TGS has generated a sequence stratigraphic interpretation and play fairway analysis project for the Northeast Newfoundland Shelf utilizing new seismic survey data and available well data. They mapped 21 sequences and delineated reservoir distribution over time. Deliverables include structure maps, horizons, leads, faults, and depositional environment maps. The benefits are a reduced exploration cycle time and risk through understanding basin development and delineating source, seal, and reservoir distributions. Clients must license 50% of the underlying seismic data.
DSD-INT 2017 WFlow - MODFLOW and Reservoirs - Van VerseveldDeltares
Presentation by Willem van Verseveld (Deltares) at the Symposium on catchment hydrology and WFlow, during Delft Software Days - Edition 2017. Tuesday, 24 October 2017, Delft.
Introduction to the petroleum system of Niger Delta Province. Geological aspects, small statistical data analysis to evaluate the general reservoir properties, oil chemical features.
CRISTIANO ASCOLANI, PHILIPP MESTERS, JEAN-MARC SÖLDNER.
Ruhr-Universität Bochum, Petroleum Geology I, Summer Semester 2014.
Reservoir analysis based on:
1) AMIGUN, John Olurotimi, and Oluwaseyi Ayokunle ODOLE. "Petrophysical Properties Evaluation for Reservoir Characterisation of SEYI Oil Field (Niger-Delta)." International Journal of Innovation and Applied Studies 3.3 (2013): 765-773.
2) Chiaghanam, O. I., et al. "Reservoir Characterisation Of Konga Field, Onshore Niger Delta, Southern Nigeria." International Journal of Science & Emerging Technologies 3.1 (2012).
3)Aigbedion, I., and S. E. Iyayi. "Formation Evaluation of Oshioka Field Using Geophysical Well Logs." Middle-East Journal of Scientific Research 2.4 (2007): 107-110.
4) Adewoye, O., et al. "Petrophysical and structural analysis of maiti field, Niger Delta, using well logs and 3-D seismic data." Petroleum & Coal 55.4 (2013): 302-310.
5) Ogbe, Ovie Benjamin, Opatola, Olatunji Abraham, Idjerhe Wilson and Ocheli Azuka. "Reservoir Quality Evaluation of Sand Bodies of K-Field, Onshore Niger Delta, Using Wireline Logs". International Journal for Science and Emerging Technologies with Latest Trends” 13.1 (2013): 46-64.
DSD-INT 2016 Effects of Extraction and Open Pit Mining on Rode Beek Saeffele...Deltares
Presentation by Eric Castenmiller (Province of Limburg) at the iMOD International User Day, during Delft Software Days 2016. Tuesday 1 November 2016, Delft.
DSD-INT 2016 Regional groundwater flow systems in the Kenya Rift Valley - Mur...Deltares
Presentation by Patrick Murunga Wakhungu (University of Twente) at the iMOD International User Day, during Delft Software Days 2016. Tuesday 1 November 2016, Delft.
DSD-INT 2017 WFlow - MODFLOW and Reservoirs - Van VerseveldDeltares
Presentation by Willem van Verseveld (Deltares) at the Symposium on catchment hydrology and WFlow, during Delft Software Days - Edition 2017. Tuesday, 24 October 2017, Delft.
Introduction to the petroleum system of Niger Delta Province. Geological aspects, small statistical data analysis to evaluate the general reservoir properties, oil chemical features.
CRISTIANO ASCOLANI, PHILIPP MESTERS, JEAN-MARC SÖLDNER.
Ruhr-Universität Bochum, Petroleum Geology I, Summer Semester 2014.
Reservoir analysis based on:
1) AMIGUN, John Olurotimi, and Oluwaseyi Ayokunle ODOLE. "Petrophysical Properties Evaluation for Reservoir Characterisation of SEYI Oil Field (Niger-Delta)." International Journal of Innovation and Applied Studies 3.3 (2013): 765-773.
2) Chiaghanam, O. I., et al. "Reservoir Characterisation Of Konga Field, Onshore Niger Delta, Southern Nigeria." International Journal of Science & Emerging Technologies 3.1 (2012).
3)Aigbedion, I., and S. E. Iyayi. "Formation Evaluation of Oshioka Field Using Geophysical Well Logs." Middle-East Journal of Scientific Research 2.4 (2007): 107-110.
4) Adewoye, O., et al. "Petrophysical and structural analysis of maiti field, Niger Delta, using well logs and 3-D seismic data." Petroleum & Coal 55.4 (2013): 302-310.
5) Ogbe, Ovie Benjamin, Opatola, Olatunji Abraham, Idjerhe Wilson and Ocheli Azuka. "Reservoir Quality Evaluation of Sand Bodies of K-Field, Onshore Niger Delta, Using Wireline Logs". International Journal for Science and Emerging Technologies with Latest Trends” 13.1 (2013): 46-64.
DSD-INT 2016 Effects of Extraction and Open Pit Mining on Rode Beek Saeffele...Deltares
Presentation by Eric Castenmiller (Province of Limburg) at the iMOD International User Day, during Delft Software Days 2016. Tuesday 1 November 2016, Delft.
DSD-INT 2016 Regional groundwater flow systems in the Kenya Rift Valley - Mur...Deltares
Presentation by Patrick Murunga Wakhungu (University of Twente) at the iMOD International User Day, during Delft Software Days 2016. Tuesday 1 November 2016, Delft.
Delineation of Hydrocarbon Bearing Reservoirs from Surface Seismic and Well L...IOSR Journals
Hydrocarbon reservoir has been delineated and their boundaries mapped using direct indicators from 3-D seismic and well log data from an oil field in Nembe creek, Niger Delta region. Well log signatures were employed to identify hydrocarbon bearing sands. Well to seismic correlation revealed that these reservoirs tied with direct hydrocarbon indicators on the seismic section. The results of the interpreted well logs revealed that the hydrocarbon interval in the area occurs between 6450ft to 6533ft for well A, 6449ft to 6537ft for well B and 6629ft to 6704ft for well C; which were delineated using the resistivity, water saturation and gamma ray logs. Cross plot analysis was carried out to validate the sensitivity of the rock attributes to reservoir saturation condition. Analysis of the extracted seismic attribute slices revealed HD5000 as hydrocarbon bearing reservoir.
Editorial - May 2014 - Special Issue jointly coordinated by Mercator Ocean and Coriolis
focusing on Ocean Observations
Greetings all,
Once a year and for the fi fth year in a raw, the Mercator Ocean Forecasting Center in Toulouse and the Coriolis Infrastructure in Brest publish a
common newsletter. Some papers are dedicated to observations only, when others display collaborations between the 2 aspects: Observations and
Modelling/Data assimilation.
The fi rst paper by Cabanes et al. introducing this issue is presenting a new methodology aiming at correcting Argo fl oat salinity measurements in
delayed time when Argo fl oats conductivity sensors are subject to drift and offset due to bio-fouling or other technical problems.
Then, Cravatte et al. are using the Argo arrays in order to compile Argo fl oats’ drifts and show that they are a very valuable tool allowing determining
the absolute velocity. They apply this to study zonal jets at 1000 meters depth in the Tropics.
In the next paper, Maes and O’Kane provide with some results indicating the impact of a sustained ocean observing Argo network on the ability to
resolve the seasonal cycle of salinity stratifi cation by contrasting periods pre- and post-Argo. They take into account the respective thermal and saline
dependencies in the Brunt-Väisälä frequency (N2) in order to isolate the specifi c role of the salinity stratifi cation in the layers above the main pycno-
cline.
Picheral et al. are telling us about the Tara Oceans voyage that took place on the schooner “Tara” from 2009 to 2013 and visited all oceans. The ship
was adapted for modern oceanography. Scientifi c instruments were mounted on a dedicated CTD frame and installed on an underway fl ow-through
system. Data were sent daily to Coriolis. Post cruise calibrations were performed leading to a high quality dataset.
Then, Roquet et al. demonstrate the importance of the contribution of hydrographic and biogeochemical data collected by Antarctic marine mammals,
and in particular elephant seals, equipped with a new generation of oceanographic tags, for the environmental monitoring of the Southern Ocean.
The last paper of the present issue is displaying the collaboration between the Ocean Observations and Ocean Modelling communities: Turpin et
al. perform several Observing System Experiments in order to assess the impact of Argo observations on the Mercator Océan global analysis and
forecasting system at ¼ degree resolution.
We wish you a pleasant reading,
Laurence Crosnier and Sylvie Pouliquen, Editors.
#50
Newsletter
QUARTERLY
The Tara Oceans voyage took place on the schooner “Tara” from 2009 to 2013 and visited all oceans to collect samples and data in order to study the relationships between ecosystem biodiversity and function and the physical-chemical oceanographic environ-
ment (water mass, transport) (cf Picheral et al. this issue).
Credits: Francois Aurat/Tara Expéditions; Marc Picheral/LOV
Effects of shale volume distribution on the elastic properties of reserviors ...DR. RICHMOND IDEOZU
Shale volume (Vsh) estimation has been carried out on three selected reservoirs (Nan.1, Nan.2, and Nan.4) distributed across four wells (01, 03, 06, and 12) in Nantin Field, using petrophysical analysis and reservoir modeling techniques with a view to understanding the reservoir elastic properties. Materials utilized for this research work include: Well Log data (Gamma Ray Log, Resistivity Log, Sonic Log, Density Log, Neutron porosity log), and a 3-D Seismic volume were used for the study. Sand and shale were the prevalent lithologies in Nantin Field. Nan. 1 reservoir was thickest in Nantin well 12 (29.7ft), Nantin 2 reservoir was thickest in Nantin Well 12 (30.9ft) while Nantin 4 reservoir was thickest in Well 3 (72ft). Correlation well panel across the Field showed that Nantin 4 reservoir, was thicker than Nan 1 and Nan 2 Reservoir respectively. Normal and synthetic Faults were also mapped, the trapping system in the field includes anticlines in association with fault closures. The thicknesses and lateral extents of these reservoirs were delineated into three zones (1, 2, and 3) which were modeled appropriately. Petrophysical and some elasticity parameters such as Poisson ratio (PR), Acoustic Impedance (AI), and Reflectivity Coefficient (RC) were evaluated for the wells. The results from elasticity evaluation showed a high Poisson Ratio of 0.40 in Nantin 2 reservoir of Well 12 based on high shale volume distribution of 0.70 indicating high stress level and possible boundary to hydraulic fracture. The lowest Poisson Ratio was evaluated in Nantin reservoir of Well 1 with lowest shale volume of 0.18 which indicates weak zones and may not constrain a fracturing job. Results from Acoustic impedance showed a high AI value of 7994.3 in Nan 2 Reservoir compared to Nan.1 which has the least AI value of 7447.3 because of low shale volume. A higher Reflectivity Coefficient of 0.01 was recorded in Nan.2 reservoir indicating bright spot while a lower RC of -0.00023 was recorded in Nan.4 Reservoir indicating dim spot. Hydrocarbon volume estimate of the three reservoirs showed 163mmstb in Nan.1 reservoir, 169mmstb, in Nantin 2 reservoir and 115mmstb in Nan. 4 Reservoir. The reservoirs encountered were faulted and laterally extensive. Nantin 2 reservoir was more prolific with a STOIIP of 169 mmstb compared to Nan. 1 with a STOIP of 163 mmstb and Nantin.4 with a STOIP of 115 mmstb, because of its good petrophysical values, facies quality and low shale volume distributions.
Reconnaissance for Hydrographic Survey ProjectNzar Braim
Reconnaissance for Hydrographic Survey Project
The system is able to withstand the harsh environment of the nearshore and acquire beach profile information across the surf zone. This paper describes the system and results of a comparison in Myrtle Beach, S.C., between surveys collected over a 3- day period by the personal watercraft system and by a similar system mounted aboard a traditional coastal survey vessel.
The bathymetric measurements for the personal watercraft-mounted echosounder surveying system display mean repetitive differences of 6 cm.
This workshop is an introductory course in Hydrographic surveying.
It is designed for surveyors, engineers, survey technicians, dredge operators, and hydrographers.
The course focuses on theoretical principles of hydrographic surveying, project description, operation, and map production.
Objectives:
Develop a replicable integrated model (methodology) for evaluating the extent and development potential of renewable (non-renewable) groundwater resources in arid lands, with the Eastern Desert of Egypt as a pilot site.
The model will be replicable for similar arid areas; North of Sudan, Tibesty, Yemen, and Saudi Arabia.
Building national capacities.
Basin intelligence for informative and strategic decision making and analysis.
With TGS Analytics, you gain deep basin intelligence for informative and strategic decision making along the project value chain. Our basin intelligence solution provides analytical partnerships to close any research gaps so you can make better informed decisions.
We differentiate our solution by bridging the gap between subsurface geologic data and interpretation with strategic analysis of production capabilities. Staying connected to the data allows for fast and transparent insights from a top-down view to each individual well.
Our tool integrates into your workflow allowing you to gain quick knowledge or perform individual analytics for your AOI.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.