Schlumberger Technology Corporation

Other

Schlumberger Technology Center

Services Petroliers Schlumberger

Lalitha Venkataramanan

Denise E Freed

Tarek M Habashy

Martin D Hurlimann

Yi-Qiao Song

Oliver Clinton Mullins

Vasileios-Marios Gkortsas

Fred K Gruber

Kenneth Edward Stephenson

Harish Baban Datir

Bhavani Raghuraman

Ricardo Vasques

Charles Flaum

Ridvan Akkurt

Richard E Lewis

Nicholas N Bennett

Martin D Hürlimann

Jeffrey Paulsen

Lin Liang

Erik Rylander

Lukasz Zielinski

Albina Mutina

Mark Flaum

Badarinadh Vissapragada

Timothy Andrew John Hopper

Robert Callan

Jean-Marc Donadille

Li Chen

Terizhandur S Ramakrishnan

Kai Hsu

Sandip Bose

Robert L Kleinberg

Henri-Pierre Valero

Pu Wang

Nicholas J Heaton

Chengli Dong

Go Fujisawa

Ravinath Kausik Kadayam Viswanathan

Michael O'Keefe

Austin Boyd

Paul Ryan Craddock

Vikas Jain

David Furse Allen

Philip M Singer

Jose Navarro

Vladislav Achourov

Christian Straley

Andrew Carnegie

Ashok Belani

Chang-Yu Hou

Peter Tilke

Gal Shulkind

Ulrich Scheven

Marcus Hofheins Donaldson

Ashish Datey

Stacy Lynn Reeder Blanco

Melanie Jensen

Augustin Prado

Nicholas A Bennett

Yi Zeng

Olivier J Terneaud

Noyan Evirgen

Khaled Hadj-Sassi

Prakhar Srivastava

Methods and systems are provided characterizing a formation traversed by a wellbore, wherein the formation includes at least a flushed zone and an uninvaded zone, which involve obtaining well log data based on plurality of different well log measurements of the formation at multiple depths in the wellbore. The well log data is used by a computational model that solves for a set of petrophysical parameters that characterize a portion of the formation corresponding to the multiple depths in the wellbore, wherein the set of petrophysical parameters include a cementation exponent, a saturation exponent, and a flushed zone water resistivity. The solved-for set of petrophysical parameters can be used to determine a value of water saturation of the uninvaded zone for the portion of the formation corresponding to the multiple depths in the wellbore.

Estimation of fluid saturation of a formation from integration of multiple well logs

Methods and systems are provided for conducting formation analysis. Data from borehole logging tools is used to conduct a petrophysical analysis of the formation in order to determine (quantify) total porosity and formation matrix permittivity for an interval of the formation. Noninvaded zone water saturation and flushed zone water saturation for the interval of the formation is determined using a saturation model of the interval. The noninvaded zone water saturation is compared to the flushed zone water saturation, and the results of the comparison are used to determine that the interval of the formation contains movable hydrocarbon, immobile hydrocarbon or movable formation water.

Formation analysis incorporating identification of immovable and viscous hydrocarbons

Processes and systems for determining asphaltene equilibrium between two or more downhole geographic locations are provided. In some embodiments, the process can include measuring one or more fluid properties of a plurality of fluid samples at varying downhole depths to generate a one or more downhole fluid analysis measurement data points; selecting an asphaltene diameter distribution based on prior knowledge; utilizing the asphaltene diameter distribution to fit a first set of one or more equation of state curves to the one or more downhole fluid analysis measurement data points to define a first model of fitted equation of state curves and to determine one or more posterior distributions of asphaltene diameters; and determining if the varying downhole depths are in an asphaltene equilibrium by determining whether the one or more posterior distributions of asphaltene diameters is consistent with that of asphaltenes in equilibrium.

Processes and systems for determining if downhole fluids are in equilibrium or non-equilibrium

Methods and systems are provided to learn and apply a mapping function from data representing concentrations of atomic elements in a geological formation (or other data corresponding thereto) to mineral component concentrations in the geological formation (and/or from mineral component concentrations to reconstructed elemental concentrations in the geological formation). The mapping function can be derived from a trained neural network (such as an autoencoder). The output of the mapping function can be used to determine estimates of one or more formation properties, such as formation matrix density, formation porosity, matrix Sigma, formation saturation, other formation property, or combinations thereof.

Estimating mineralogy and reconstructing elements of reservoir rock from spectroscopy data

A neural network system includes a first neural network configured to predict a mean value output and epistemic uncertainty of the output given input data, and a second neural network configured to predict total uncertainty of the output of the first neural network. The second neural network is trained to predict total uncertainty of the output of the first neural network given the input data through a training process involving minimizing a cost function that involves differences between a predicted mean value of a geophysical property of a geological formation from the first neural network and a ground-truth value of the geophysical property of the geological formation. The neural network system further includes one or more processors configured to run a software module that determines aleatoric uncertainty of the output of the first neural network based on the epistemic uncertainty of the output and the total uncertainty of the output.

Dual neural network architecture for determining epistemic and aleatoric uncertainties

Methods are provided for determining values for a set of parameters for multiple locations in a formation by inversion of formation data obtained from a plurality of different logging tools. The inversion of the formation data is constrained by certain formation data that characterizes each particular location in the formation as obtained from at least one of the plurality of different logging tools. In one embodiment, the set of parameters for each particular location in the formation includes an apparent cementation factor mand a formation water saturation S, which can be derived by inverting dielectric data that characterizes the particular location in the formation as obtained from a dielectric logging tool. The methods can also be adapted to characterize a porous medium such as reservoir rock, particular with regard to laboratory analysis of porous media samples.

Methods and systems of determining parameters characterizing porous media from data gathered by a plurality of different tools

Methods and systems are provided for characterizing fluids in a subterranean formation traversed by a borehole, where NMR data is measured by a downhole NMR tool that is conveyed in the borehole that traverses the formation. The NMR data is processed to derive T1-T2 maps at different depths of the formation. The T1-T2 maps at different depths of the formation can be processed to generate a cluster map of different fluids that are present in the formation, wherein the cluster map is a two-dimensional array of grid points in the T1-T2 domain with each grid point being assigned or classified to a specific fluid. The cluster map of different fluids that are present in the formation can be used to characterize properties of the formation, such as fluid volumes for the different fluids at one or a number of depths.

Methods for determining fluid volumes from NMR T1-T2 log data

A method, computer program product, and computing system for receiving downhole logging data for a porous media. A pore size distribution index may be estimated based upon, at least in part, nuclear magnetic resonance data (NMR) from the downhole logging data of the porous media. A relative permeability and capillary pressure curve may be generated with a feasible region of solutions based upon, at least in part, the pore size distribution index.

System and method for reducing a feasible region of solutions in a relative permeability and capillary pressure curve

A methods are provided for investigating a sample containing hydrocarbons by subjecting the sample to a nuclear magnetic resonance (NMR) sequence using NMR equipment, using the NMR equipment to detect signals from the sample in response to the NMR sequence, analyzing the signals to extract a distribution of relaxation times (or diffusions), and computing a value for a parameter of the sample as a function of at least one of the relaxation times (or diffusions), wherein the computing utilizes a correction factor that modifies the value for the parameter as a function of relaxation time for at least short relaxation times (or as a function of diffusion for at least large diffusion coefficients).

Methods of investigating formation samples using NMR data

Apparatus and method of characterizing a subterranean formation including observing a formation using nuclear magnetic resonance measurements, calculating an answer product by computing an integral transform on the indications in measurement-domain, and using answer products to estimate a property of the formation. Apparatus and a method for characterizing a subterranean formation including collecting NMR data of a formation, calculating an answer product comprising the data, wherein the calculating comprises a formula and estimating a property of the formation using the answer product.

Estimation of petrophysical and fluid properties using integral transforms in nuclear magnetic resonance

Methods and related systems are described for estimating fluid or rock properties from NMR measurements. A modified pulse sequence is provided that can directly provide moments of relaxation-time or diffusion distributions. This pulse sequence can be adapted to the desired moment of relaxation-time or diffusion coefficient. The data from this pulse sequence provides direct estimates of fluid properties such as average chain length and viscosity of a hydrocarbon. In comparison to the uniformly-spaced pulse sequence, these pulse sequences are faster and have a lower error bar in computing the fluid properties.

Modified pulse sequence to estimate properties

Systems and methods are described herein for investigating a downhole formation using a nuclear magnetic resonance (NMR) tool. The tool includes multiple detectors spaced along an axis parallel to a length of the wellbore. While the tool is moving through the wellbore, NMR pulse sequences are applied to the formation and resulting NMR signals are detected by the detectors. The data obtained over a period of time by the multiple detectors are inverted together to obtain an indication of a parameter of the formation at multiple locations along the length of the wellbore.

Multiple detector NMR tool system and inversion methods for NMR logging

Methods are provided for determining values of a pore cementation exponent m and/or a saturation exponent n for locations in a formation having similar petrophysical properties. Formation porosity, formation water saturation, and an apparent cementation exponent mare obtained for the locations and their values are utilized to find the exponents. In one embodiment, the apparent cementation exponent and the formation water saturation are obtained from a dielectric logging tool.

Methods of determining cementation exponent and saturation exponent in porous media from dielectric dispersion data

Systems and methods are provided for investigating a downhole formation using a nuclear magnetic resonance (NMR) tool. While the tool is moving through the borehole, the formation is magnetized and resulting signals are obtained. In accordance with the present approach, the acquired signals can be resolved azimuthally and/or laterally and can be reconstructed to obtain an indication of a parameter of the formation at multiple locations along the length of the borehole.

Imaging subterranean formations and features using azimuthal phase encoding

Methods and systems for characterizing a subterranean formation using nuclear magnetic resonance (NMR) measurements are described herein. One method includes locating a downhole logging tool in a wellbore that traverses the subterranean formation, and performing NMR measurements to obtain NMR data for a region of the subterranean formation. The NMR data is processed by employing sparse Bayesian learning (SBL) to determine a multi-dimensional property distribution of the NMR data (e.g., T-T, D-T, and D-T-Tdistributions). The sparse Bayesian learning can utilize Bayesian inference that involves a prior over a vector of basis coefficients governed by a set of hyperparameters, one associated with each basis coefficient, whose most probable values are iteratively estimated from the NMR data. The sparse Bayesian learning can achieve sparsity because posterior distributions of many of such basis coefficients are sharply peaked around zero.

Robust multi-dimensional inversion from wellbore NMR measurements

Growing community of inventors

Lexington, MA, United States of America

Lalitha Venkataramanan