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If a contest or a division is not held in your assigned region, you can request to present your paper in an assigned alternate region. Every region has only one alternate region. To make an alternate region paper request, or if the alternate region is not holding a contest, please contact spc@spe.org.
Brazilian independent Enauta has agreed to sell a 20% participating interest in the BS-4 concession, which includes the Atlanta and Oliva fields, to Westlawn Americas Offshore (WAO) for 301.7 million. WAO is a portfolio company of Westlawn Group LLC and owns various interests in the Gulf of Mexico offshore basins. Enauta said the sale amount will be paid at closing and subject to adjustments related to the net cash flow with investments for the delivery of Atlanta and Oliva generated between the effective date of 1 November 2023 and the transaction closing date. As part of the transaction, 75 million will be paid over the coming 60 days as a loan to be deducted from the amount paid at closing. The transaction also includes an option to sell a 20% stake in Atlanta Field B.V. (AFBV) for 65 million in 2024 upon agreement.
- North America (1.00)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean (0.99)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Santos Basin > Block BS-4 > Atlanta Field > Marambaia Formation (0.99)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Campos Basin > Block BMโCโ36 > Tartaruga Verde Field (0.99)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean > Campos Basin > Block BMโCโ36 > Tartaruga Mestica Field (0.99)
- South America > Brazil > Brazil > South Atlantic Ocean > Santos Basin (0.99)
Patricia de Lugรฃo received a Bachelor of Science degree in environmental engineering and water resources from the University of South Carolina in 1988, a master's degree in geophysics from the Observatรณrio Nacional in Rio de Janeiro in 1992 and a Ph.D. in geophysics from University of Utah in 1997. At Observatรณrio Nacional, she worked with Sergio Fontes on the acquisition, processing, and modeling of magnetotelluric data from the Recรดncavo Basin, Brazil. During her Ph.D. studies at the University of Utah, de Lugรฃo had the good fortune to work with Phil Wannamaker and Michael Zhdanov on the development of modeling and inversion algorithms for magnetotellurics. After her Ph.D., de Lugรฃo worked in the research department at Western Atlas in Houston with Kurt-Martin Strack, where she applied her knowledge in modeling and inversion to the development of algorithms for array borehole tools. In the Geosignal division of Western Atlas, Patricia worked with Lee Bell on two- and three-dimensional refraction tomography techniques for statics correction and initial velocity model for prestack depth migration of seismic data from the foothills of South America to the Gulf of Mexico.
- North America > United States > Utah (0.47)
- South America > Brazil > Rio de Janeiro > Rio de Janeiro (0.26)
- Geophysics > Electromagnetic Surveying (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.72)
- Geophysics > Seismic Surveying > Seismic Processing (0.57)
- South America > Brazil > Brazil > South Atlantic Ocean > Santos Basin (0.99)
- South America > Brazil > Bahia > Reconcavo Basin (0.99)
- Information Technology > Knowledge Management (0.76)
- Information Technology > Communications > Collaboration (0.76)
Fourier domain vertical derivative of the nonpotential squared analytical signal of dike and step magnetic anomalies: A case of serendipity
de Souza, Jeferson (Paranรก State Secretary of Education) | Oliveira, Saulo Pomponet (Federal University of Paranรก) | Szameitat, Luizemara Soares Alves (Universidade Do Estado Do Rio de Janeiro โ UERJ) | de Souza Filho, Oderson Antรดnio (Geological Survey of Brazil (CGA/SGB)) | Ferreira, Francisco Josรฉ Fonseca (Federal University of Paranรก)
ABSTRACT Vertical derivatives of nonpotential fields are, intentionally or not, often performed in the Fourier domain producing nonphysical but interpretable results. Using the dike model, we prove that the vertical derivative of the squared analytic signal amplitude calculated in the Fourier domain does not correspond to the true one. We derive an analytical expression for this pseudovertical derivative, providing a mathematical meaning for it. One significant difference between the pseudo and true vertical derivative is that the former possesses real roots, whereas the latter does not. Taking advantage of this attribute, we find using synthetic and field data that the pseudovertical derivative can be used for qualitative and quantitative interpretation of magnetic data, despite being nonphysical. As an example of the usefulness of this filter in qualitative interpretation, we convert the image of the pseudoderivative to a binary image where the anomalies are treated as discrete objects. This allows us to morphologically enhance, disconnect, classify, and filter them using the tools of shape analysis and mathematical morphology. We also illustrate its usefulness in quantitative interpretation by deriving a formula for estimating the depths of magnetic thin dikes and infinite steps. Our outcomes are also corroborated by the observation of outcrops found by field surveys.
- South America > Brazil (1.00)
- North America (0.93)
- Geology > Geological Subdiscipline (0.46)
- Geology > Structural Geology > Tectonics (0.46)
- North America > United States > New Mexico > San Juan Basin (0.99)
- North America > United States > Colorado > San Juan Basin (0.99)
- North America > United States > Arizona > San Juan Basin (0.99)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (0.72)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (0.46)
Borehole geophysics is well established in the oil and gas industry, assisting geoscientists in a wide range of key applications, such as geological and reservoir quality assessment, well-to-seismic ties, seismic imaging, velocity modelling, geosteering and reservoir monitoring to name just a few. For academia/research institute and student registration please contact sshahir@seg.org Mr. Ms. First/Given Name ZIP/Postal Code Country Address listed: Business Home Are you a student? All check payments are required in US Dollars ($) on US Banks only. From outside the US, you can process payments in your local currency with Flywire.
- South America > Brazil > Bahia (0.26)
- North America > United States (0.17)
Toward Real-time Fracture Detection on Image Logs Using Deep Convolutional Neural Networks , YoloV5
Azizzadeh Mehmandost Olya, Behnia (University of Tehran) | Mohebian, Reza (University of Tehran) | Bagheri, Hassan (University of Tehran) | Mahdavi Hezaveh, Arzhan (University of Tehran) | Khan Mohammadi, Abolfazl (Memorial University of Newfoundland)
Fractures in reservoirs have a profound impact on hydrocarbon production operations. The more accurately fractures can be detected, the better the exploration and production processes can be optimized. Therefore, fracture detection is an essential step in understanding the reservoir's behavior and the stability of the wellbore. The conventional method for detecting fractures is image logging, which captures images of the borehole and fractures. However, the interpretation of these images is a laborious and subjective process that can lead to errors, inaccuracies, and inconsistencies, even when aided by software. Automating this process is essential for expediting operations, minimizing errors, and increasing efficiency.While there have been some attempts to automate fracture detection, this paper takes a novel approach by proposing the use of YOLOv5 as a Deep Learning (DL) tool to detect fractures automatically. YOLOv5 is unique in that it excels at speed, both in training and detection, while maintaining high accuracy in fracture detection. We observed that YOLOv5 can detect fractures in near real-time with a high mean average precision (mAP) of 98.2, requiring significantly less training than other DL algorithms. Furthermore, our approach overcomes the shortcomings of other fracture detection methods.The proposed method has many potential benefits, including reducing manual interpretation errors, decreasing the time required for fracture detection, and improving fracture detection accuracy. Our approach can be utilized in various reservoir engineering applications, including hydraulic fracturing design, wellbore stability analysis, and reservoir simulation. By using this technique, the efficiency and accuracy of hydrocarbon exploration and production can be significantly improved.
- Asia (0.69)
- Europe (0.46)
- South America > Brazil (0.28)
- North America > United States (0.28)
- Geology > Geological Subdiscipline > Economic Geology > Petroleum Geology (0.53)
- Geology > Rock Type > Sedimentary Rock (0.46)
- Geology > Geological Subdiscipline > Geomechanics (0.46)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Europe > Norway > North Sea > Central North Sea > Central Graben > PL 018 > Block 2/4 > Greater Ekofisk Field > Ekofisk Field > Tor Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > Central Graben > PL 018 > Block 2/4 > Greater Ekofisk Field > Ekofisk Field > Ekofisk Formation (0.99)
- Asia > China > Xinjiang Uyghur Autonomous Region > Tarim Basin (0.99)
Experimental Investigation of Paint Roughness on the Resistance of a Flat Plate
Kiosidou, Evangelia D. (National Technical University of Athens, Athens) | Liarokapis, Dimitrios E. (National Technical University of Athens, Athens) | Tzabiras, Georgios D. (National Technical University of Athens, Athens) | Pantelis, Dimitrios I. (National Technical University of Athens, Athens)
In this work, an experimental investigation of the hydrodynamic resistance of a flat plate painted with newly developed marine antifouling paints of polyurethane (PU) and silicone (Si) formulations was performed. In total, six different paint systems of Si, PU, and acrylic formulations were applied, both experimental and commercial. The total resistance of each painted condition of the plate was measured through towing tank tests for the range of 0.75โ2.5m/sec, with a step of 0.25m/sec. The Si and PU formulations exhibited similar hydrodynamic behavior, fluctuating around the smooth condition, whereas the acrylic system exhibited the highest resistance increase of all. The roughness function calculation was based on Ra and the correlation with the Colebrook roughness function was generally limited for most systems. Extrapolation to ship scale revealed that no significant drag differences are expected in the as-painted condition among the different paint system types.
- Europe (1.00)
- South America > Brazil (0.28)
- North America > United States (0.28)
Eric Didier National Laboratory for Civil Engineering, Hydraulics and Environment Department Lisbon, Portugal Paulo R. F. Teixeira Federal University of Rio Grande, Engineering School Rio Grande, Rio Grande do Sul, Brazil This study aims to validate a numerical model based on Reynolds-averaged Navier-Stokes (RANS) equations to simulate the wave-interaction between regular incident waves and the overtopping-type wave energy converter. Results of the overtopping device with two reservoirs in small scale are compared with experiments. The methodology, which includes the use of a hybrid k-shear stress transport turbulence/laminar model, achieves good results, especially considering the difficulties of numerical models to reproduce overtopping because of the complexity of involved phenomena. Water wave energy has great potential to contribute significantly with this type of energy source. However, technical difficulties, such as high capital and maintenance costs, low efficiency, and structural risks as a result of storms, still restrict its use to some prototypes. Many approaches have been developed to overcome these challenges.
- North America > United States (0.46)
- Europe > Portugal > Lisbon > Lisbon (0.34)
- South America > Brazil > Rio Grande do Sul (0.24)
Halliburton announced it will work with Libra Consortium, led by Petrobras, to develop a digital twin for the Mero pre-salt field system in Brazil. The Libra digital twin aims to help the consortium reduce capital expenditures, accelerate production times, and improve crude oil recovery rate using new insights obtained in real time. Digital twins are a virtual representation of a physical asset that replicates its behavior and characteristics. They allow operators to run "what if" scenarios to improve decision-making and maximize operational predictability for optimal field development. Halliburton and Libra Consortium plan to develop an integrated and dynamic digital twin of the production system, including the reservoir, wells, and subsea network.
- South America > Brazil (0.85)
- North America > United States > Louisiana (0.64)
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > South America Government > Brazil Government (0.33)
The increasing use of sparse acquisitions in seismic data acquisition offers advantages in cost and time savings. However, it results in irregularly sampled seismic data, adversely impacting the quality of the final images. In this paper, we propose the ResFFT-CAE network, a convolutional neural network with residual blocks based on the Fourier transform. Incorporating residual blocks allows the network to extract both high- and low-frequency features from the seismic data. The high-frequency features capture detailed information, while the low-frequency features integrate the overall data structure, facilitating superior recovery of irregularly sampled seismic data in the trace and shot domains. We evaluated the performance of the ResFFT-CAE network on both synthetic and field data. On synthetic data, we compared the ResFFT-CAE network with the compressive sensing (CS) method utilizing the curvelet transform. For field data, we conducted comparisons with other neural networks, including the convolutional autoencoder (CAE) and U-Net. The results demonstrated that the ResFFT-CAE network consistently outperformed other approaches in all scenarios. It produced images of superior quality, characterized by lower residuals and reduced distortions. Furthermore, when evaluating model generalization, tests using models trained on synthetic data also exhibited promising results. In conclusion, the ResFFT-CAE network shows great promise as a highly efficient tool for the regularizing irregularly sampled seismic data. Its excellent performance suggests potential applications in the preconditioning of seismic data analysis and processing flows.
- North America > United States (0.28)
- South America > Brazil (0.28)