing automated wellbore placement systems. Automated systems need to contain sufficiently robust technologies and algorithms to avoid unintended and frequent exceptions. Equally, the human element must be considered to design an automated system with a great user experience. To gain user acceptance, an automated system must have the characteristics of predictability, transparency, adaptability, and automation levels that are validated prior to utilization. Without this, the result will be wellbore misplacement by engineers who blindly trust immature automated systems. This paper provides an overview of processes and tasks within a comprehensive wellbore placement system, including the directional drilling and geosteering services as used by stakeholders who own well placement execution. We will provide an overview of the potential of automation and pitfalls to be avoided. The experience of many expert engineers from complementary disciplines has been used to develop a comprehensive concept as a framework to implement an automated wellbore placement system. The paper also provides an analogy to the automotive industry which has developed reliable and robust systems for navigation, lane and speed control over the last few decades. The comparison highlights a fundamental difference to the petroleum industry of having multiple stakeholders involved in the process of wellbore placement. Consequently, communication between all the stakeholders during operations, notably proposals and approvals, must be designed into the system from the beginning. Automation concepts to achieve great user experience are demonstrated on components of a wellbore placement process, including the illustration of lessons learned from recent development initiatives. Based on the demonstration, we conclude that an iterative development process is essential to ensure acceptance by the user community.