Schlumberger Technology Corporation

Services Petroliers Schlumberger

Schlumberger Holdings Limited

Sushil Shetty

Tarek M Habashy

Dzevat Omeragic

John C Rasmus

Smaine Zeroug

Jeffrey Miles

Austin Boyd

Lin Liang

Vanessa Simoes

Bikash Kumar Sinha

Koji Ito

Christopher Edward Morriss

Shahzad Asif

Hui Xie

Vittorio Picco

Fabio Cesar Canesin

Qiwei Zhan

A method for determining properties of a laminated formation traversed by a well or wellbore employs measured sonic data, resistivity data, and density data for an interval-of-interest within the well or wellbore. A formation model that describe properties of the laminated formation at the interval-of-interest is derived from the measured sonic data, resistivity data, and density data for the interval-of-interest. The formation model represents the laminated formation at the interval-of-interest as first and second zones of different first and second rock types. The formation model is used to derive simulated sonic data, resistivity data, and density data for the interval-of-interest. The measured sonic data, resistivity data, and density data for the interval-of-interest and the simulated sonic data, resistivity data, and density data for the interval-of-interest are used to refine the formation model and determine properties of the formation at the interval-of-interest. The properties of the formation may be a radial profile for porosity, a radial profile for water saturation, a radial profile for gas saturation, radial profile of oil saturation, and radial profiles for pore shapes for the first and second zones (or rock types).

Method for determining properties of a thinly laminated formation by inversion of multisensor wellbore logging data

Systems and methods are disclosed for well logging using radiation detection and/or emission of gamma rays. A method according to the disclosure includes collecting data from the subterranean formation using a nuclear density tool, wherein the nuclear density tool is configured to collect data to form an azimuthal image. The method further includes characterizing a section of the subterranean formation comprising data and images acquired in a high angle wellbore section, a horizontal wellbore section, or a combination thereof. The method additionally includes performing a parallel inversion using apparent densities and volumetric photoelectric factor images to build a formation model, wherein the parallel inversion comprises a high angle workflow that models high angle wellbore sections and a horizontal workflow that models horizontal wellbore sections.

Inversion-based workflow for consistent interpretation of nuclear density images in horizontal wells

Methods and apparatus for characterizing a subterranean formation traversed by a wellbore including collecting data from the formation using a tool wherein the tool collects data to form an azimuthal image, characterizing a section of the formation comprising data and images acquired in a high angle wellbore section or horizontal wellbore section using a parametric model, and performing an inversion using apparent densities and volumetric photoelectric factor images to build a formation model wherein the inversion is tailored for high angle wellbore sections and/or horizontal wellbore sections.

Inversion-based workflow for processing nuclear density images in high-angle and horizontal wells

A method for automatic interpretation of bulls-eye and sinusoidal features observed in LWD images is disclosed. In some embodiments, the method includes an automatic workflow for extracting smooth contours from images that demarcate boundaries of structural features, followed by projection of the contours to three-dimensional (3D) point clouds in the well coordinate system for structural interpretation. The method may characterize both sinusoidal features and bulls-eye features, taking into account variations of formation dip/azimuth, or well inclination/azimuth, on the topology of a structural feature. The disclosed method may be sufficiently fast for use in real-time analysis and interpretation, or to provide constraints for physics-based data inversion processing.

Automatic method for three-dimensional structural interpretation of borehole images acquired in high-angle and horizontal wells

A computer-implemented method is provided for determining properties of a formation traversed by a well or wellbore. A formation model describing formation properties at an interval-of-interest within the well or wellbore is derived from measured sonic data, resistivity data, and density data for the interval-of-interest. The formation model is used as input to a plurality of petrophysical transforms and corresponding tool response simulators that derive simulated sonic data, resistivity data, and density data for the interval-of-interest. The measured sonic data, resistivity data, and density data for the interval-of-interest and the simulated sonic data, resistivity data, and density data for the interval-of-interest are used by an inversion process to refine the formation model and determine properties of the formation at the interval-of-interest. In embodiments, properties of the formation may be radial profiles for porosity, water saturation, gas or oil saturation, or pore aspect ratio.

Method for determining formation properties by inversion of multisensor wellbore logging data

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Arlington, MA, United States of America

Sushil Shetty