The in situ stress field of the west tuna area, gippsland basin: implications for natural fracture-enhanced permeability and wellbore stability

2004 ◽  
Vol 2004 (1) ◽  
pp. 1-4
Author(s):  
Emma J. Nelson ◽  
Richard R. Hillis ◽  
Scott D. Mildren ◽  
Jeremy J. Meyer
2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Wei Ju ◽  
Ke Xu ◽  
Jian Shen ◽  
Chao Li ◽  
Guozhang Li ◽  
...  

Knowledge of the present-day in-situ stress distribution is greatly important for better understanding of conventional and unconventional hydrocarbon reservoirs in many aspects, e.g., reservoir management, wellbore stability assessment, etc. In tectonically stable regions, the present-day in-situ stress field in terms of stress distribution is largely controlled by lithological changes, which can be predicted through a numerical simulation method incorporating specific mechanical properties of the subsurface reservoir. In this study, a workflow was presented to predict the present-day in-situ stress field based on the finite element method (FEM). Sequentially, it consists of: i) building a three-dimensional (3D) geometric framework, ii) creating a 3D petrophysical parameter field, iii) integrating the geometric framework with petrophysical parameters, iv) setting up a 3D heterogeneous geomechanical model, and finally, v) calculating the present-day in-situ stress distribution and calibrating the prediction with measured stress data, e.g., results from the extended leak-off tests (XLOTs). The approach was successfully applied to the Block W in Ordos Basin of central China. The results indicated that the workflow and models presented in this study could be used as an effective tool to provide insights into stress perturbations in subsurface reservoirs and geological references for subsequent analysis.


1998 ◽  
Vol 38 (1) ◽  
pp. 466 ◽  
Author(s):  
C.A. Barton ◽  
D.A. Castillo ◽  
D. Moos ◽  
P. Peska ◽  
M.D. Zoback

To minimise wellbore failures in unstable environments, knowledge of the complete stress tensor is crucial to designing optimally-stable borehole trajectories, selecting suitable mud weights, and determining appropriate casing points. Understanding how the in situ stress field interacts with the drilling and production of a well enables one to design for maximum stability and to facilitate intersecting the greatest population of hydraulically-conductive fractures for efficient production. Knowledge of the in situ stress field is also important to reduce uncertainties in sand production prediction to allow more aggressive completion designs and production schedules.A new interactive software system, Stress and Failure of Inclined Boreholes (SFIB) (Peska and Zoback, 1995a) is used to demonstrate how observations of drilling-induced compressive and tensile wellbore failures from acoustic and electrical images in vertical and inclined boreholes can be integrated with routinely-collected drilling data (leak-off and drill stem tests) to construct a well-constrained stress tensor. These techniques can also exploit wellbore image data to constrain in situ rock strength in vertical and inclined wells. This paper illustrates how to apply this knowledge to limit wellbore instability, design optimally stable wellbores, develop constraints that help mitigate problems associated with sand production, and optimise productivity of fractured reservoirs.In addition to mapping drilling-induced wellbore features, image data can also be used to determine the distribution, orientation, and apparent aperture of natural fractures and fault systems. With knowledge of the orientations and magnitudes of the in situ stresses it is possible to identify the subset of fractures that are likely to be hydraulically conductive.Examples of recent applications in the North Sea, Gulf of Mexico, California, and Puerto Rico illustrating how this integrated approach can be used in a variety of tectonic settings.


2003 ◽  
Vol 2003 (2) ◽  
pp. 1-5 ◽  
Author(s):  
Scott D. Reynolds ◽  
Richard R. Hillis ◽  
Evelina Paraschivoiu

2019 ◽  
Vol 102 ◽  
pp. 61-73 ◽  
Author(s):  
Wei Ju ◽  
Bo Jiang ◽  
Yong Qin ◽  
Caifang Wu ◽  
Geoff Wang ◽  
...  

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