Thanks to cloud-native technologies, the oil and gas industry is now pursuing how to retrieve information from unstructured data. This is especially relevant in mature exploration and production (E&P) areas such as the Norwegian Continental Shelf (NCS). Valuable information from historical unstructured data (documents, reports, images, etc.) can help when improving processes related to exploring a new area, planning a new well, and creating a rig activity plan. However, the biggest challenge with this unstructured data has always been that it is typically stored in internal servers and within complex folder structures, making the search for a single file a time-consuming -- if not impossible -- process. This paper details a cloud-based methodology of searching and contextualizing unstructured data in order to make it available to domain experts through Application Programming Interfaces (APIs). We have developed a framework for configurable document processing that makes raw data searchable by leveraging existing cloud-based services such as popular natural language processing (NLP) and computer vision APIs. This makes it possible to extract content and make it searchable and contextualized to related assets (wellbores, seismic, etc.) based on keywords and geospatial location. Machine learning categorization supports file grouping into document types, such as a work order or rig action plan. To illustrate this methodology we present two examples. The first example shows how a user can draw a polygon on a map to retrieve and extract all the data within that polygon. This can be used in reporting tools or to build knowledge graphs. The data is fully contextualized to the geographical area of investigation. The second example shows content extracted from well reports, providing information about historical issues that happened to offset wells, which supports the planning of a new well in the same area under similar conditions. Content extracted from unstructured data offers an opportunity to add valuable information to support risky and time-consuming processes such as evaluating an exploration prospect and planning a new well. Searching for and contextualizing this content are the first steps toward making the retrieved information instantly available and more interactive for domain experts.

Digital transformation of existing processes using technologies such as big data, advanced data analytics, machine learning, automation and cloud computing will enable continuous performance improvements within the operational sphere. The application of the technology will link the physical and digital world, providing a digital model of physical assets and processes. It will represent the evergreen, wholly integrated digital asset model - from reservoir to export pipeline. The Brage operations team identified processes with the highest potential for digital transformations during an initial opportunity framing workshop. Based on pain points and business needs, the clear emphasis is in the areas of production & well performance optimization, high-spec live-data visualization, as well as the entire flow of information from database integration up to dashboarding. Strong reliance on an improved data infrastructure and IT/OT performance will require close cooperation with the IT/OT team. New solutions will be aligned with and integrated into already identified global solutions. The improved acquisition of data, together with the integration of already existing ‘Digital Twin’ technologies will enable the first redesign of work processes. Prioritization of processes to be transformed will be mandated by their business impact as well as possibility to scale to other Wintershall Dea assets too. Focus areas, such as Slugging, Digital Production Engineer, Intelligent Maintenance, Dashboarding and Planning/Scheduling, were defined as more and more ideas evolved. Individual processes such as water injection and scaling surveillance were made more time efficient and transparent. The vision is to bring all processes together into a customizable and collaborative dashboarding solution. Intended completion of the first phase is Q4 2019. The following phase will be the execution of a larger scoped technology implementation that will be defined in detail by then.

In this work we present results of long-term aging tests of a novel cement system (cement R) in carbonated brine and effect of reaction with CO 2 on the mechanical properties. Aging tests in carbonated brine were performed for one week, four weeks and two months in a pressure cell at 100 bar and 80 °C. For each test, three cores were placed at the bottom of the cell and fully immersed in 3.5 wt% NaCl brine. The cell was then pressurized with CO 2 from the top. X-ray computed tomography (CT) was performed prior to and after the aging tests. Macro-porosity was estimated based on selection of appropriate grayscale range. Unconfined compressive strength (UCS) tests were performed on unexposed cores for reference and on the exposed cores after the aging tests. Reaction with the carbonated brine was observed already after one week of aging. The reaction front progressed further into the bulk after four weeks. However, the reaction slowed down after four weeks. There was no significant difference between samples exposed for four weeks and those exposed for two months. Precipitation of minerals on the surface occurred after four weeks, and this process continued after two months. Macro-porosity decreased and net mass increased due to the reaction with the carbonated brine. The UCS tests indicated that one week of aging had little effect on the unconfined compressive strength and Young's modulus. Decrease of UCS and Young's modulus was observed after four weeks and two months of aging. One reason for strength decrease after two months, by about 40 %, was appearance of cracks within the samples that coincided with the reaction front to a great degree. This could have occurred during the depressurization of the cell. The inorganic Cement R works by reacting with water, CO 2 and/or brines to expand into available pores and cracks in ordinary well cements. This effect is interesting to study for possible applications in CO 2 storage, plug and abandonment and reuse of existing wells.

The Norwegian oil and gas industry (O&G) operates nowadays in more demanding and sensitive drilling environments while it approaches more complex reservoirs facing multiple challenges, both technically and environmentally. Not allowing shortcuts to success, clearly any technology helping to mitigate risks, increasing efficiency and reliability should be embraced. Especially as in parts the public perception towards O&G is more critical, clear corporate governance towards risk reduction by process or technology is more than adequate, assuring to comply with the general guideline of reducing critical activities and operations, such as radioactive source handling and logging with it. A recent operation on the Norwegian Continental Shelf (NCS) is an excellent example of combining local knowledge with fit-for-purpose technology to minimize timescales and risks while improving efficiency and formation evaluation in an extended reach horizontal well construction to further develop the Marulk field in the Norwegian Sea. This was achieved through the first global application of geosteering operations using a comprehensive real-time (RT) data acquisition governed by a sourceless "green bottom hole assembly (BHA)" in oil-based mud (OBM) environment. Including most notably a novel high-definition dual physics OBM imager and in the logging-while-drilling (LWD) arena unique accelerator-based radioisotope-free bulk density, neutron, sigma and elemental capture spectroscopy measurements, deployed along with azimuthal ultra-deep electro-magnetic (EM) reservoir mapping technology. All to provide a complete reservoir and geological description of the Cretaceous sandstones deposited in turbidite fans with moderate to good quality. The utilization of this sourceless LWD technology as the kernel acquisition empowers the well construction to be actively steered not only by formation qualities but also by the fluid characteristics in real-time, basically providing information about the structure, rock properties and in-situ movable fluids. The quantitative evaluation of petrophysical logs for hydrocarbon saturation had a good match with reservoir delineation and maps from deep EM measurements, confirming the net hydrocarbon bearing producible sands. Surface mud gas data was also analyzed, and its integration with petrophysical interpretation indicated the presence of heavier hydrocarbon fractions towards the toe of the well. A high-resolution sand count interpretation from dual physics borehole imaging tool confirmed the maximum net reservoir potential. The well is currently producing above the predicted rate. The case studied is a great example where a strong interaction between professionals both in the planning and execution phase making use of available and most suitable technologies. Together with a positive mind-set and a winning attitude it resulted in a better understanding of the complexity of the reservoir and finally placing the lateral in the best evaluated reservoir facies.

Planning a well for safer and faster operations requires complex and experience-based decision making. In this aspect of the oil and gas industry, the main source of information is the limited amount of offset well data. The offset well data is spread across different domains which makes it more difficult to analyze in the stipulated period of time and in turn the quality of a planned well is always sub-optimum. The main objective of this study is to make use of machine learning and deep learning algorithms to increase the scope of offset well planning by analyzing a large number of wells efficiently. This approach represents an alternative workflow for offset well planning with a focus on data-driven KPI's (Key Performance Indicators). The significant KPI's that can be tracked is increased use of reference wells with a drastic reduction in time required for waiting and searching for data. The area of this study is the Norwegian Continental Shelf (NCS) encompassing wells in the North Sea, the Norwegian Sea, and the Barents Sea. The dataset consists of around 4500 wells with high dimensionality features based on stratigraphy data and well path data (eg. top and bottom depth, thickness, azimuth, inclination etc.) for each well. A new methodology is discussed in this study that includes the use of deep learning algorithms i.e. Convolutional Neural Networks (CNN) and non-linear algorithm for dimensionality reduction (t-Distributed Stochastic Neighbouring Entities and Uniform Manifold Approximation And Projection) on this high dimensional dataset. The results of this study show that the reduced dimension data obtained from the above methodology is able to extract high-level features from the wells based on the input data/features. Obtained embeddings show the relative distance between the wells which can then be used to find how similar the wells are with respect to each other. The value of the results obtained from this study can potentially increase the horizon for offset well planning by incorporating not just the nearby wells but all the wells from the corporate databases. This, in turn, tracks key KPI's and saves time by providing automated answers to the engineers.

A fit for purpose 4D Geomechanical model is regarded valuable for most fields. Although tools for building such models have been available for some time they are commonly not made or not fully utilized due to the extensive amount of time, complexity and costs involved. In Equinor a workflow (DE4RM) has been developed for fast 4D geomechanical modeling, effective visualization and interpretation. Using this workflow, models have been built for more than 20 fields over the last 4 years and results applied for a variety of areas including input to seismic time shift analysis, short and long term well planning, estimation of cooling effects from injectors, subsidence/compaction predictions, input to well completion, monitoring optimization, overburden integrity studies, out of zone injection and fault re-activation assessment. Some examples on such use will be given in this paper. On the modeling side key factors for efficient modeling are utilization of existing reservoir models, use of commercial finite element software and a streamlined, easy to use, workflow for all pre-processing steps. Particularly, a well-equipped toolbox for various grid-editing functionality has been essential for being able to complete the modeling fast enough (1-3 weeks). Once a model is built it is readily available for both geomechanical experts and non-specialists through the open source powerful visualization platform Resinsight. In this software geomechanical capabilities have been developed over the last years guided by practical use of the models. Further development on both the modeling, visualization and post-processing side is ongoing and as Resinsight is open source, use of the software and development of new functionality is possible for anyone. In summary, 4D geomechanical modeling and utilization of such models has become a daily activity in Equinor for numerous applications, gradually replacing simplified 1-D based methods with the faster and more accurate DE4RM methodology.

In a typical well completion system, retrievable plugs run on wireline are used to set production packers and thereafter, to perform leak testing of the upper completion tubing. There are significant costs and risks associated with these intervention operations to set and retrieve aforementioned plugs. This paper presents the development and implementation of a system using dissolvable technology that allows for interventionless packer-setting and tubing testing of upper completions. The solution developed is a packer-setting kit consisting of a seat profile and a dissolvable ball. The seat is run as part of the tubing string below the production packer. After landing the completion string, the dissolvable ball is dropped from surface to land on the seat profile below the packer. This ball-seat system holds pressure from above, thereby, enabling the production packer to be set and a leak testing of the tubing to be performed. Eventually, the ball dissolves completely in the presence of downhole packer fluids permitting start-up of production activities. This paper documents the extensive qualification test program which was undertaken to qualify a dissolvable ball-seat system for one-such application. These tests were aimed to verify the capability of the packer-setting kit to fulfil the operational requirements (pressure rating, dissolution time periods) under the specific downhole conditions (packer fluid type, temperature). Following successful qualification testing, this solution was successfully implemented in 3 wells on the Norwegian Continental Shelf in 2018. Adopting this technology significantly improved operational efficiency by reducing well completion and intervention times along with associated costs. Consequently, this enabled earlier production start-up on these wells. The most challenging aspect of this new approach is the selection and qualification of a suitable dissolvable ball material appropriate for the application-specific requirements and operational constraints. The various steps and tests necessary to verify suitability of dissolvable technology for such applications are outlined in this work. Key operational considerations which need to be kept in mind when implementing this solution shall also be addressed.

The transition towards drilling automation in the oil and gas industry has increased the need for digital infrastructures for development and testing of new technology. This includes infrastructures to facilitate changes in work processes and technical competences. This paper describes the design and use of OpenLab Drilling, a digital infrastructure with applications in education, technology development and testing. OpenLab Drilling offers access to a high fidelity drilling process simulator capable of simulating transient hydraulics, temperature, torque and drag, and cuttings transport. Since 2018, the infrastructure has been publicly available for students, researchers and engineers who need realistic drilling data for technology development, demonstration and education. The simulated drilling data can be accessed by several means. First, through a user-friendly web application used as a tool for teaching the physics involved in drilling operations. Secondly, drilling data can be accessed programmatically through a web API or via programming language APIs written in MATLAB, Python and .NET. Thirdly, OpenLab offers a fast communication interface that can be used for applications that are closer to hardware, and which require a realistic Hardware in The Loop (HIL) infrastructure. This paper describes the objectives of OpenLab as a project, its system architecture, its simulation capabilities, the design of its web application, and its various communication interfaces. The paper also presents projects that uses OpenLab in education, research on machine learning, semantical representation of drilling data, and other industrial relevant activities. The paper is naturally divided in two parts: The design of the infrastructure, and its applications.

Occasionally the drilling fluid pressure exceeds the fracturing pressure and drilling fluid is lost to the formation. Several types of lost circulation materials (LCM) are used to heal such losses. However, in standard testing procedures like American Petroleum Institute Recommended Practice 13-1 or 13-2, only a 100psi or 500psi differential pressure is required in the pressure cell for LCM testing. It is shown that this pressure is by far too small to give any meaningful data for LCM performance. Lost circulation can occur in all well sections. Especially, will lost circulation represent a potential problem during drilling long sections with varying formation strengths and varying formation pressures. In a typical drilling situation, the minimum static overbalance in the well is more than 100psi in order to control the formation pressures and avoid influx of formation fluids into the wellbore. During drilling this overbalance will increase due to, amongst others, frictional effects. These effects, together with variations in formation pressures sometimes lead to dynamic differential pressures exceeding 2000 or even 3000psi. Testing under conditions exceeding the expected maximum differential pressures are meaningful in order to identify the sealing capabilities of LCM materials under such conditions. Some tests focus on losses through tapered slots. In such cases particles larger than the slot outlet will sooner or later contribute to stopping the loss. In a real situation the fracture would be in position to open further. Hence, such tests are not optimal. Other tests are based on slot openings as the minimum size. In such cases the fluids will need to bridge off the opening to work. Based on bridging formation ideas, a development of new LCMs was conducted. These LCMs were able to handle downhole pressure differences. Slotted disks were installed into a high-pressure cell. The slots were 18.00 mm long and 400, 700, 1600, 2000 and 2500μm wide which were made into disks with a diameter of 24.13 mm. Drilling fluid was pumped through the cell and an LCM filter cake was formed across the disk slot. The pressure required to break this filter cake was obtained (unless it exceeds 5000 psi) and recorded. The fluid filtration losses through the apparatus was strongly dependent on the LCM concentration. A set of LCM tests was performed, and examples are given where the LCM actually would withstand a differential pressure 5000 psi across the slotted disks without failing.

Lack of relevant screening methods of oil recovery techniques for water flood with added nanoparticles in a given reservoir are hindering its implementation for enhanced oil recovery (EOR) purposes. Moreover, the understanding of the underlying mechanisms of oil increased by nanoparticles must be improved. In this work, we screened twenty-three different types of silica nanoparticles as additives to injection water for oil recovery applications. The nanoparticles were surface functionalised to remain stable in the injection water and be active at the surface. The hypothesis is that the particles will improve the microscopic oil recovery efficiency of water flood in an oil reservoir. The concentrated solution of nanoparticles were prepared to 0.1 wt % concentration in synthetic North Sea water. Crude oil was obtained from a field in the North Sea. The following investigations were carried out to quickly verify the performance of nanoparticle oil recovery: 1) secondary injection through a visual glass micromodel. 2) For the prominent silica nanoparticles, we evaluated oil recovery by conducting secondary core flooding experiments in water-wet Berea sandstone rocks; and 3) the displacement mechanisms of nanoparticles were investigated by interfacial tension measurements between nanofluids and crude oil; Amott-wettability test; and by analyzing differential pressure across the core. Experimental results from secondary floods showed that modified silica nanoparticles can boost oil recovery. The core flood recoveries ranged from 45.7% to 54.5% of original oil in place (OOIP) compared to 39.7% of reference water flood. Displacement studies revealed that, oil recovery was obtained from a contribution of interfacial tension reduction, wettability alteration, and log jamming effect due to pore blockage. This work suggests a procedure for screening nanoparticles for EOR applications while providing insights into the role of the modified-silica nanoparticles for recovery of oil.

In recent years, nanomaterials have attracted researcher's attention especially in the field of oil and gas. Nanomaterials based research results showed an improved performance in the areas of cement, drilling fluid and enhanced oil recovery. In this study, the effects of Boron Nitride (BN) microparticles on mechanical friction, fluid loss and viscosity were investigated. Boron Nitride (BN) microparticles were dispersed in a solution of Carboxymethylcellulose (CMC) and Fe 2 O 3 nanoparticles were dispersed in Xanthan gum (XG) solution in water. Both fluids were treated with KCl and bentonite to create laboratory drilling fluid systems, which were studied at 22 °C. The results show that the addition of 0.0095 wt. % BN and Fe 2 O 3 reduced the mechanical friction coefficients of the laboratory drilling fluids by 37 %, and 43 %, respectively. Fe 2 O 3 nanoparticles reduced the API static filtrate loss by 14.3 %, but the addition of BN didn't show any impact on filter loss. The particles have also shown an impact on the drilling fluid's viscosity parameters. The essence of this study is to understand the effect of nanoparticles on the drilling fluid performance and to get the better idea of how nanoparticles can contribute to improve the drilling fluid properties.

The concept of the ensemble-based optimization has matured over the last several years and is rooted in the field of reservoir-model-based production optimization. Usually, a backtracking line search scheme is used, but this approach often leads to inefficient searching path direction (e.g. zig-zag patterns). As such, it has some redundancies in finding an optimal solution effectively, increasing the computational overhead with greater risk of problematic numerical instability. Here, we introduce a trust-region conjugate gradient method embedded in EnOpt, motivated by the general applicability and the success in practice. The approach is tested on a synthetic truth model developed by TNO, namely the Brugge benchmark model. The optimization strategy is to control maximum allowed water cut in each connection at which control valves (ICVs) are closed, and the objective is to maximize the net-present-value (NPV). Injectors are controlled using voidage replacement. The methodology performs well on the case considered here. In particular, we use the entire ensemble of controls to adapt the covariance matrix. As such, the gradient estimate of EnOpt is statistically equivalent to that of a Gaussian Mutation Optimization (GMO) algorithm.

Current methods for determining the depth to the top of cement (TOC), blockages, or wellbore features are limited to intrusive applications that require a significant amount of associated time, equipment, risk, and cost. This is a long-standing challenge to operators, particularly when critical decisions need to be made to promptly verify downhole status or remediate flow restrictions to restore production. This paper details a systematic, comprehensive, and proven solution to these challenges using pressure wave analysis. The method is based on analyzing the return reflections generated by a pressure wave transiting the well to and from the blockage location. By capturing high-resolution pressure measurement on an ultrahigh-speed logger, the generated pressure wave can be recorded for analysis. Applying acoustic velocity gradient modeling in conjunction with effects of the well and fluid medium, the distance from the recording location to the blockage can be accurately determined without the use of intrusive or localized external tools. This work shows that the method theory is substantiated by results observed when used during a controlled full-scale field trial in addition to subsequent activities to locate blockages and features within actual wells. A case study is presented demonstrating that the method can be used to identify where a blockage or feature is located. The theoretical method for calculation of acoustic velocity for known system and fluid parameters is shown to be accurate within tolerances compared to the acoustic velocity obtained in the field by recording the time of flight between two known points. It is demonstrated that blockages can be detected to a level of accuracy up to 0.3% of system length, verified by comparison with known measured well construction details. The method presented significantly differentiates itself from traditional depth determination systems and applications. It can provide information with a repeatable and verified level of accuracy without the need for costly and time-consuming intrusive intervention, which allows operators the opportunity to target remediation work in the most efficient and cost-effective manner.

Production at Heidrun is normally limited by the gas handling capacity. Maximum oil production is achieved by producing wells with the lowest gas/oil ratio (GOR) and at the same time utilize the available gas capacity. GOR may change over time, so to obtain desired production it is vital with a continuous follow-up work of well testing and maintenance of multiphase meters. The Heidrun field also has many wells with challenges like; sand entrainment, drifting draw-down, limited draw-down or bottom hole pressure (BHP) and drifting GOR. These elements are crucial to control to achieve desired production. This time-consuming task is handled through a close cooperation between offshore operations and production engineers onshore. Automatic choke control is installed at Heidrun to ensure operation at the maximum gas capacity and keeping the wells at desired operating point. The automatic controllers lead more precise production from each well with a totalized higher production, reduced emissions, reduced operator loads and is a valuable tool for production optimization.

The challenging environment in the Kvitebjørn field offshore Norway comprises high-temperature wells, long drilling hours, low rate of penetration (ROP), managed pressure drilling (MPD), and mud additive requirements, all of which are very detrimental for operations and reliability of the positive displacement motor (PDM) power section. In fact, until now, no one has successfully drilled the 5 ¾-in. section in a single run due primarily to motor failures such as elastomer chunking and debonding. This paper presents the steps used for optimizing the selection of a PDM section to achieve a single-run drilling operation with improved ROP. The method includes understanding the drilling environment, type of wells, rig capabilities, formations, temperatures, MPD, and drilling fluid requirements. Furthermore, the usual motor and bottomhole assembly requirements must be evaluated and the mud compatibility with the elastomer must be scrutinized. All of these variables were then input into a modeling engineering workflow to simulate and analyze the power output, the elastomer fatigue life, the hysteresis heating, and the debonding stress to select the best possible PDM candidate for the drilling job. A new long-life elastomer and the drilling parameters recommended by the mud motor modeling resulted in drilling this section in a single run for the first time in the field. Simultaneously, it was possible to drill to the deepest total depth without any need to set the section total depth shallower, as occurred in previous wells due to motor failures. The motor drilled through a very thick cemented sandstone stringer with no stall incidents. This motor set new records for drilling the 5 ¾-in. section with a total run length 60% longer than the previous longest run and a total pumping time 67% greater than the previous record. The combined new technologies of the modeling and the new long-life elastomer were applied for the first time in the anticipated challenging drilling conditions. The successful results demonstrated that with thorough analysis and proper planning, one can achieve a step change in performance and reliability without additional costs. The scope of the operation is even broader than the mud motor application.

This paper describes the approach, experience and results achieved by a North Sea operator (the Operator) when using purpose-built riserless light well intervention (RLWI) vessels to perform continuous well intervention operations on its subsea fields over the last 10 years. Using RLWI vessels on a continuous basis, the Operator has been able to; achieve a high intervention intensity on its subsea wells (345% increase—from 11 wells in 2006 to 49 wells in 2016), lower the intervention cost per well and improve field recovery factors. The contributory factors to these successes that are covered in this paper are: – Continuous improvements in efficiency during all stages of the intervention operation. This has resulted in the capacity to perform more interventions and hence a lower intervention cost per well. Specifically, over the last 10 years, there has been a 60% decrease in the average number of days to perform an operation. – Improved reservoir management, as a result of regular data acquisition of production and saturation monitoring logs. – Introduction of new technologies and the improved robustness of powered mechanical intervention systems. This has enabled more complex intervention work scopes, such as milling and manipulation of completion components, which would previously have required a modular offshore drilling unit (MODU). The next target, is to reach water depths deeper than 1500 m. Some of the main challenges and equipment upgrades required to work at these depths are discussed.

The micro-sonde well logging system utilizes miniaturized data logging devices, which are released at the bottom of a well and record downhole parameters whilst being transported by fluid flow to surface. The μSonde capsules are designed to be small enough to pass restrictions without obstructing the flow path. Each sonde is activated when launched and thereafter records sensor measurements to a memory. Typical measurements include pressure, temperature, motion and fluid electrical properties. Upon reaching surface, wireless communication transfers the recorded data for analysis. For production wells a magazine carrying μSondes is deployed to the bottom of the well and thereafter, based on predetermined well conditions and/or time intervals, the sondes are released. For drilling operations, the μSonde storage magazine is deployed together with the bottom hole assembly. The sondes are constructed from low density materials such that their effective density can be matched to the well fluid. Applications and design requirements for the μSonde well logging system have been investigated for drilling operations and production well surveys. The development of the micro-sonde (μSonde) well logging system is supported by the Research Council of Norway' Petromaks 2 Ground breaking technology research program.

International standards for well barrier integrity traditionally prescribe cement as annular sealing material. Despite a more than 100-year long history using cementing techniques, a high number of wells have poor annular integrity and are facing sustained casing pressure (SCP). A quality assessment of the cement seal is obtained by return volume and surface pressure trend calculations together with bond logs. All of these measurements are indirect and open for interpretation. Commonly, excess cement volumes are pumped to account for uncertainties but cement failure rate remains high. This paper describes an extensive testing and qualification program performed on a wireless downhole measurement system. Testing has been done on a component and system level basis on the permanently deployed equipment together with the hardware, software and telemetry on the equipment designed to retrieve the data. Focus has been given to robustness and simplicity to accurately capture the data of interest and ensure a fast and reliable download. A direct measurement of annular integrity is now available. A continuous pressure and temperature measurement, named the Well Data Monitor (WDM), can be mounted on the exterior of the casing or liner. The system is non-intrusive to the tubulars and communicates by acoustics through the pipe-wall. No control lines to surface are needed. Interrogation of the sensor pack will provide a full history of events from deployment to the time of download. Hence, historical pressure and temperature data are available from the time of deployment, through the process of establishment of annular barriers to the final verification test. The verification test will provide a direct and non-negotiable measurement of integrity. The development of the WDM was initiated following a need to provide verification for the Well Annular Barrier (WAB) to confirm to Norsok D-010 barrier requirements and to use the WAB as a barrier in open-hole.

A reservoir-conditions coreflood study was undertaken to assist with design of drilling and completion fluids for a Norwegian field. Multiple fluids were tested, and the lowest permeability alterations did not correlate with the lowest drilling fluid filtrate loss volumes. This paper will examine the factors which contributed to alterations in the core samples. A series of corefloods were carried out using core from 2 formations and different drilling fluids. Separate tests were carried out using drilling fluid alone and the full operational sequence. Filtrate loss and permeability measurements combined with interpretative analyses to understand what happened in the near-wellbore. Micro-CT "change maps" gave 3D visualisations of the thickness of operational fluid cakes and extent of retention/clean-up – valuable insights into factors that influence hydrocarbon recovery. All drilling fluids tested had "normal" filtrate loss volumes, with one having notably higher losses with a particular formation. Normally this would be considered a bridging issue and "fixed", but those tests showed comparable or slightly lower alterations in permeability. Analysis showed that, despite deeper constituent infiltration, they were not contributing significant extra damage or retention; the nature of the drilling fluid attachment and cake seemed to be more relevant here than depth of invasion. Other examples will illustrate that the impact of drilling fluid infiltration and retention can range widely, and that there are more key factors than simply filtrate loss volume. Results showed that focusing on the metric of filtrate loss alone may increase risk during drilling fluid selection. Understanding the relationship between filtrate loss, permeability/inflow alteration, retention/clean-up after production is important in selecting fluids as well as giving a better understanding of where improvements can be made. 3D visualisations of the alterations caused by drilling fluid allow conclusions to be drawn when previously there would be speculation.

The Ivar Aasen field was discovered in 2008 and consists of two main groups of reservoirs – the Jurassic and Triassic reservoir zones. The reservoir architecture is complicated by their different depositional settings and by syn- and post-sedimentary faulting. Developing a new field of such complexity is a challenging task that demands a novel approach to optimize well placement and improve reservoir characterization. Reservoir mapping while drilling (RMWD) technology has recently been introduced to the industry, providing an array of deep, directional measurements that are converted to a resistivity map of the formation out to approximately 30 m above and below the borehole. The reservoir mapping results are available for the operator to make geosteering decisions during drilling, to optimize the completion design with inflow control devices after TD, and to update the post-well reservoir model for planning the next wells. This process helps the operator maximize the benefits from the already drilled well on the yet-to-drill wells. The sequence of the wells to be drilled can be logically arranged to leverage the maximum value from the information that reservoir mapping provides. The drilling campaign on the Ivar Aasen field started in summer 2015 and the RMWD technology was used while drilling all the production wells. It revealed that the actual reservoir structure was even more complex than originally expected, and enabled the operator to pursue the best well path to maximize field production potential. This was achieved by using the data to actively geosteer, estimate reservoir producibility (through permeability-thickness calculation) in real-time to decide on TD, and by sidetracking to new targets revealed by the mapping. This new approach can also be applied to infill campaigns on existing fields. In this paper, one of the producer wells are reviewed in details to illustrate the process and demonstrate the results.