Increase Exposed Bitumen Reserves by Optimizing Wellbore Placement in Oil Sands with Extra-Deep Azimuthal Resistivity LWD Service

2018 ◽  
Author(s):  
Aleksandr Vetsak ◽  
Bryce Jablonski
Keyword(s):  
Oil Sands ◽  
Resistivity Lwd ◽  
Azimuthal Resistivity

Integration of Seismic and 3D Ultra-Deep Azimuthal Resistivity LWD

2021 ◽  
Author(s):  
M. Alexander ◽  
D. Salim ◽  
M. Etchebes ◽  
T. Akindipe
Keyword(s):  
Resistivity Lwd ◽  
Azimuthal Resistivity

A New Deep Azimuthal Resistivity LWD for Optimal Well Placement and Reservoir Exploitation; Successful Validation with Saudi Aramco

2008 ◽  
Author(s):  
Richard Palmer ◽  
Andre Silva ◽  
A.A. Hajari ◽  
Michael Bittar ◽  
Ramez Shokeir ◽  
...  
Keyword(s):  
Well Placement ◽  
Optimal Well Placement ◽  
Saudi Aramco ◽  
Resistivity Lwd ◽  
Azimuthal Resistivity

Reversible jump MCMC inversion of the ultra-deep azimuthal resistivity LWD tools using Cauchy proposal function

2019 ◽  
Author(s):  
Jian Wang* ◽  
Hao Chen ◽  
Lei Zhang ◽  
Jiaqi Xiao ◽  
Xiuming Wang
Keyword(s):  
Reversible Jump ◽  
Reversible Jump Mcmc ◽  
Resistivity Lwd ◽  
Azimuthal Resistivity

THE FINAL PIECE OF THE PUZZLE: 3-D INVERSION OF ULTRA-DEEP AZIMUTHAL RESISTIVITY LWD DATA

2019 ◽  
Author(s):  
Nigel Clegg ◽  
Timothy Parker ◽  
Bronwyn Djefel ◽  
Luc Monteilhet ◽  
David Marchant
Keyword(s):  
Resistivity Lwd ◽  
Azimuthal Resistivity

An Improved Complex Image Theory for Fast Resistivity Modeling and Its Application to Geosteering

SPE Journal ◽  
2016 ◽  
Vol 21 (04) ◽  
pp. 1450-1457 ◽  
Author(s):  
Jiefu Chen ◽  
Jing Wang ◽  
Yao Yu
Keyword(s):  
Gamma Ray ◽  
Observation Point ◽  
Image Theory ◽  
Additional Information ◽  
Complex Image ◽  
Parallel Layer ◽  
Resistivity Anisotropy ◽  
Resistivity Lwd ◽  
Dip Angle ◽  
Azimuthal Resistivity

Summary azimuthal resistivity logging-while-drilling (LWD) tools with tilted antennas (Bittar 2002; Li et al. 2005) are widely used in geosteering because of their azimuthal sensitivity and the relatively large depth of investigation compared with other LWD tools such as nuclear, acoustic, or gamma ray measurements. Compared with conventional resistivity tools, azimuthal-resistivity LWD measurements can provide additional information including distance-to-boundary, relative dip angle, and resistivity anisotropy (Li et al. 2014). Because of the computing efficiency requirement, modeling and inversion of azimuthal-resistivity LWD measurements are usually based on a 1D parallel-layer model in practice (Zhong et al. 2008). Clearly, this 1D model assumption is not applicable to some realistic situations such as when the tool is navigating in unparallel-layer formation, or approaching a fault. The 3D full-wave simulations such as finite-difference or finite-element methods can handle the complex cases, but they are generally too slow for real jobs, not to mention the inversion that is based on iterative calls of forward modeling. An approximation method called complex image theory was proposed for geophysical prospecting (Wait 1969; Bannister 1986), and recently was introduced to well logging (Dong and Wang 2011; Wang and Liu 2014). This theory approximates electromagnetic-wave reflection by an interface between local and adjacent beds as signal radiated from a virtual source with a complex distance from the observation point. The complex image theory can be several orders of magnitude more efficient than 3D simulations. However, it also has several limitations: This method only works in resistive beds with conductive shoulders, and the measurement cannot be too close to bed interfaces. Those shortcomings greatly limit this method to more extensive applications. An improved complex image theory is proposed here to tackle the aforementioned difficulties. This improved theory can handle a very short distance from the tool to a bed interface as well as the scenarios in which the source is in a conductive bed instead of a resistive one. One can implement robust inversion schemes on the basis of this method. The effectiveness and efficiency of this method are verified by several numerical examples as well as laboratory tests and field jobs.

Impacts of Canada's oil-sands operations 'exaggerated'

Nature ◽  
2010 ◽  
Author(s):  
Hannah Hoag
Keyword(s):  
Oil Sands

Megaloads and Mobilization

2017 ◽  
Vol 1 (1) ◽  
pp. 1-7
Author(s):  
Corrie Grosse
Keyword(s):  
Oil Sands ◽  
Fossil Fuel ◽  
Cost Effective ◽  
Nez Perce ◽  
Grassroots Organizations ◽  
Canadian Province ◽  
Creation Story ◽  
Oil Companies ◽  
Heavy Crude ◽  
Ways Of Life

From 2011 to 2014 fossil fuel corporations trucked tar sands processing machinery along rural Idaho highways. The machinery was bound for the world's largest deposits of tar or oil sands, a heavy crude oil substance called bitumen, located in the western Canadian province of Alberta. These loads of machinery, what became known as megaloads, encountered much resistance. Throughout Idaho and the surrounding region, a network organized opposition. Neighbors, grassroots organizations, nonprofits, and the Nez Perce and other tribes all collaborated. They held information sessions, protested, waged legal battles, monitored the loads, and blockaded highways. What oil companies hoped would be a cost-effective solution for transporting their megaloads became a David versus Goliath, Coyote versus the Monster—to reference the Nez Perce creation story—struggle to protect rural and indigenous ways of life and sovereignty, and the planet.

Improvements to production planning in oil sands mining through analysis and simulation of truck cycle times

CIM Journal ◽  
2019 ◽  
Vol 10 (1) ◽  
Author(s):  
E. Goris Cervantes ◽  
S. P. Upadhyay ◽  
H. Askari-Nasab
Keyword(s):  
Production Planning ◽  
Oil Sands ◽  
Cycle Times ◽  
Oil Sands Mining

Unusually physical and chemical characteristics of oil sands from Qaidam basin, NW China

2005 ◽  
Vol 39 (2) ◽  
pp. 121-130 ◽  
Author(s):  
Zhi-Nong Gao ◽  
Li-Bo Zeng ◽  
Fei Niu
Keyword(s):  
Oil Sands ◽  
Qaidam Basin ◽  
Chemical Characteristics ◽  
Nw China ◽  
Physical And Chemical Characteristics ◽  
Physical And Chemical
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