3D In-situ Stress Characterization Using Seismic Inversion and Downhole Measurements

S. Esmaeilpour, I. Ispas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The exploitation of hydrocarbon reservoirs requires innovative skills to allow better characterization of potential pay zones. Determining the reservoir's Geomechanical properties such as in-situ stresses and rock strengths is essential for effective reservoir management. It is now realized that they are critical for a variety of applications, ranging from borehole stability to well stimulation and reservoir management issues such as optimal placement of water injectors and oil producers. The reservoir pore pressure is also a significant parameter that can affect the drilling operations and well design processes. Under pressured or over pressured formations can lead to severe problems like loss of circulation, blowout while drilling, and borehole instability. This study aims to optimize drilling decisions and well planning by quantifying and predicting of in-situ stresses prior to drilling using innovative approaches involving seismic inversion and conventional downhole measurements. Direct measurement of in-situ stresses and rock mechanical properties in the subsurface is usually not viable due to the high cost of testing or a lack of available data, particularly in old wells. Despite the fact that they may be measured, they are localized over some limited and small area. For computing these parameters and their variations “elastic inversion” of surface seismic data has been performed, which is a geophysical process used to recover the constituent rock properties of the earth and is a critical component for the development of conventional and unconventional reservoirs. The vertical and lateral heterogeneity of rock properties are critical factors that impact production. In this way, seismic surveys will continue to be a backbone of subsurface prediction of rock properties and identifies their distribution in the rock. In order to do this, an inversion strategy based on Multi Attribute Analysis was applied to predict the spatial variations of the parameters for inter-well regions. In this method, acoustic impedance (AI) models are computed from pre-stack seismic amplitude data by seismic inversion in the time domain with measured log density and velocity as constraints. The obtained results reveal that the proposed strategy leads to the accurate prediction of geomechanical properties. This study presents a methodology and workflow to investigate the natural variation in the geomechanical properties of the main reservoirs in the Wellington Oil Field in the south-central Kansas, as well as their stress state and rock mechanical properties using a narrow-azimuth seismic volume and integrating it with wireline logs, core data, and drilling mud reports. The integration of a variety of datasets, through a number of processes, have shown that understanding geomechanical properties, enhancing resolution, and being aware of drivers to stimulation may all aid in the optimization of completions in the Wellington oil field. The methodologies developed in this study can be successfully applied to other areas in south central Kansas with the same burial history and similar geological settings, as well as to any other basin in the world with similar chert, clastic and carbonate reservoirs characterized by downward porosity reduction, as demonstrated in this study. This study reveals the potential for considerable improvements in performance, efficiency, and profitability.

Original languageEnglish
Title of host publication57th US Rock Mechanics/Geomechanics Symposium
PublisherAmerican Rock Mechanics Association (ARMA)
ISBN (Electronic)9780979497582
StatePublished - 2023
Event57th US Rock Mechanics/Geomechanics Symposium - Atlanta, United States
Duration: Jun 25 2023Jun 28 2023

Publication series

Name57th US Rock Mechanics/Geomechanics Symposium


Conference57th US Rock Mechanics/Geomechanics Symposium
Country/TerritoryUnited States


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