The estimation of continuous downhole permeability is widely performed by nuclear magnetic resonance (NMR) using the classical Seevers-Kenyon and Timur-Coates models. The first approach uses an average of the relaxation times, whereas the latter approach is based on the fractional fluid content computed from a relaxation time distribution cutoff. However, several case studies in the literature reported that these models might fail, especially when applied to complex carbonate rocks in which permeability is often less correlated to porosity, irreducible water saturation, and relaxation times. This study develops and evaluates perm-estimators that use multiple relaxation times, proving that they are a general case of the classical models. The so-called multivariate estimators are calibrated with core permeability using principal component regression, which describes NMR variables in a simple and linear-independent space according to data variance. An important feature of the multivariate approach is the possibility of simultaneously using longitudinal T1 and transverse T2 relaxation times or simply using a specific segment of their distribution. Moreover, the multivariate estimators can also be applied to size-scaled T1,2 distributions for cases in which relaxation times are less sensitive to permeability, such as the carbonate rocks studied in this work. By employing mercury injection capillary pressure (MICP) data for the NMR size scaling, permeability estimates are improved considerably compared to the nonscaled estimates. The superior results achieved with the novel multivariate estimators over the classical models indicate that core and NMR well-logging data should be better explored to improve the accuracy of permeability estimates.

Reliable estimates of porosity can be obtained from different types of geophysical well logs. However, obtaining in situ permeability estimates is still a major challenge in the geosciences. This work aims to evaluate the application of data mining techniques to NMR logs for rock permeability classification, thus far tested only on laboratory data. For this study, we used a petrophysical database from two Brazilian Pre-salt wells located in the Santos Basin, a formation notoriously difficult to characterize, mainly due to its diversity and complexity. Six classification algorithms were evaluated (k-NN, NB, C4.5, RF, SMO, and MLP) according to their ability to estimate the permeability of rocks in four distinct classes (low: <1 mD, intermediate: 1–10 mD, high: 10–100 mD, and excellent: >100 mD). The predictive performance of the algorithms was compared to the behavior of two traditional permeability estimators. With an accuracy of 66%, the Naïve Bayes algorithm, combined with two preprocessing steps – unsupervised discretization and attribute selection – achieved the highest predictive performance. That mark surpassed the accuracy obtained by Kenyon and Timur-Coates estimators by 154% and 106%, respectively, providing evidence for the superiority of the data mining technique to recognize permeability classes based on NMR logs. Classification experiments employing NMR logs in conjunction with conventional logs were also conducted, but this log combination was not able to best the predictive result based solely on the NMR log data.

In this work, we characterized mineralogical, petrographic and petrophysically the Mupe Member from the Purbeck Group lower portion, located in southern England and northern France.These rocks mainly consist of limestones and can be considered as a partial analogue rock of the Brazilian pre-salt carbonate reservoirs.The laboratory tests campaign to characterize there lithologies comprised of X-ray diffraction (XRD) tests and thin sections description, gas effective porosity and absolute permeability, nuclear magnetic resonance (NMR).The results of XRD and thin sections indicated a mineralogy rich in low-magnesium calcite and the presence of different types of pores.The NMR T2 distribution indicated that the plugs are very heterogeneous, having pore size distributions varying from bimodal to polymodal.

ABSTRACT. Characterization of carbonate rocks presents several challenges regarding the acquisition of petrophysical parameters and the understanding of fluid-flow dynamics in their pore system. To face these challenges, techniques such as X-ray microtomography, three-dimensional digital model reconstruction and fluid-flow numerical simulations have been continuously developed and improved. This study analyzes the representative elementary volume (REV) of a region of interest (ROI) of a highly heterogeneous stromatolite sample. Porosity and permeability are estimated for different subvolumes of the sample based on digital petrophysics. All necessary steps for reconstruction and segmentation of the complex pore system of the sample, as well as numerical simulations of fluid flow, are presented and discussed. The workflow is promising for reservoir evaluation because it can be applied to any type of carbonate rock.Keywords: Stromatolite, mCT, segmentation, REV, digital petrophysicsRESUMO. A caracterização de rochas carbonáticas apresenta diversos desafios quanto à determinação de seus parâmetros petrofísicos e o entendimento da dinâmica de escoamento de fluidos em seus sistemas porosos. Técnicas como a microtomografia de raios X, a modelagem digital tridimensional e a simulação numérica do escoamento de fluidos têm sido continuamente desenvolvidas e aprimoradas para superar esses desafios. Este estudo analisa o volume elementar representativo (REV) em uma região de interesse (ROI) de uma amostra de estromatólito altamente heterogênea. A porosidade e a permeabilidade são estimadas em diferentes subvolumes da amostra através da petrofísica digital. São apresentadas e discutidas todas as etapas necessárias para a reconstrução e segmentação do sistema poroso e a simulação numérica do escoamento de fluidos. A metodologia é promissora para avalição de reservatórios visto que o fluxo de trabalho pode ser aplicado a qualquer tipo de rocha carbonática.Palavras-chave: Estromatólitos, mCT, segmentação, REV, petrofísica digital

ABSTRACT. Nuclear magnetic resonance (NMR) is a recognized petrophysical tool in the oil and gas industry to characterize reservoir rocks and fluids. In this study, the pore system of coquinas from a single bed of a quarry in the Morro do Chaves Formation was evaluated. These sedimentary rocks have been considered as a potential analogous to some Brazilian pre-salt reservoir rocks. The objective of this work was to characterize the porous system of coquinas in terms of total porosity and pore size distribution using low-field NMR. Conversion of T2 relaxation times to pore size radii was performed and literature cut-offs were applied for porosity partitioning. Coquinas were classified and ranked according to their percentage of macro, meso and micro porosity. This work verified quantitatively the pore system heterogeneities for the coquina samples and the variation in the layer from which they were extracted. The study provides some clues on lateral porosity and pore size variation in any reservoir for which this unit is an analogue.Keywords: Petrophysics, NMR, Total Porosity, Pore Size Distribution, Porosity Partitioning.RESUMO. Ressonância magnética nuclear (RMN) é uma técnica petrofísica reconhecida na indústria de óleo e gás pela sua capacidade de caracterizar rochas reservatório e seus fluidos saturantes. Neste estudo, foi avaliado o sistema poroso de coquinas pertencentes à uma camada de uma pedreira na Formação Morro do Chaves. Essas rochas sedimentares foram consideradas possíveis análogos de algumas rochas carbonáticas do pré-sal brasileiro. O objetivo do trabalho foi caracterizar o sistema poroso dessas coquinas em termos de porosidade total e distribuição de tamanho de poros utilizando RMN de baixo campo. Realizou-se a conversão dos tempos de relaxação T2 para raios de poro e empregou-se cut-offs da literatura para o particionamento da porosidade. As coquinas foram classificadas e ranqueadas de acordo com a sua porcentagem de macro, meso e micro poros. Verificou-se quantitativamente a heterogeneidade do sistema poroso das coquinas estudadas e a variação da camada sedimentar em que os plugues foram retirados. O estudo fornece informações sobre a variação lateral de porosidade e tamanho de poros para reservatórios que tenham a unidade estudada como análogo.Palavras-chave: Petrofísica, RMN, Porosidade Total, Distribuição do Tamanho de Poros, Particionamento da Porosidade.

The effect of the selection of different nuclear magnetic resonance (NMR) relaxation times for permeability estimation is investigated for a set of fully brine-saturated rocks acquired from Cretaceous carbonate reservoirs in the North Sea and Middle East. Estimators that are obtained from the relaxation times based on the Pythagorean means are compared with estimators that are obtained from the relaxation times based on the concept of a cumulative saturation cutoff. Select portions of the longitudinal (T-1) and transverse (T-2) relaxation-time distributions are systematically evaluated by applying various cut-offs, analogous to the Winland-Pittman approach for mercury injection capillary pressure (MICP) curves. Finally, different approaches to matching the NMR and MICP distributions using different mean-based scaling factors are validated based on the performance of the related size-scaled estimators. The good results that were obtained demonstrate possible alternatives to the commonly adopted logarithmic mean estimator and reinforce the importance of NMR-MICP integration to improving carbonate permeability estimates.

Complex pore structure in carbonate rocks causes the petrophysical characterization and formation evaluation a challenge. Permeability is one of the main evaluation parameters for determining the potential production of a reservoir because it defines the ability of fluids to flow through rocks. It is not possible to directly measure permeability using a wireline tool; one method to obtain it, however, is from Nuclear Magnetic Resonance (NMR) logs using various models such as Timur-Coates, T2LM (Kenyon) and P-connectivity which are adjusted using laboratory core analysis. Interpretation methods were developed to obtain permeability of the formation from NMR readings. These models relate permeability with other petrophysical properties such as porosity that can be directly estimated using well log information. The NMR models include parameters such as c, m, n and T2,cutoff, that must be calibrated with NMR laboratory analyses because they vary for each formation. In some cases, NMR models must be modified to estimate rock permeability more accurately. This paper presents a workflow to modify the NMR models to determine permeability in carbonate rocks. The correlation between conventional laboratory core analysis and NMR permeability from Timur-Coates and Kenyon models is improved using an adjustment factor applicable for each equation. The adjustment factor can be correlated with petrophysical properties of the rocks such as NMR porosity, the irreducible fluid volume (BVI) and the moveable fluid volume (BVM). The results of calculating NMR permeability in carbonate rocks applying the modified equations to laboratory data and NMR log is also presented. Permeability from formation tests is used to correlate with NMR permeability using log data.

The accurate permeability mapping, even with the aid of modern borehole geophysics methods, is still a big challenge on the reservoir management framework. One concern within the petrophysics community is that rock permeability value predicted by well logging should not be considered as absolute, mainly for carbonates, but a relative index for identifying more permeable zones. Therefore, in this paper a permeability classification methodology, based exclusively on H-1 NMR (Nuclear Magnetic Resonance) relaxation data, was evaluated for the first time as an alternative to the prediction of permeability as a continuous variable. To pursue this, a side-by-side comparison of different data mining techniques for the permeability classification task was performed using a petrophysical dataset with 78 rock samples from six different carbonate reservoirs. The effectiveness of six classification algorithms (k-NN, Naive Bayes, C4.5, SMO, Random Forest and Multilayer Perceptron) was evaluated to predict the rock permeability class according to the following ranges: low (<1 mD), fair (1-10 mD), good (10-100 mD) and excellent (>100 mD). Discretization and feature selection strategies were also employed as preprocessing steps in order to improve the classification accuracy. For the studied dataset, the results demonstrated that the Random Forest and SMO strategies delivered the best classification performance among the selected classifiers. The computational experiments also evidenced that our approach led to more accurate predictions when compared with two methods widely adopted by the petroleum industry (Kenyon and Timur-Coates models). (C) 2015 Elsevier Ltd. All rights reserved.

Nuclear magnetic resonance (NMR) transverse relaxation times (T2) were measured for carbonate rocks saturated with brine and crude oil under different saturation conditions. The NMR measurements were intercalated within the stages of standard wettability core analyses, which monitor imbibition and drainage processes after restoring in situ condition. The T2 distributions are interpreted for seven core plugs in each of the following stages: 1) totally brine saturated;2) at irreducible water saturation after drainage;3) restored after ‘ageing’ for sixty days;4) at residual oil saturation after imbibition and;5) at final water saturation after second drainage. Under these complex saturated rock systems, brine and crude relaxation contributions are highly overlapped. However a practical relaxation-time-domain method is proposed and fluid signals are separated. Guided by T2 monophasic results, closely related to rock pore size distribution, biphasic results reveal pore occupancy and wettability of the micro, meso and macro porosity. Finally, this work reinforces the importance of NMR technique to complement conventional wettability core analysis and its potentiality for in situ wettability measurements in borehole geophysics. Introduction

The pore structure of many carbonate formations is known to be very complex and heterogeneous, resulting in poor performance from the most commonly used NMR permeability models. A majority of the complex carbonate wells in Brazil are drilled with OBM, which further complicates calibration of these models. To circumvent these problems, we developed a new approach using core-permeability data and NMR logging measurements to construct a radial-basis-function (RBF)-based permeability-prediction model. To reduce the noise-induced uncertainty in NMR relaxation-time-spectrum data, a PCA method is applied and a small number of principal components are used instead of the full spectrum. To stabilize the prediction result, regularized RBF instead of the RBF interpolation method was used. Furthermore, a regularized forward-selection algorithm,is applied to overcome oversensitivity when training the RBF-based model. Generalized crossvalidation methods and crosswell tests are used to evaluate the performance of the model and verify that good results are obtained.

Examinamos o comportamento do sinal de Ressonância Magnética Nuclear (RMN) adquirido em laboratório.Dados de relaxação magnética transversal (T2) foram analisados tanto no domínio do tempo

PreviousNext No Access13th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 26–29 August 2013Image Analysis and NMR modeling of Sedimentary RocksAuthors: Giovanna da Fraga CarneiroAndre SouzaAustin BoydLawrence SchwartzBernardo Coutinho Camilo dos SantosWillian Andrighetto TrevizanEdmilson Helton RiosVinicius de França MachadoGiovanna da Fraga CarneiroBRCG – Schlumberger;Search for more papers by this author, Andre SouzaBRCG – Schlumberger;Search for more papers by this author, Austin BoydBRCG – Schlumberger;Search for more papers by this author, Lawrence SchwartzSDR – Schlumberger;Search for more papers by this author, Bernardo Coutinho Camilo dos SantosCENPES – PetrobrasSearch for more papers by this author, Willian Andrighetto TrevizanCENPES – PetrobrasSearch for more papers by this author, Edmilson Helton RiosCENPES – PetrobrasSearch for more papers by this author, and Vinicius de França MachadoCENPES – PetrobrasSearch for more papers by this authorhttps://doi.org/10.1190/sbgf2013-193 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract In this paper, the Nuclear Magnetic Resonance response of three sedimentary rocks (one sandstone and two carbonates) is modeled through random walk simulations. With this modeling, we aim to improve micro-porosity content and pore size estimation, by taking into account both surface relaxation and diffusive coupling. Experimental Magnetic Resonance data and microscopic image analysis are used to compare the results. We obtained a good match between simulated and experimental T2 distribution curves. Geometrical parameters used as inputs in the model provide macro- and micro-porosity content as well as pore sizes. Keywords: South America, porosity, reservoir characterization, modeling, imagingPermalink: https://doi.org/10.1190/sbgf2013-193FiguresReferencesRelatedDetails 13th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 26–29 August 2013ISSN (online):2159-6832Copyright: 2013 Pages: 2001 publication data© 2013 Published in electronic format with permission by the Brazilian Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished: 09 Jan 2014 CITATION INFORMATION Giovanna da Fraga Carneiro, Andre Souza, Austin Boyd, Lawrence Schwartz, Bernardo Coutinho Camilo dos Santos, Willian Andrighetto Trevizan, Edmilson Helton Rios, and Vinicius de França Machado, (2013), "Image Analysis and NMR modeling of Sedimentary Rocks," SEG Global Meeting Abstracts : 938-941. https://doi.org/10.1190/sbgf2013-193 Plain-Language Summary KeywordsSouth Americaporosityreservoir characterizationmodelingimagingPDF DownloadLoading ...

Taking rock and saturation heterogeneity into account is of great importance both in well logging and petrophysical core analysis programs. This work presents some results achieved with novel low field laboratorial nuclear magnetic resonance techniques that can spatially resolve transversal relaxation time (T2) and signal amplitudes along core plugs length. The measurement quality is firstly tested with a mixture of bulk fluids (water and oil) and then performed in sandstone and carbonate rocks under fully and also partially (centrifuged) saturated conditions. These one dimensional rock imaging techniques can efficiently inform about sample pore-size distribution heterogeneities and also monitor in situ rock saturation with important centrifuge capillary pressure implications.

O presente trabalho demonstra algumas importantes tecnicas de petrofisica laboratorial atraves de um fluxo de trabalho muito comum na industria de petroleo. Tal fluxo comeca pela correta extracao, selecao e limpeza das amostras; passa pela petrofisica de rotina, cujas propriedades petrofisicas basicas sao mensuradas a gas, tais como densidade de graos, volume de poros, porosidade e permeabilidade; e vai ate a petrofisica especial, onde os ensaios sao realizados com saturacőes de fluidos diversos para medidas de propriedades eletricas, pressőes capilares, permeabilidades relativas, distribuicao de gargantas e tamanho de poros e indices de molhabilidade. Sao discutidos aspectos teoricos e praticos de cada metodo e seus principais protocolos de medida. No contexto da exploracao e caracterizacao de reservatorios, a importância da medida laboratorial tanto para calibracao do dado de campo quanto para geracao de informacőes indisponiveis em campo e enaltecida ao longo do texto.

This study explores the application of the partial least squares regression (PLSR) technique to rock permeability prediction from nuclear magnetic resonance (NMR) relaxation data. A total of 68 Brazilian sandstone cores selected from reservoirs and outcrop analogs were fully saturated and analyzed by NMR. The permeability of the cores ranged from 0.007 to 9,800mD. From their 1H transverse relaxation times (T2) measured at 2MHz, two PLSR models were developed for the relaxation spectra and the raw relaxation curves. Both models led to more uniform and accurate predictions (RMSE=0.47 and 0.50 log mD, respectively) compared with the classical Kenyon model (RMSE=0.78 log mD).