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Collaborating Authors
Lunde Formation
The Mula River basin is in an active tectonic region of the Kirthar fold fault belt in Western Himalayas. The presence of numerous major faults like Chaman Fault, Kirthar Frontal Fault and Bannh Fault near the study suggest complex tectonic processes in the region. The seismic record of the study area also indicates that this area is tectonically active. This makes the study area an ideal site to measure tectonic activity through geomorphic indices like hypsometric integrals (HI). For tectonic analysis of the Mula River basin, we divided the study area into 309 sub-basins. The results obtained from the HI calculations for the sub-basins led us to the classification of the study area into three classes i.e., Class 1 (0.51-0.78), Class 2 (0.37 0.50) and Class 3 (<0.37), where Class 1 is for the highest tectonic activity and Class 2 responds to the moderate and class 3 is for the lowest tectonic activity. We calculated the hypsometric curves to understand the geomorphological cycle of the Mula River basin. We quantified the sub-basins of the Mula River basin, inside the highly active tectonic zone of Kirthar fold and fault zone, as per their tectonic activity and found that a major portion of the study area shows low tectonic activity (44.33%), medium tectonically active and high tectonically active sub-basins are 37.86 % and 17.79 % respectively. These findings are supported by the presence of high-relief areas and known faults in the study area.
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.95)
- Geology > Structural Geology > Tectonics > Compressional Tectonics > Fold and Thrust Belt (0.83)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Statfjord Group (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Lunde Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Lista Formation (0.99)
- (5 more...)
A Hybrid Data-Physics Framework for Reservoir Performance Prediction with Application to H2S Production
Leeuwenburgh, Olwijn (TNO (Corresponding author)) | Egberts, Paul J. P. (TNO) | Barros, Eduardo G. D. (TNO) | Turchan, Lukasz P. (Bluware) | Dilib, Fahad (Equinor ASA) | Lødøen, Ole-Petter (Equinor ASA) | de Bruin, Wouter J. (Equinor ASA)
Summary Model-based reservoir management workflows rely on the ability to generate predictions for large numbers of model and decision scenarios. When suitable simulators or models are not available or cannot be evaluated in a sufficiently short time frame, surrogate modeling techniques can be used instead. In the first part of this paper, we describe extensions of a recently developed open-source framework for creating and training flow network surrogate models, called FlowNet. In particular, we discuss functionality to reproduce historical well rates for wells with arbitrary trajectories, multiple perforated sections, and changing well type or injection phase, as one may encounter in large and complex fields with a long history. Furthermore, we discuss strategies for the placement of additional network nodes in the presence of flow barriers. Despite their flexibility and speed, the applicability of flow network models is limited to phenomena that can be simulated with available numerical simulators. Prediction of poorly understood physics, such as reservoir souring, may require a more data-driven approach. We discuss an extension of the FlowNet framework with a machine learning (ML) proxy for the purpose of generating predictions of H2S production rates. The combined data-physics proxy is trained on historical liquid volume rates, seawater fractions, and H2S production data from a real North Sea oil and gas field, and is then used to generate predictions of H2S production. Several experiments are presented in which the data source, data type, and length of the history are varied. Results indicate that, given a sufficient number of training data, FlowNet is able to produce reliable predictions of conventional oilfield quantities. An experiment performed with the ML proxy suggests that, at least for some production wells, useful predictions of H2S production can be obtained much faster and at much lower computational cost and complexity than would be possible with high-fidelity models. Finally, we discuss some of the current limitations of the approach and options to address them.
- North America > United States > Texas (0.68)
- Europe > Norway > Norwegian Sea (0.46)
- Europe > Norway > North Sea > Northern North Sea (0.29)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 128 > Block 6608/10 > Norne Field > Tofte Formation (0.99)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 128 > Block 6608/10 > Norne Field > Not Formation (0.99)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 128 > Block 6608/10 > Norne Field > Ile Formation (0.99)
- (10 more...)
- Information Technology > Modeling & Simulation (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.46)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.46)
Integrated Workflow for Reservoir Management in Mature Waterflooded Reservoir within a Complex Geological Environment: Gullfaks Case Study
Kareb, Ahmed (University of Houston, Houston) | Dindoruk, Birol (University of Houston, Houston) | Chiboub-Fellah, Abd Elaziz (IFP School, Paris) | Gareche, Mourad (University of Boumerdes, Boumerdes)
In the context of field development planning, the project workflow has to be outlined beforehand to ensure the most optimal and accurate outcomes within time limits. The workflow started by utilizing a G&G software, Petrel, to depict the rock type and fault distribution within the geological models by incorporating interpreted seismic data and well logs. This integrated approach facilitated a comprehensive understanding of the reservoir's structural and geological characteristics. Furthermore, standard geostatistical techniques applied in software generated property models that ensured alignment of permeability and porosity distribution with the corresponding well logs. Interpretation of production data, PVT, and SCAL served as the basis for initializing the model using a reservoir simulator, Intersect, as a dynamic flow simulator. The accuracy and reliability of the model were ensured through quality checks, which include volume estimate comparison starting with equilibrium runs. Additionally, sensitivity analysis was performed by adjusting model parameters to achieve a history match and align simulated results with actual reservoir behavior in various ways. The calibrated model explored using a high-resolution simulator for high accuracy and more options for development strategies such as infill wells (horizontal and vertical), well conversions, water shut-off (zonal isolation and selective perforation), stimulation operations, and ESP systems in order to optimize reservoir performance and maximize production while improving sweep efficiency. Lastly, economic evaluation based on net present value (NPV) analysis considered techno-economic factors to identify the most suitable development strategy that balanced technical feasibility with economic viability.
- North America > United States (0.94)
- Europe > Norway > North Sea > Northern North Sea (0.70)
- Geology > Rock Type (0.88)
- Geology > Geological Subdiscipline (0.68)
- Geology > Structural Geology > Fault (0.47)
- Geophysics > Borehole Geophysics (0.88)
- Geophysics > Seismic Surveying (0.54)
- North America > United States > North Dakota > Williston Basin > Bakken Shale Formation > Middle Bakken Shale Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > Statfjord Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Statfjord Group (0.99)
- (7 more...)
- Information Technology > Software (0.50)
- Information Technology > Modeling & Simulation (0.47)
- Information Technology > Software Engineering (0.41)
Pre-Drill Geomechanical Modelling and Wellbore Stability Analysis for Successful Drilling in a Highly Overpressured Shale Zone and Potential Losses Carbonate Zone - A Case Study from West Tuban Block, East Java, Indonesia
Mikhael Chrislianto, Reynaldi (Baker Hughes) | Sagita, Romi (Baker Hughes) | Ghosh, Amitava (Baker Hughes) | Meidiya Putra, Riko (Pertamina Hulu Energi) | Hisanah, Nabilah (Pertamina Hulu Energi)
Abstract A high pressure well with a high risk of encountering a loss zone is a challenging drilling operation and requires a proper pre-drill study incorporating drilling practices, an understanding of the subsurface, and geomechanical modelling. This paper presents a case from the West Tuban Block. This block is within the East Java Basin, one of the prolific basins in Indonesia and a proven hydrocarbon reserve. The major challenge is drilling through the shale overpressure zone and the carbonate loss zone safely and successfully. This paper describes the building of a pre-drill geomechanical model, the subsequent wellbore stability analysis and how the results and recommendations were applied during drilling. The geomechanical model was built using data from seven offset wells and also incorporated regional knowledge. The offset well review of the drilling experiences showed that the key challenges that will need attention are significant drilling problems such as pack-off and tight hole while POOH, RIH with casing and while wireline logging. Added to this are instances of losses and gains while drilling the carbonate reservoir section. The geomechanical modelling process involves using petrophysical, geological, geophysical and drilling data to constrain the magnitudes of the overburden, pore pressure, rock mechanical properties and the two horizontal principal stresses. It is also important to constrain the azimuth of the maximum horizontal stress. The final model is verified using stress-related drilling problems and observations of wellbore failure in shale interpreted from caliper data. The resultant geomechanical model suggests that the planned well is associated with a strike-slip stress regime. The magnitudes and azimuths of the stresses play an important role in successful drilling because the well is directional in the reservoir section with a maximum inclination ∼26°. The wellbore stability analysis was used to optimise mud weights for each hole section of the planned well. Recommendations were also made regarding additional data gathering (cores for conducting rock tests, extended leak-off tests, full suite of logs, etc.) to reduce uncertainty in the geomechanical model. The mud weight and drilling practice recommendations, that were an outcome of the study, were followed meticulously by the drilling team so the well was able to safely overcome the overpressure zone and the loss zone. The effort contributed to the operator's success in the onshore development campaign with timely execution within budget and no reported HSE events.
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.82)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.33)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Statfjord Group (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Lunde Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 050 > Block 34/10 > Gullfaks Field > Lista Formation (0.99)
- (4 more...)
Equinor's Hywind Tampen wind farm, the world's largest floating offshore wind farm, opened in August. The farm consists of 11 wind turbines with 88 MW of capacity that will cover around 35% of the annual power demand for five platforms at the Snorre and Gullfaks oil and gas fields in the North Sea, according to Reuters. The farm is expected to reduce 200 000 tonnes of CO2 annually. "With Hywind Tampen, we have shown that we can plan, build, and commission a large, floating offshore wind farm in the North Sea. We will use the experience and learning from this project to become even better," Siri Kindem, head of Equinor's renewables business in Norway, said in a company press release.
- North America > United States (1.00)
- Europe > United Kingdom > North Sea (0.48)
- Europe > Netherlands > North Sea (0.48)
- (2 more...)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Statfjord Group (0.94)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Lunde Formation (0.94)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/4 > Snorre Field > Statfjord Group (0.94)
- (14 more...)
Abstract Meeting the Paris Agreement targets and rapidly transitioning towards renewable energy are critical. Despite significant renewable energy growth, projections indicate fossil fuels will meet almost half the UK's energy demand by 2050. The oil and gas industry is facing increasing decarbonization mandates due to environmental concerns and the need for a sustainable energy future. However, the UK is unlikely to completely achieve its Nationally Determined Contribution (NDC) target. Offshore oil and gas industry emissions are primarily due to energy-intensive processes that could be significantly reduced by shifting towards more sustainable practices and electrifying these processes. The West of Shetland region holds strategic significance in energy security, economic contributions, and potential for further exploration. The rapidly evolving offshore wind power sector and technological innovations in this field present a promising path towards a sustainable energy future. However, the electrification of oil and gas assets in the West of Shetland area will encounter challenges relating to grid connectivity, wind intermittency, environmental impact, and potential large-scale wind power generation elsewhere in the UK. Three key network design options are suggested for supplying required offshore electricity: a coordinated approach, an individual approach, and a local supply approach. There are three key groupings in the West of Shetland region: the Clair grouping, Schiehallion-Lancaster-Solan, and Rosebank-Cambo. Each has potential for electrification, but also unique challenges to be addressed. The adoption of renewable energy and energy storage technologies for oil and gas facilities in the West of Shetland area involves a variety of factors. Initial costs can be substantial, especially offshore, but these could be offset in the future due to tightening emissions regulations and carbon pricing. Older assets nearing their end of life may not be worth electrifying. Overcoming these challenges necessitates a collaborative strategy among industry players, the government, and regulators. Norway is leading in electrification, while the UK North Sea is moving much more slowly. A coherent energy policy for the West of Shetland area addressing oil and gas developments alongside renewable energy developments appears essential.
- Europe > United Kingdom > Atlantic Margin > West of Shetland > West Shetland Basin > Block 204/9 > Cambo Field > Corona Ridge Formation (0.99)
- Europe > United Kingdom > Atlantic Margin > West of Shetland > West Shetland Basin > Block 204/10 > Cambo Field > Corona Ridge Formation (0.99)
- Europe > United Kingdom > Atlantic Margin > West of Shetland > Faroe-Shetland Basin > Rona Ridge > Block 206/9 > Clair Field (0.99)
- (75 more...)
Equinor announced this week the opening of the Hywind Tampen wind farm that was built to help power some of its offshore oil and gas platforms. With a capacity of 88 MW, the 11-turbine project stands out as Norway's first offshore wind installation and also the world's largest to employ the floating concept. Equinor is also hoping that the new floating asset becomes a template for future wind projects in the deepwater where there are just a small handful. Located almost 140 km offshore Norway, each of the 8-MW turbines are installed in depths ranging from 260 to 300 m. The turbines have been operational since November but Equinor said they achieved full capacity for this first time this month.
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Statfjord Group (0.94)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/7 > Snorre Field > Lunde Formation (0.94)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 375 > Block 34/4 > Snorre Field > Statfjord Group (0.94)
- (14 more...)
Summary Over the past years, it has become clear that greenfield oil production forecasts are subject to strong optimism and overprecision biases: Significant early production shortfalls are the rule rather than the exception and the elicited uncertainty range is generally too narrow. This has large negative consequences for the net present valuation of such investments. A study from 2011 based on post-factum evaluation of greenfield production forecasts suggests that there is a causal relationship between certain project/field characteristics and production attainment (i.e., optimism bias). However, while self-reported causes of failure may provide interesting insights, such analyses are subject to cognitive hindsight bias. It is therefore necessary to test such claims more rigorously. Research on megaprojects in other industries suggests that forecasting bias is omnipresent but is stronger in certain circumstances (e.g., information and communication technology projects are subject to larger cost overruns than road construction projects). An important question is therefore whether there are combinations of field characteristics/features which can be measured objectively, such as field size, reservoir complexity, oil prices, and lack of drillstem tests (DSTs), etc., and which can be shown to have predictive power of overly optimistic and overconfident production forecasts. The data set in this study consists of 71 greenfield oil production forecasts at project sanction on the Norwegian Continental Shelf (NCS), with production starting between 1995 and 2020. Each forecast consists of a triplet of production curves which represent the statistical p10, the expectation, and the statistical p90. The forecasts are compared with actual production data. Metadata about the fields gathered from the Norwegian Petroleum Directorate (NPD) are used to establish 16 informative field features, from field reserves to the number of appraisal wells per unit area. These features are tested for predictive power, both individually and simultaneously, of optimism bias and of a general forecast quality metric. First, we show that value erosion caused by time overruns and production shortfalls are both significant, but that the relative importance of effects after production start is higher. Second, none of the tested machine learning models show any predictive power of forecasting bias. Because of this systematic presence of bias in the production forecasts, we argue that oil and gas companies need to make important changes to their decision-making workflows to take into account well-documented research findings on cognitive and organizational bias from the past decades, instead of the ever-increasing model complexity. Illustratively, as a final point, we show that a no-skills-involved reference class forecast based on empirical production curves from abandoned fields outperforms operators’ own greenfield forecasts. This approach may perhaps serve as a useful benchmark for future forecasts.
- Europe > Norway > North Sea > Northern North Sea (0.28)
- North America > United States > Montana > Sheridan County (0.24)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 120 > Block 34/8 > Gimle Field > Lunde Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 120 > Block 34/8 > Gimle Field > Brent Group Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > East Shetland Basin > PL 120 > Block 34/8 > Gimle Field > Amundsen Formation (0.99)
- (28 more...)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Production forecasting (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring (1.00)
- Management > Strategic Planning and Management > Project management (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
The Near-Surface Electromagnetic Induction special section The manuscript peer-review turnaround times are essentially was proposed by Associate Editors Colin Farquharson and Mark flat in the past few years, mostly because of the switch to Everett, and they were so dedicated that they volunteered to be a Web-based peer-review process implemented by my predecessors.
- South America (1.00)
- Europe (1.00)
- Asia > Middle East (1.00)
- (4 more...)
- Research Report (1.00)
- Personal > Honors (1.00)
- Overview (1.00)
- (2 more...)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type (0.67)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.46)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Magnetic Surveying (1.00)
- Geophysics > Electromagnetic Surveying (1.00)
- (6 more...)
- Law (1.00)
- Government > Regional Government > North America Government > United States Government (1.00)
- Government > Regional Government > Asia Government (1.00)
- (8 more...)
Abstract Most companies to date have adopted GHG emission targets in an effort to limit global warming well below 2 °C above pre-industrial levels, and 2020 estimations forecast a decrease of about 1/3 of emissions from O&G activities by 2050. It is also foreseen that regulations with economic impact on emissions from hydrocarbon production will be progressively adopted. This is triggering oil and gas (O&G) attention to find faster and economic ways to decarbonize while maintaining operational performance. Several types of initiatives are being considered including the reduction of flaring and venting, mitigation of methane leaks, increasing efficiency in energy use, use of renewable energy, and electrification of processes, in combination with the use of digital tools, and advanced monitoring to optimize performance. In this work we focus on a comparison of different decarbonization pathways for an offshore platform. It is assumed that the platform is already in place and in operation, and that the industry is already taking the required actions to reduce flaring and venting and mitigating methane leaks. The analysis starts by identifying the major contributors to the GHG emissions from the platform, which in this case is the power system, followed by fluid related processes like compression, separation, heating for transportation, and other associated operations. Public data from international energy agencies indicates that approximately 16 TWh/year is used to power offshore oil and gas platforms globally. We analyze the following five decarbonization pathways: a) improved energy use - decreasing the energy demand of the processes running on the platform and associated operations, b) increasing the efficiency of the power generation source, c) changing the nature of power source (renewable – wind, solar, wave, hybrid systems), d) implementing carbon capture units, and e) electrifying the facility (partial/full electrification cases). The analysis includes a comparison of promising concepts under each of the proposed pathways and summarize the challenges and opportunities offshore O&G operators have to implement them. Some of the alternatives are based on technology already used in the oil and gas industry, or in other industries, while in some others the technology is still under development. Reference is made to novel technology with potential to address the identified challenges for the different pathway options. We use a simplified metric system to highlight the most effective solutions according to location of the platform and its distance to shore. A discussion of what we will be needed for such pathways to be feasible is also presented.
- North America > United States (1.00)
- Europe > Norway > North Sea > Central North Sea (1.00)
- Asia (1.00)
- Europe > United Kingdom (0.93)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 093 > Block 6407/9 > Hasselmus Field > Ror Formation (0.99)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 093 > Block 6407/9 > Hasselmus Field > Ile Formation (0.99)
- Europe > Norway > Norwegian Sea > Halten Terrace > PL 093 > Block 6407/9 > Draugen Field > Ror Formation (0.99)
- (97 more...)