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Summary The lateral well position uncertainty of magnetic/gyro measurement-while- drilling (MWD) measurements can often exceed the requirements regarding anticollision, for optimal placement of infill wells between existing producers, or for hitting targets with limited geological extent. The positional uncertainty can be significantly reduced by implementing high-precision drill-bit localization using passive seismic data. Consequently, not only drilling risks can be reduced, but optimal reservoir drainage is ensured as well. By using passive seismic recordings from the seafloor, we can "listen" to the noise generated by the bottomhole assembly (BHA) while drilling. Despite various noise sources in the vicinity (e.g., vessels and rigs), advanced data processing and the combination of hundreds of seafloor receivers spread above the ongoing drilling enable us to detect the drilling signal and locate the drill bit. Whereas the magnetic and gyro MWD tools have errors that accumulate with measured depth (MD), each bit position derived from seismic (usually every 90 seconds) is completely independent. For horizontal sections, the error does not increase with MD and hence can provide improved lateral accuracy. No additional BHA tool is required, and the measurements are neither dependent on the magnetic nor gravitational field. Moreover, the passive seismic measurements can be used to obtain an improved lateral well position estimate. This is done by optimizing the azimuth information of the well trajectory in the minimum curvature method. A lateral uncertainty measure can be derived from the residuals between the passive measurements and the updated well path. Since 2018, we have used the continuous stream of passive data from permanent seafloor sensors at the Grane Field, with its reservoir depth of around 1800 m true vertical depth subsea (TVDSS) to follow all wells with this drill-bit tracking scheme. Lateral deviations from the official well path based on magnetic/gyro measurements are mostly within 30 m. The lateral position uncertainty can be as low as a couple of meters under optimal conditions.
Legends of Artificial Lift This year, the SPE Artificial Lift Conference and Exhibition–Americas will be held 23–25 August in Galveston, Texas, with the theme “Modern Artificial Lift–Adapting to a Changing Industry.” The event provides opportunities for technical professionals to gain insights into current trends and field experiences and explore innovative solutions. A special Legends of Artificial Lift Luncheon on 23 August will celebrate three individuals for their outstanding contributions to the technical knowledge in this field: Norman Hein Jr., Ken Nolen, and Gabor Takacs. Norman W. Hein Jr. Norman W. Hein Jr. has worked for 45 years in upstream production, his distinguished career spanning from research, development, and testing to ventures in production engineering, manufacturing, onshore and offshore project management, industry standardization, and the principles of artificial lift. Hein joined the industry in 1977 as a research scientist with Continental Oil Company, where he learned about oil and gas production materials, failures, fatigue, and offshore construction. He then worked for Conoco and later ConocoPhillips in various engineering positions. In 2010, he joined the sucker-rod division of Norris Production Solutions as director of research, development, engineering, and quality; later at CONSOL Energy he was promoted to chief technology professional and senior advisor. Currently, Hein is president and managing director of Oil and Gas Optimization Specialists Ltd., which he established in 2003. Kenneth B. (Ken) Nolen Kenneth B. (Ken) Nolen for 62 years has been a key contributor to what he calls “the art and science of artificial lift.” “My college degree in mechanical engineering was largely devoted to science,” he explains, “and that’s a branch of knowledge dealing with the physical world of facts and principles. Art, on the other hand, uses science to create new technology and products—in my field, that is to enhance artificial lift.” His career in optimizing this art and science began after graduating from Texas A&M and serving his country in the US Air Force for a 3-year tour. Nolen joined Shell Oil Company as a production engineer before teaming up with Dr. Sam G. Gibbs to become co-founderand vice president of Nabla Corporation in Midland, Texas—a technical service company that specialized in artificial-lift diagnosis, optimization, design, training on pumping wells, and manufacturing pumpoff controllers and fluid-level sounders. “It was at Nabla that I pursued my long-held passion for optimizing production from artificially lifted wells.” Gabor Takacs Gabor Takacs joins the Legends of Artificial Lift as an internationally recognized consultant with more than 35 years of consulting and teaching experience in the fields of production engineering, with a concentration in artificial lift. “The great honor of being nominated is an absolutely thrilling sensation for me,” he said. “It gives me a special satisfaction to be the first foreigner to join those wonderful people whom I have been privileged to meet and cooperate with during my career.” Takacs is a professor emeritus at the University of Miskolc, Hungary, where he led the petroleum engineering department from 1995 to 2012.
Ahmad, Sayyid (Halliburton) | Barrett, Peter (Halliburton) | Fouda, Ahmed (Halliburton) | Guner, Baris (Halliburton) | Jambunathan, Venkat (Halliburton) | Van Beest, Eric (Halliburton) | Nagy-Korodi, István (MOL) | Kemény, Botond (MOL) | Haugestaul, Jon (Three60 Energy) | Spitzmüller, Ádám (Independent Consultant)
Abstract Less than a decade has passed since altered and fractured basement rocks were found to be commercial hydrocarbon reservoirs, and also to be possible providers of migration pathways in some of the fields, which are situated on the Norwegian North Sea. These fractured basement reservoirs are underlying thick clastic successions from Triassic to Quaternary. Recently, a modern oil-based mud resistivity imaging log with ultra-high-resolution was run in two appraisal wells with the aim to understand the complex fracture network in these basement rocks (in off-set wells: biotite-muscovite schist, garnet schist, albite-microcline gneiss, microcline gneiss to sericite-bearing quartzite and cataclasite) which will help in understanding the migration paths, which are deemed vital for further development of this area. This latest generation of oil-based mud imagers required us to question the traditional assumptions that open fractures would have a "Bright" response due to being filled with resistive mud and thus the role drilling mud has in the electro-magnetic response. To gain an image in oil-based mud, high frequencies and short current paths allow capacitive coupling of the formation to the buttons. The signal received is measured by two components, the phase and amplitude. These are affected by resistivity, permittivity, and stand-off. By dealing with the phase and amplitude as complex numbers, we can generate a resistivity dominated impedivity image and a permittivity dominated "imaginary" image. These impedivity and permittivity dominated images plus an understanding of the mud behaviour help to differentiate between the types of fractures to create a more robust localized fracture model. It also proves that the assumption that a fracture has to be "bright" to be open is now invalid (Fig. 1). This paper provides several examples of fractures and how traditional thinking falls down when the effects of solids in the mud and the behaviour of the water phase are considered. The use of permittivity dominated images is to help identify and classify fractures, which may be missed by just looking at resistivity-based images is also demonstrated.
Horstman, Mathias (Schlumberger) | Shrivastava, Chandramani (Schlumberger) | A., Adrian (Schlumberger) | Goswami, Rishav (Schlumberger) | Sikdar, Koushik (Schlumberger) | Bakke, Beate A. (Lundin Energy) | Aasheim, Odd (Lundin Energy) | Kollien, Terje (Lundin Energy) | Stirø, Øyvind (Lundin Energy)
Abstract Real-time geological interpretation while drilling can be achieved with high-resolution borehole images; however, the use of different drilling fluids, telemetry-related limitations, and non-optimal depth control on rigs often leave geoscientists with limited and poorquality data, leading to inconsistencies over a field's life cycle. This study from offshore Norway presents applications of new measurements and algorithms to address such challenges providing consistent borehole imaging for geological interpretations while drilling complex subsurface. New multi-physics high-resolution LWD (logging while drilling) technology was deployed for real-time imaging in boreholes drilled with nonconductive fluids, addressing technology gaps that earlier allowed such services only in conductive aqueous fluids and providing much-needed independence to drill various well trajectories in any mud configuration without limiting high-resolution imaging for geological, petrophysical, and geomechanical interpretation. Correspondingly, real-time data transmission challenges were addressed with improved mud-pulse telemetry and wired drill-pipe. Furthermore, new application algorithms were developed to compensate for inadequate depth control impacting the integrity of high-resolution data. We present results from field development operations in the Utsira High region of the Norwegian North Sea, including examples of pilot and lateral sections drilled with conductive and nonconductive fluids. Conventional evaluation of the encountered heterogeneous mix of alluvial fans, plains, and aeolian dune facies is difficult, even more in horizontal drains where standard logs are often featureless across problematic conglomerates. Real-time dips picked on high-definition images helped with geosteering as well. Examples of geological features from different wells are presented with unique resistivity images from new LWD borehole imager for nonconductive fluid, comparing with image data acquired in conductive mud for consistent interpretation. Structural elements of sub-seismic faults and fractures were interpreted with consistency to provide geologists with confident feature-picks for updating their reservoir models. Introduction: LWD Imaging Borehole images have long been used by geologists and log analysts for various aspects of reservoir characterization and well-operations support. However, most of these applications were earlier possible only with e-line logging after drilling operation was complete and the open-hole needed to be left for wireline operations. Logging while drilling (LWD) imagers often provided lower resolution data compared to Wireline, that too in recorded mode whilst the real-time data streamed while drilling often lacked the quality to pick the subtle features with confidence to subject the data for further interpretation. Technology advances in LWD imaging brought higher resolution imagers to operations and resistivity and ultrasonic images were made available compared to the legacy photo-electric (PEF), density and gamma-ray (GR) images (Fig 1). The recorded mode (memory) data started to approximate wireline imaging quality in water-base mud (WBM). Oil-base mud (OBM) LWD imaging for geological interpretation remained a challenge till Maeso (2018) presented a new dual physics imager. Shrivastava (2019, 2020) presented a brief account of borehole imaging journey, and the multiphysics LWD imager that overcame the barrier of OBM imaging.
Abstract Permeability models largely rely on core measurements as input. The propagation of these models beyond the cored interval is often by use of the empirical porosity-permeability relationship. The problem is that porosity itself does not contain information about the pore geometry which controls permeability, hence these relationships carry high uncertainty in uncored intervals and nearby wells. Dielectric dispersion, on the other hand, is inherently linked to the pore geometry since it is sensitive to charge build up at the rock-fluid interfaces of the interconnected pore network through the Maxwell-Wagner effect. We aim to utilize this connection between pore geometry and dielectric dispersion to predict permeability using a core-data trained supervised machine learning model on dielectric dispersion wireline logging arrays. It builds upon a previous single-well study (Norbisrath, 2018) where the main concern was the repeatability in other wells, which is now addressed here. The study area is the Johan Sverdrup field on the Norwegian Continental Shelf. Data consists of core plug permeabilities and dielectric dispersion wireline logs from five wells. Capturing the dielectric frequency dispersion involves determining the slope of both attenuation and phase shift measurements made at different frequencies and transmitter-receiver spacings (feature engineering). The model will be trained on a subset of the core data (supervised machine learning), and subsequently propagated along the entire logged interval, as well as to the test well which was not part of the training set. Hyperparameter tuning will be used to optimize the model, and cross-validation used to prevent overfitting. Preliminary results show that the dielectric dispersion logging data contains enough information about the pore geometry to accurately describe and predict core plug permeabilities, not only in the same well but also in nearby wells that were not used in training the model. Correlation coefficients between estimated and predicted core permeability values are around R = 0.8. Given additional training input data and ground truthing in other wells, the described method could potentially reduce the need for coring when dielectric dispersion wireline logs are run. In the future we aim to explore the possibility of using dielectric dispersion data from LWD (Logging While Drilling) resistivity propagation tools as input for our permeability predictions. This would greatly enhance formation evaluation since these data are readily available in thousands of wells and are generally acquired in every new well. A model trained on a large amount of existing core data could enable real time permeability predictions from LWD tools.
Gupta, Shilpi (Schlumberger) | Vindheim, Helge (Repsol Norge AS) | Govil, Amit (Schlumberger) | Obando, Guillermo (Schlumberger) | Kumar, Apoorva (Schlumberger) | Agrawal, Gaurav (Schlumberger) | Dutta, Shaktim (Schlumberger)
Abstract The Gyda field in the North Sea operated by Repsol was proven in 1980 and the platform started producing in 1990. In June 2017, the Norwegian authorities approved the decommissioning plan for the Gyda field. The decommissioning scope included the permanent plugging of 32 wells in the field. Decommissioning is estimated to cost several hundred million dollars and is expected to finish in 2022. As per the NORSOK standards, each well needs to have confirmed barriers to isolate inflow zones, both for preventing from flowing to the surface and hindering crossflow between them. Cement and creeping formation are both considered to be potentially effective barrier elements. However, the criteria and verification methods used to confirm formation creep and cement as barrier elements are different and hence require an innovative interpretation technique which is presented in this paper. As per the regulations and standards, it is critical not only to evaluate the quality of the circumferential bond for cement and formation creep but also to determine their respective bond length. The most important measurement to accurately determine those criteria in each well is through the ultrasonic and flexural attenuation tool. However, interpretation to differentiate formation creep from cement presents challenges, especially when they have similar ultrasonic properties. Quite often, they coexist at the same depths on different sides behind the casing. Barrier evaluation becomes even more challenging with added complexities such as borehole mud settling due to high deviation, high eccentricity, casing damage, or presence of a microannulus. This paper discusses the techniques and interpretation methods used to accurately evaluate barrier elements, differentiate between cement and formation creep, estimate the tops of cemented areas, and eliminate complex challenges posed by mud, deviation, eccentricity, and wet microannulus sections. Successful and accurate determination of the potential presence and location of annulus barrier elements has been fundamentally important for Repsol to meet the regulatory requirements. A special interpretation technique was established using integrated data evaluation to differentiate creeping formation from cement. This technique successfully determined accurate barrier intervals, helping to meet all the regulatory requirements. The processes and methods have been audited and evaluated by the Petroleum Safety Authority Norway.
Andersen, Pål Østebø (Department of Energy Resources, University of Stavanger, Norway) | Skjeldal, Miranda (Department of Energy Resources, University of Stavanger, Norway) | Augustsson, Carita (Department of Energy Resources, University of Stavanger, Norway)
Abstract Accurate estimation of reservoir parameters such as fluid saturations and porosity is important for assessing petroleum volumes, economics and decisionmaking. Such parameters are derived from interpretation of petrophysical logs or time-consuming, expensive core analyses. Not all wells are cored in a field, and the number of fully cored wells is limited. In this study, a time-efficient and economical method to estimate porosity, water saturation and hydrocarbon saturation is employed. Two Least Squares Support Vector Machine (LSSVM) machine learning models, optimized with Particle Swarm Optimization (PSO), were developed to predict these reservoir parameters, respectively. The models were developed based on data from five wells in the Varg field, Central North Sea, Norway where the data were randomized and split into an unseen fraction (10%) and a fraction used to train the models (90%). In addition to the unseen fraction, a sixth well from the Varg field was used to assess the models. The samples are mainly sandstone with different contents of shale, while fluids water, oil and gas were present. The ‘seen’ data were randomized into calibration, validation and testing sets during the model development. The petrophysical logs in the study were Gamma-ray, Self-potential, Acoustic, Neutron porosity, bulk density, caliper, deep resistivity, and medium resistivity. The log based inputs were made more linear (via log operations) when relevant and normalized to be more comparable in the algorithms. Feature selection was conducted to identify the most relevant petrophysical logs and remove those that are considered less relevant. Three and four of the eight logs were sufficient, to reach optimum performance of porosity and saturation prediction, respectively. Porosity was predicted with R2 = 0.79 and 0.70 on the model development set and unseen set, for saturation it was 0.71 and 0.61, a similar performance as on the training and testing sets at the development stage. The R2 was close to zero on the new well, although the predicted values were physical and within the observed data scatter range as the model development set. Possible improvements were identified in dataset preparation and feature selection to get more robust models.
Norway's Ministry of Petroleum and Energy (MPE) has extended production licenses in the Greater Ekofisk Area from 2028 to 2048 with ConocoPhillips as operator. The company said the license extension provides long-term operations and resource management aligned with the company's long-term perspective on the Norwegian continental shelf. Fields on the shelf are required to operate with a valid production license where the operator and licensees enter into an agreement with the authorities, including relevant field activities. The authorities may require commitments, leading to increased oil recovery. The existing production licenses 018, 018 B, and 275 in the Greater Ekofisk Area were set to expire on 31 December 2028; however, the MPE approved an extension through 2048.
Kaasa, Baard (Scale Consult) | Somme, Bodil (Spirit Energy) | MacDonald, Ross (Spirit Energy) | Kjørsvik, Kristin (Spirit Energy) | Saunes, Anders (Spirit Energy) | Heath, Stephen (Creative Chemical Solutions Ltd) | Stamnes, Marius (Scale Protection)
Abstract In this paper we will tell the story of a sub-sea well in the Oda field where the predicted downhole calcium sulphate (CaSO4) scale risk did not concur with observations in the field. Seawater was injected into the oil leg and the first sample collected at 5% water cut had ~ 80% seawater breakthrough, with a harsh CaSO4 scaling tendency predicted (SR 3.5 at 120°C). A squeeze treatment was planned as part of the mitigation strategy and, in addition, continuous downhole injection of scale inhibitor (SI) was instigated to provide protection to the production tubing, flow line and topside facilities. An extensive monitoring program consisting of productivity monitoring, weekly produced water ionic composition and ESEM/EDX bulk scale analysis (BSA) was instigated to confirm the scaling risk. The water cut increased as did the seawater content to ~90%, however, the results of the BSA did not indicate any significant amounts of CaSO4 scale on the filters indicating stable produced water. Scale and 1D reservoir simulations also showed that to match the produced water composition with the correct FW:SW ratio, CaSO4 should have precipitated in the reservoir, but not to equilibrium resulting in a produced water with SR higher than one. In addition, a further increase in seawater content would lead to lower scale risk and the produced water was confirmed as stable even with a calculated SR of about 3-3.5. Several scale prediction models were evaluated with the same outcome. A new scaling risk matrix created from the BSA field data, backed up by the trends in measured vs predicted ion data, indicated no significant scale risk to the Oda well which is in contrast to what was predicted. Based upon this data it was agreed that the planned squeeze treatment was no longer required, but this still raised the question of why the well didn't scale. Several theories including metastability, natural inhibition and kinetic effects coupled with partial protection by downhole injection of SI will be discussed. In addition, this paper will highlight the benefits of using a holistic, integrated scale management strategy, consisting of scale and reservoir simulations combined with field data (ions and BSA), to identify a more realistic field risk and save unnecessary treatment costs.