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Offshore Technology Conference, OTC 2025

作者： Oliveira, I.M.N. Lima Junior, E.T. Vieira, T.M.A. Silva, A.C.A. Ramos, D.L. Aranha, P.E. Laboratory of Scientific Computing and Visualization Federal University of Alagoas Alagoas Maceió Brazil Petrobras Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781959025610

Ensuring well integrity in offshore oil and gas operations is critical for safety, environmental protection, and production efficiency. Early detection of anomalies, such as spurious Downhole Safety Valve (DHSV) closures and rapid productivity loss events, mitigates risks and economic losses. However, challenges like anomaly rarity, data imbalances, and operational complexities, including valve changes, hinder the effectiveness of traditional detection methods. This study evaluates TranAD, a deep transformer network based model, to detect anomalies in multivariate time-series data using the 3W dataset, a realistic public offshore well repository. TranAD leverages attention-based architecture to capture intricate temporal dependencies, making it well-suited for imbalanced datasets. When trained exclusively on non-anomalous data, it employs adversarial training and predictive-reconstructive learning for robust detection. The methodology incorporates preprocessing to address missing values, frozen sensors, and imbalances, with feature selection optimizing model performance. Two training approaches are examined: well-specific models and a generalized model spanning multiple wells. The findings highlight the potential for real time anomaly detection systems to ensure well integrity in offshore operations. By employing advanced methodologies, operators can achieve automated, continuous monitoring of offshore wells, reducing risks and enhancing operational reliability. © 2025 Offshore Technology Conference.

关键词： Offshore oil well production

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Predicting Remaining Useful Life of Well Tubulars: A Reliability-Based Approach

Predicting Remaining Useful Life of Well Tubulars: A Reliabi...

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Offshore Technology Conference, OTC 2025

作者： Ribeiro Almeida, L.P. Gouveia, L.P. Silva, T.B. Lima Junior, E.T. Lima Santos, J.P. Colombo, D. Melosantanna, V. Abrego, A.L.S. Laboratory of Scientific Computing and Visualization Federal University of Alagoas Alagoas Maceió Brazil Petrobras Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781959025610

This work estimates the Remaining Useful Life (RUL) of tubulars throughout the lifecycle of oil and gas wells. The RUL evaluation is supported by probabilistic analysis that addresses uncertainties associated with geometrical and material properties, regarding the failure modes defined in API/TR 5C3 code. The proposed framework is applied to tubular design and monitoring analyses, considering degradation effects due to corrosion and extreme scenarios, such as Worst Case Discharge (WCD). The proposed solution comprises a mechanical model to provide the safety factors and the probability of occurrence associated to failure modes involving internal/external pressure and axial force, according to API/TR 5C3 models. By applying structural reliability concepts and the Monte Carlo simulation, the uncertainties are taken into account and the load scenarios can be revisited over time, evaluating the probability of occurrence of unexpected events. This framework allows estimating integrity indicators for RUL analysis of tubulars, such as the failure rate and the mean time to failure (MTTF). The case study presented aims to assess RUL for a 20-year lifetime offshore production well, leveraging statistical information about tubular geometry, material and degradation effects. The simulation covers two operational phases: drilling for the first 2 months and production for the following 238 months. The probability of failure grows over time as corrosion progressively reduces the wall thickness of tubulars, weakening their structural integrity. As a result, the survival function declines, while the failure rate rises with time. This deterioration in strength leads to a greater likelihood of failure throughout the well's lifecycle, potentially affecting its remaining useful life (RUL). Such a trend directly impacts the mean time to failure (MTTF) of tubulars, influencing the longevity of oil and gas wells. The proposed methodology assesses the integrity of well tubulars in both serv

关键词： Failure rate

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Improving the Free Span Analysis of Subsea Rigid Pipelines for Life Extension Through Integration and Automation and Efficiency

Improving the Free Span Analysis of Subsea Rigid Pipelines f...

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Offshore Technology Conference, OTC 2025

作者： Martins, R.R. Cardoso, C.O. Matt, C.G.C. Nunes, L.A.N. Góes, R.C.O. Rosa, A.S. Silveira, E.S.S. Petrobras Rio de Janeiro Rio de Janeiro Brazil Laboratory of Scientific Computing and Visualization Federal University of Alagoas Alagoas Maceió Brazil

ISBN: (纸本)9781959025610

Free span analysis is essential for the integrity management and life extension of subsea assets at Petrobras. It ensures operational safety and efficiency, minimizes environmental impacts, and supports the company's long-term sustainability goals. This paper presents IntegriSpan, a specialized digital web application developed for the integrated structural and VIV analysis of free spans in subsea rigid pipelines. The application is designed to improve integrity management, simultaneously reducing costs and saving time. To address the challenge of assessing the integrity of thousands of kilometers of subsea pipelines, Petrobras, in collaboration with national science and technology institutes, developed a specialized digital web application aligned with Industry 4.0, focused on integrated structural and VIV analysis of free spans in subsea rigid pipelines. The current version of the application facilitates data querying and sharing with commercial software, environmental databases, and external inspection data from multibeam ROVs within the company's collaborative web portal, SUBWEB. This automation and integration streamline the analysis process, reduce simulation time, enhance data security and integrity, simplify results visualization, and standardize report generation. IntegriSpan has been successfully implemented at Petrobras, optimizing the subsea pipeline integrity analysis process, reducing the time of analysis cycles and the amount of pipeline interventions, and enabling more realistic simulations. An application example presented in this article involves fatigue life assessment in free spans of a large-diameter gas export pipeline, where the initial recommendation for mitigating potential VIV issues was reduced from 120 to 6, avoiding the need for around 400 days of support vessel activity and significantly reducing the time required for an analysis of this magnitude. Currently, the application is also being considered for the assessment of free spans on s

关键词： Offshore technology

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A Numerical Model for Friction Prediction in Directional Wells

A Numerical Model for Friction Prediction in Directional Wel...

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Offshore Technology Conference, OTC 2025

作者： Rodrigues, O. Fernandes, C. Araujo, J. Lira, W. Santos, J. Carmo, I. Souza, C. Laboratory of Scientific Computing and Visualization Alagoas Maceió Brazil Federal University of Alagoas Alagoas Maceió Brazil Petrobras Rio de Janeiro Brazil

ISBN: (纸本)9781959025610

Improving the accuracy of oil and gas well design is critical to reducing the risk of structural failure over the well's life cycle, particularly for production and injection column components. The friction effect resists tubing movement and results in a redistribution of axial loads. This work proposes a static numerical model that accounts for load history to accurately predict friction and its effect on axial forces in tubing strings in directional wells. Tubular axial forces with friction are load-history dependent. The literature provides a static numerical model with this effect, but with some limitations. To overcome this, sinusoidal and helical buckling equations for directional wells are incorporated into the model. Friction due to buoyant weight and the capstan effect are also integrated using soft-string equations. The proposed model is implemented computationally, and each added effect is verified using literature examples. A friction sensitivity analysis is performed in a directional well case study, governing equations are presented, and the method is detailed to allow replication of results. The vertical well model is implemented, and when a numerical study is replicated, the axial forces agree with reference results. In a parametric friction study, the displacements generated by the implementation are verified, revealing discrepancies between elastic displacements and available analytical solution. Further differences arise in a deviated tubing case when buckling equations for directional wells are incorporated into the model. In this context, the numerical results are compared with analytical solutions developed in this work and a commercial software, showing notable agreement. The incorporation of buoyancy weight and the capstan effect proves successful, showing good correlation with effective force calculations in build-tangent well. In the case study, results indicate that friction reduces axial forces compared to frictionless analyses but increa

关键词： Offshore oil well production

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Numerical Modeling of Conductor Casing Installation: Leveraging the Material Point Method

Numerical Modeling of Conductor Casing Installation: Leverag...

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Offshore Technology Conference, OTC 2025

作者： Barboza, B.R. Melo, J.M.F. Tenorio, M.S.C. Lima Junior, E.T. Santos, J.P.L. Cutrim, F.S. Dias, R. Laboratory of Scientific Computing and Visualization Federal University of Alagoas Alagoas Maceió Brazil Petrobras Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781959025610

Objective: The tophole sections are critical for well stability, providing support to the well structure, preventing shallow fluid influx, and protecting against formation collapse. This paper aims to simulate the conductor casing installation by driving in offshore clayey soils, by developing a numerical model using the Material Point Method (MPM). The model is validated against operational data to ensure its applicability in predicting the behavior of soil-structure interaction under severe offshore conditions. Methods: A clayey soil from the Campos basin, eastern Brazil, is characterized by in-situ CPTu data and modeled using the Mohr-Coulomb criteria. A 2D axisymmetric model with a non-structured triangular mesh and a two-phase single-point explicit formulation is employed to simulate the soil in undrained condition. The casing tubular, described as a rigid body, interacts with soil through an adhesive contact algorithm. A moving mesh procedure ensures the integrity of the mesh near the casing’s external surface. The simulation includes both the self-weight penetration phase and subsequent impact driving. Observations: The case study presented refers to a 58.8-m. section of conductor casing, with 36-in. outer diameter and linear weight of 3470 lb/ft. It reached approximately 10 meters in 5 seconds during the selfweight phase, with further penetration during impact driving. The soil is described by a 60 m thick domain consisting of four clayey layers. The depth behavior over time was analyzed by monitoring the conductor tip during soil penetration. The numerical model demonstrated a strong correlation with actual operational data, accurately predicting displacement and stress distributions around the conductor. Soil resistance increased with depth, stabilizing the penetration rate. The Material Point Method proves effective in modeling large deformation problems involving contact mechanics, providing valuable insights into the soil-conductor interaction. Novel: T

关键词： Offshore technology

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A System to Detect Oilwell Anomalies Using Deep Learning and Decision Diagram Dual Approach

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SPE Journal 2023年第3期29卷 1540-1553页

作者： Aranha, P.E. Lopes, L.G.O. Sobrinho, E.S. Paranhos Oliveira, I.M.N. de Araújo, J.P.N. Santos, B.B. Lima, E.T. da Silva, T.B. Vieira, T.M.A. Lira, W.W.M. Policarpo, N.A. Sampaio, M.A. Well Construction Department Petrobras Brazil Department of Mining and Petroleum Engineering Universidade de São Paulo Brazil Laboratory of Scientific Computing and Visualization Federal University of Alagoas Brazil

Detecting unexpected events is a field of interest in oil and gas companies to improve operational safety and reduce costs associated with nonproductive time (NPT) and failure repair. This work presents a system for real-time monitoring of unwanted events using the production sensor data from oil wells. It uses a combination of long short-term memory (LSTM) autoencoder and a rule-based analytic approach to perform the detection of anomalies from sensor data. Initial studies are conducted to determine the behavior and correlations of pressure and temperature values for the most common combinations of well valve states. The proposed methodology uses pressure and temperature sensor data, from which a decision diagram (DD) classifies the well status, and this response is applied to the training of neural networks devoted to anomaly detection. Data sets related to several operations in wells located at different oil fields are used to train and validate the dual approach presented. The combination of the two techniques enables the deep neural network to evolve constantly through the normal data collected by the analytical method. The developed system exhibits high accuracy, with true positive detection rates exceeding 90% in the early stages of anomalies identified in both simulated and actual well production scenarios. It was implemented in more than 20 floating production, storage, and offloading (FPSO) vessels, monitoring more than 250 production/injection subsea wells, and can be applied both in real-time operation and in testing scenarios. Copyright © 2023 Society of Petroleum Engineers.

关键词： Anomaly detection

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Application of Data-Driven Techniques in 3D Soil Characterization for Top-Hole Design

Application of Data-Driven Techniques in 3D Soil Characteriz...

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Offshore Technology Conference, OTC 2025

作者： Filho, C. A. F. Várady Tenório, J.K.F. Junior, E. T. Lima Santos, J.P.L. Dias, R. Cutrim, F.S. Laboratory of Scientific Computing and Visualization Federal University of Alagoas Maceió Alagoas Brazil Petrobras Rio de Janeiro Riode Janeiro Brazil

ISBN: (纸本)9781959025610

Present work investigated the application of 3D Sparse Bayesian Learning (SBL) and Gaussian ProcessRegression (GPR) for data-driven offshore site characterization focusing specifically on estimating critical soil parameters for top-hole design in oil and gas wells, such as undrained shear resistance and specific unit weight. These parameters are essential for designing conductor and surface casing sections in drilling operations and ensuring the structural integrity of wellhead systems and casing strings. This study used datasets of piezocone penetration tests (CPTu) conducted in the Campos basin in Brazil and supplied by the partner operator. Input data is used to generate 2D and 3D modeling of the spatial trend of undrained shear resistance and specific weight using the test data. The trend is assessed using Sparse Bayesian Learning and Gaussian Process Regression, which are probabilistic-based methods capable of dealing with data uncertainties. These methods, which represent the latest advancements in the field according to current literature, provide accurate and cost-effective estimates of soil properties. Analysis procedure consisted of assessing the plausibility of the models regarding the CPTu data used as input. The comparative analysis revealed that both SBL and GPR improved soil characterization compared to traditional methods. Both methods show significant capabilities to model spatial trends, and accuracy and performance issues are addressed for 3D modeling with different soil types. Depending on the initial data, both methods can present interesting results with similar computational cost but, in general, SBL takes longer time to be *** evidence is used as metric to compare both models as it is shown that is equivalent to a cross-validation procedure using the log posterior probability function as scoring function. The probabilistic nature of both techniques supports robust evaluation of uncertainties associated with spatial heterogeneit

关键词： Gaussian distribution

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Improved analysis of GW190412 with a precessing numerical relativity surrogate waveform model

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Physical Review D 2021年第10期103卷 104027-104027页

作者： Tousif Islam Scott E. Field Carl-Johan Haster Rory Smith Department of Physics and Center for Scientific Computing and Visualization Research University of Massachusetts Dartmouth Massachusetts 02747 USA Department of Mathematics and Center for Scientific Computing and Visualization Research University of Massachusetts Dartmouth Massachusetts 02747 USA LIGO Laboratory Massachusetts Institute of Technology 185 Albany St Cambridge Massachusetts 02139 USA Department of Physics and Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave Cambridge Massachusetts 02139 USA School of Physics and Astronomy Monash University Vic 3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery Clayton VIC 3800 Australia

The recent observation of GW190412, the first high-mass ratio binary black hole merger, by the LIGO-Virgo Collaboration (LVC) provides a unique opportunity to probe the impact of subdominant harmonics and precession effects encoded in a gravitational wave signal. We present refined estimates of source parameters for GW190412 using nrsur7dq4, a recently developed numerical relativity waveform surrogate model that includes all ℓ≤4 spin-weighted spherical harmonic modes as well as the full physical effects of precession. We compare our results with two different variants of phenomenological precessing binary black hole waveform models, imrphenompv3hm and imrphenomxphm, as well as to the LVC results. Our results are broadly in agreement with imrphenomxphm results and the reported LVC analysis compiled with the seobnrv4phm waveform model, but in tension with imrphenompv3hm. Using the nrsur7dq4 model, we provide a tighter constraint on the mass ratio (0.26−0.06+0.08) as compared to the LVC estimate of 0.28−0.07+0.13 (both reported as median values with 90% credible intervals). We also constrain the binary to be more face on, and find a broader posterior for the spin precession parameter. We further find that even though ℓ=4 harmonic modes have negligible signal-to-noise ratio, omission of these modes will influence the estimated posterior distribution of several source parameters including chirp mass, effective inspiral spin, luminosity distance, and inclination. We also find that commonly used model approximations, such as neglecting the asymmetric modes (which are generically excited during precession), have negligible impact on parameter recovery for moderate signal-to-noise ratio events similar to GW190412.

关键词： Gravitational waves

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Corrigendum to “Thermoelastic homogenization of periodic composites using an eigenstrain-based micromechanical model” [Applied Mathematical Modelling 85 (2020) 1-18

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Applied Mathematical Modelling 2021年 89卷 1999-1999页

作者： Eduardo Nobre Lages Severino Pereira Cavalcanti Marques Laboratory of Scientific Computing and Visualization Center of Technology Federal University of Alagoas Maceió 57072-900 Alagoas Brazil

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High-Precision Ringdown Surrogate Model for Non-Precessing Binary Black Holes

arXiv

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arXiv 2024年

作者： Zertuche, Lorena Magaña Stein, Leo C. Mitman, Keefe Field, Scott E. Varma, Vijay Boyle, Michael Deppe, Nils Kidder, Lawrence E. Moxon, Jordan Pfeiffer, Harald P. Scheel, Mark A. Nelli, Kyle C. Throwe, William Vu, Nils L. Department of Physics and Astronomy University of Mississippi UniversityMS38677 United States Theoretical Astrophysics 350-17 California Institute of Technology PasadenaCA91125 United States Department of Mathematics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Center for Computational Research East Hall University of Rhode Island KingstonRI02881 United States Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY14853 United States Laboratory for Elementary Particle Physics Cornell University IthacaNY14853 United States Department of Physics Cornell University IthacaNY14853 United States Am Mühlenberg 1 Potsdam14476 Germany

Highly precise and robust waveform models are required as improvements in detector sensitivity enable us to test general relativity with more precision than ever before. In this work, we introduce a spin-aligned surrogate ringdown model. This ringdown surrogate, NRSur3dq8_RD, is built with numerical waveforms produced using Cauchy-characteristic evolution. In addition, these waveforms are in the superrest frame of the remnant black hole allowing us to do a correct analysis of the ringdown spectrum. The novel prediction of our surrogate model is complex-valued quasinormal mode (QNM) amplitudes, with median relative errors of 10−2 − 10−3 over the parameter space. Like previous remnant surrogates, we also predict the remnant black hole’s mass and spin. The QNM mode amplitude errors translate into median errors on ringdown waveforms of ∼ 10−4. The high accuracy and QNM mode content provided by our surrogate will enable high-precision ringdown analyses such as tests of general relativity. Our ringdown model is publicly available through the python package surfinBH. Copyright © 2024, The Authors. All rights reserved.

关键词： Relativity

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