Halliburton Energy Services, Inc.

Ingrain, Inc.

Jonas Toelke

Naum Derzhi

Yaoming Mu

Giuseppe De Prisco

Radompon Sungkorn

Abraham S Grader

Xiaobo Nie

Rafael March Castaneda Neto

Christopher Michael Jones

Santiago Gabriel Drexler

Gabriela Alexandra Davalos

Carl Sisk

Bin Dai

Mehdi Alipour Kallehbasti

Joel D Walls

Hamed Chok

Avrami Grader

Michael Suhrer

Bryan Guzman

Gustavo Carpio

Anthony Herman Van Zulekom

Anyela Morcote

Jacob Michael Proctor

Venkata Ajay Gundepalli

Sneha Bhakta

Yangqiu Hu

Milena Ferreira De Siqueira Lima

Andre De Almeida Maximo

Michael Foster

Abrahm S Grader

A method includes imaging, at an imaging resolution, a core of a subsurface formation to create a core image and iteratively performing the following operations until a defined feature of a rock of the subsurface formation exceeds a viewable image feature threshold: extracting a number of subsamples from the core for a first iteration and from each of the number of subsamples previously extracted for a subsequent iteration; increasing the imaging resolution; and imaging each subsample. The method includes performing the following operations for the subsamples last extracted: determining at least one formation property characteristic; determining a guiding rock property for each voxel of the core image and the number of subsample images; and determining a subsample that is a shortest distance to the voxel based on the number of guiding rock properties; and mapping, for each voxel, the at least one formation property characteristic that is the shortest distance.

Upscaling of formation petrophysical characteristics to a whole core scale

The disclosure provides an approach, or workflow, that extrapolates a segmentation carried out on a formation image into the labelling of fractures. The workflow can be applied to 2D and 3D images, which can be generated by different imaging technologies. Advantageously, one or more steps of the workflow can be performed automatically. An example of the workflow includes: (1) distinguishing fractures identified in a formation image from a background of the formation image by applying an entropy filter, wherein the formation image has elements that are defined as either fracture elements or non-fracture elements and entropy values for the elements are generated by the applying of the entropy filter, and (2) identifying the fracture elements that correspond to the fractures by solving a diffusion equation, wherein the entropy values are used as a diffusivity field for solving the diffusing equation and the fracture elements are used as a source.

Entropy-diffusion method for fracture identification and labelling in images

A method comprises receiving a measurement of a pressure in a subsurface formation at a number of depths in a wellbore formed in the subsurface formation across a sampling depth range of the subsurface formation to generate a number of pressure-depth measurement pairs and partitioning the sampling depth range into a number of fluid depth ranges. The method comprises performing a fitting operation over each of the number of fluid depth ranges to determine a fluid gradient for the type of the reservoir fluid for each of the number of fluid depth ranges. The method comprises generating a solution set of one or more solutions based on the fluid gradient of the reservoir fluid for each of the number of fluid depth ranges determined from performing the fitting operation, wherein each solution defines a partitioning of the sampling depth range and the fluid gradient of each fluid depth range.

Determination of location and type of reservoir fluids based on downhole pressure gradient identification

A system and method to partition pores and throats in 2D or 3D scanned tomographic representations. To achieve partitioning, the methods employ a series of techniques that include the Maximum Inscribed Ball technique, Connected Component Labelling technique, and the 3D Binary Morphology technique.

Partitioning of pores and throats in 2D and 3D digital tomographic representations

The disclosed embodiments include methods to perform an in-situ determination of a formation property of a downhole formation, methods to operate a tool to perform an in-situ determination of formation properties of a downhole formation, and in-situ formation property measurement tools. In one embodiment, a method to perform an in-situ determination of a formation property includes deploying a tool into a borehole that is drilled through a formation. The method also includes isolating a source zone from an injection zone. While the source zone is isolated from the injection zone, the method further includes withdrawing a fluid that partially fills the source zone; flowing the fluid into the injection zone; injecting the fluid into a first portion of the formation that is along the injection zone; and determining at least one formation property of the first portion based on an injection of the fluid into the first portion.

Methods to perform an in-situ determination of a formation property of a downhole formation and in-situ formation property measurement tools

A method is provided. Cells of a digital model of a formation are classified corresponding with one or more classes based on minerals and/or pore sizes. Wettability of the formation in the digital model is calibrated based on imbibition and/or drainage curves from physical experimentation for a rock sample and the one or more classes of the cells of the digital model.

System and method to calibrate digital rock wettability

Overlapping pores in a multiscale model of heterogeneous core formation contributes errors during flow simulations. A scale-coupled multiscale modeling that corrects for contributions of overlapping pores may be used to determine capillary pressure and relative permeability of the heterogenous core formation more accurately. The effects of overlapping pores may be removed by converting pores that have a certain radius or are filled with certain fluids into solid regions. The effects of overlapping pores may also be removed by running flow simulations on a modified model and correcting various fluid properties of the core formation with the results.

Scale-coupled multiscale model simulation

Systems and methods for determining properties of subterranean formations surrounding a wellbore are provided. An example method can include receiving an image of a formation sample; partitioning the image into a plurality of patches; detecting, via a semantic extraction processor, textures captured in the plurality of patches; associating the textures to a location of the image of the formation sample; reducing a dimension of representation of the textures to obtain one or more vectors, the one or more vectors being based on the textures; and providing a plurality of curves based on the one or more vectors.

Method and system to analyze geologic formation properties

A graphical representation of an image of a subterranean formation along with log properties of the formation provided in a single graphical representation. Logged formation property values are coded into graphic representations of images of the formation in order to provide a graphical representation which allows the user to visually perceive the formation images and the logged formation properties simultaneously. A method may include receiving an image of a formation, the image including image values based on the formation, and also receiving a log property of the formation, the log property including log property values based on the formation. The log property values of the formation are correlated to corresponding locations in the image. A transfer function with the image values and the correlated log property values as inputs is determined. Based on the transfer function, a joint graphical representation of the image and the log property is rendered.

Property based image modulation for formation visualization

A method may comprise obtaining a formation sample, scanning the formation sample to form a data packet, loading the data packet on an information handling machine, performing a digital porous plate experiment with the data packet, and determining geometry of a pore throat in the formation sample. A system may comprise a computer tomographic machine configured to scan a formation sample and create a data packet from the scan and an information handling system. The information handling system may be configured to configured to perform a digital porous plate experiment with the data packet and determine geometry of a pore throat in the formation sample.

Measuring size and shape of pore throat using digital porous plate experiments

Methods and systems for characterizing a wellbore depth interval from rock fragments, including a method that includes converting measurements of a bulk rock fragment sample and of individual rock fragment samples to a concentration percent, computing a normalization deviation for each of the individual rock fragment samples relative to the bulk rock fragment sample (said normalization deviation being derived from the concentration percent of the bulk and individual rock fragment samples) and ranking the individual rock fragment samples based on a corresponding normalization deviation. The method further includes selecting one or more individual rock fragment samples based on a corresponding ranking, characterizing the properties of the wellbore depth interval from which the bulk and individual rock fragment samples originated using measured properties of at least some of the selected individual rock fragment samples and presenting to a user the characterized wellbore depth interval.

Characterizing a wellbore depth interval from rock fragments

The pore structure of rocks and other materials can be determined through microscopy and subjected to digital simulation to determine the properties of fluid flows through the material. To determine a porosity-permeability over an extended range even when working from a small model, some disclosed method embodiments obtain a three-dimensional pore/matrix model of a sample; measure a distribution of porosity-related parameter variation as a function of subvolume size; measure a connectivity-related parameter as a function of subvolume size; derive a reachable porosity range as a function of subvolume size based at least in part on the distribution of porosity-related parameter variation and the connectivity-related parameter; select a subvolume size offering a maximum reachable porosity range; find permeability values associated with the maximum reachable porosity range; and display said permeability values as a function of porosity.

Digital rock analysis systems and methods that reliably predict a porosity-permeability trend

Methods and systems for conditioning expanded porosity, including a method that includes creating a disconnected pore structure by reducing the pore sizes of a rock sample's scanned image, identifying expanded pores within the rock sample and generating an expanded pore image from the expanded pores. The method further includes combining the expanded pore image with the scanned image to create an expansion mask, generating a grain conditioning volume based on at least one unexpanded region of the rock sample, combining the grain conditioning volume with the expansion mask to generate a fill volume image, combining the fill volume image with the scanned image to create an unexpanded volume image, and generating and presenting to a user a formation log using a model generated based upon the unexpanded volume image.

Conditioning of expanded porosity

An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes iteratively analyzing property measurements collected throughout the digital images using different subsample sizes to identify a property distribution convergence as a function of subsample size. The method also includes selecting a smallest subsample size associated with the property distribution convergence as a representative elementary area or volume for the rock sample.

Representative elementary volume determination via clustering-based statistics

An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes selecting a subsample within the digital images. The method also includes deriving a trend or petrophysical property for the subsample. The method also includes applying the trend or petrophysical property to a larger-scale portion of the digital images.

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Houston, TX, United States of America

Jonas Toelke