Autor: EPIC Energy

Improving pseudo-optimal Kalman-gain localization using the random shuflle method

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In present days, Iterative ensemble smoothers (IES) are among the main methods to perform ensemble-based history matching in petroleum reservoirs. Generally, some localization technique is applied to the IES to pre- vent ensemble collapse, which is the consequence of an excessive reduction of the posterior ensemble variance. When the standard distance-based localization is applied, the assimilation of non-local parameters is difficult, and besides that, this kind of methodology has also several intrinsic parameters that need to be defined before the assimilation. In contrast, adaptive localization methods aim to overcome the noticed problems of distance-based localization, by using some statistical method to define the localization. This article proposes a novel adaptive localization scheme, on top of two preexisting techniques: pseudo-optimal and correlation-based localizations. The motivation here is to further improve the adaptive localization scheme, by combining the strengths of these two preexisting techniques. The efficacy of the proposed localization scheme is tested in one 2D and one 3D case studies, whereas the latter case study involves a field-scale reservoir model with both local and non-local pa- rameters, which often impose challenges on the conventional localization schemes. In comparison to other evaluated localization schemes, our results indicate that the proposed adaptive localization scheme achieves improved history matching performance.

 

4th EPIC Conference

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Atualização (21/10/2022): diante da grande procura e como o número de vagas era limitado, as inscrições para a 4th EPIC Conference estão encerradas.

O EPIC gostaria de convidar estudantes de pós-graduação, pesquisadores e profissionais da área de engenharia de reservatórios para a 4th. EPIC Conference, evento anual voltado à divulgação dos trabalhos em desenvolvimento no centro. A 4th. EPIC Conference ocorrerá entre os dias 07 e 09 de novembro de 2022* no campus da Universidade Estadual de Campinas (UNICAMP), localizado em Campinas – SP – Brasil.

As atividades da 4th EPIC Conference estarão distribuídas em dois locais:

Para mais informações, consulte o Programa da Conferência, logo abaixo, ou

Baixe o Programa da Conferência (em PDF)

Em caso de dúvidas, contacte-nos em epic@unicamp.br

* O minicurso intitulado “Electric Submersible Pumps (ESPs): Fundamentals, Failure Analysis & Reliability, and Emulsion as a Flow Assurance Issue” terá uma sessão extra no dia 10 de novembro de 2022, às 8:30.

Programa da Conferência

Day 1: General Program
Day 1: Poster Session
Day 2: General Program
Day 2: Poster Session
Day 3: General Program

Minicurso: Ensemble based Decision Making in Reservoir Management and Field Development Planning

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Minicurso

Atualização (21 de junho): instruções para os participantes inscritos foram enviadas para o e-mail fornecido na inscrição. Caso não tenha recebido, verifique sua pasta de spam. Quaisquer dúvidas, contacte-nos em epic@unicamp.br

O EPIC gostaria de convidar estudantes de pós-graduação, pesquisadores e profissionais da área de engenharia de reservatórios para o minicurso intitulado “Ensemble based Decision Making in Reservoir Management and Field Development Planning“, a ser oferecido pelo Prof. Remus Gabriel Hanea, consultor chefe em tecnologia de reservatórios na Equinor, e pelo Prof. Bogdan Sebacher, professor na Academia Técnica Militar de Bucareste, Romênia.

O curso será oferecido em inglês, entre os dias 27 e 29 de junho de 2022, na Faculdade de Engenharia Mecânica (FEM) da Universidade Estadual de Campinas (UNICAMP), em Campinas, Brasil.

O Prof. Remus Gabriel Hanea é consultor chefe em Tecnologia de Reservatórios, Ajuste Assistido ao Histórico e Otimização/Tomada de Decisão no departamento de Excelência em Subsuperfície na Equinor. Sua formação é em Matemática Aplicada, e o Prof. Remus tem 15 anos de experiência em Quantificação de Incerteza, Assimilação e Otimização de Dados e Tomada de Decisão com aplicações em Ciências Atmosféricas, Hidrologia e em vários domínios de Energia (principalmente O&G). Ele também é professor em tempo parcial no Departamento de Engenharia de Petróleo da Universidade de Stavanger (Noruega), atuando no grupo de Engenharia de Geociências de Petróleo. Os principais tópicos de pesquisa do Prof. Remus são: ajuste assistido ao histórico e otimização robusta para gerenciamento de reservatórios, valor da informação, decisão e análise de risco e geoestatística. O Prof. Remus ministra também curso especializado para alunos de Doutorado e Mestrado em Modelagem Inversa, Assimilação e Otimização de Dados com aplicações em Gestão de Reservatórios, além de orientar alunos de Mestrado e Doutorado.

O Prof. Bogdan Sebacher é professor associado junto à Academia Técnica Militar de Bucareste (Romênia).

Programa do Curso

Dia 1

(27 de junho de 2022)

Introduction to Reservoir Management and Data Assimilation

Período da Manhã (9:00 às 12:00)

  • Introduction to Reservoir Management and Field Development Planning – basic notions
  • Introduction to Data Assimilation and Decision Making/Optimization – basic notions
  • Models, Data, Uncertainties
  • Bayes Theorem
  • Kalman Filter

Período da Tarde (14:00 às 17:00)

  • From Ensemble Kalman Filter (EnKF) to Ensemble Smoother Multiple Data Assimilation (ES-MDA) – the journey
  • Pros and Cons and practical implementations (case studies)
  • Ensemble validation and analysis, Quality assurance and the definition of success

Dia 2

(28 de junho de 2022)

Facies modeling and estimation

Período da Manhã (9:00 às 12:00)

  • Pluri-Gaussian approach
  • Adaptive Pluri-Gaussian Simulation (APS)
  • Probability cubes for facies distributions – Seismic and log data information

Período da Tarde (14:00 às 17:00)

  • Multipoint Geostatistics (MPS) approach
  • Parameterization and estimation
  • Machine learning approaches

Dia 3

(29 de junho de 2022)

Decision Making/Optimization under geological uncertainties

Período da Manhã (9:00 às 12:00)

  • Robust/Ensemble Optimization
  • Basic concepts
  • Ensemble and stochastic gradient optimization approaches
  • Practical Implementations
  • Way forward – Structured decision making approach

Disciplina de CCUS (2022)

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O Programa de Pós-graduação em Ciências e Engenharia de Petróleo da UNICAMP e o Energy Production Innovation Center (EPIC) gostariam de comunicar o oferecimento da disciplina PP590 “An Introduction to CCUS: Carbon Capture, Utilization and Storage“, que será aberta também a alunos de pós-graduação externos à UNICAMP. A disciplina terá início em 03/03/2022 e terá duração de 15 semanas, com aulas sempre às quintas-feiras das 9h00 às 12h00.

A disciplina tem como pré-requisitos graduação em ciências exatas ou tecnológicas e habilidades para comunicação em inglês (nível C1 ou superior). Mais informações podem ser obtidas no banner abaixo e as pré-inscrições devem ser feitas em https://forms.gle/N5obKKdjvjojb3yi6.

A matrícula no curso, para alunos regulares e pós-docs, deve ser realizada no período de alteração de matrícula (08 a 11/03). Para os alunos externos que tenham interesse, é necessário realizar a matrícula como aluno especial por meio deste link até o dia 08/03/2022.

Informações sobre o curso de CCUS

 

 

Evidence that wax deposition is a phase transition rather than a molecular diffusion phenomenon

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Over the past five decades, wax deposition has been widely considered a mass transfer-controlled phenomenon. Despite the highly inaccurate predictions, engineers cannot accurately predict the final thickness of the deposit, the hypothesis that wax deposition is a mass transfer phenomenon was not commonly questioned, but this has recently changed. This paper shows evidence that wax deposition is limited by phase transition (heat transfer), by analyzing a vast experimental matrix previously presented in the literature and clearly showing that the thickness decreases as the Reynolds number increases, which cannot be explained by molecular diffusion alone, also by showing that the Reynolds number does not influence the ratio between the deposit’s thermal resistance and the total thermal resistance (dimensionless temperature) for all cold flow experiments, which is further evidence of phase transition. When comparing the limits of the molecular diffusion approach with the experimental data, without any fitting parameter, one observes that not only the experimental data cannot be predicted, but the trend is also incorrect. When using the phase transition model (heat transfer), the accuracy in the thickness prediction is high, which is evidence that what limits the wax deposition is the phase transition. This shows that heat transfer equations can accurately predict wax deposition thickness. Since all wax deposition simulators have the heat transfer calculations, to improve their predictions, one must only implement a single boundary condition.

Critical Review on Wax Deposition in Single-Phase flow

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Wax deposition is a costly problem for the O&G industry, especially for pipelines in cold environments. For at least three decades, the scientific community has overwhelmingly agreed that molecular diffusion is the main mechanism for wax deposition. There are, however, severe problems with models based on molecular diffusion. They rely on untested hypotheses and several empirical correlations; hence, they can hardly predict the experimental data from laboratory. For real fields, the prediction is no better than an educated guess – heuristic solutions. Several research areas in wax deposition need to be better understood, and these are discussed in detail here, with a highlight to the most important concern: the controlling mechanism. Is wax deposition indeed a mass transfer controlled phenomenon? What is the evidence supporting this “general knowledge”? Is it possible that, for some conditions, mass transfer is dominant, and for others, the phase transition mechanism is dominant? Apart from this, we also discuss other issues: the accuracy of empirical correlations for diffusivity, the behavior of crystals in the deposit and how that influences the general deposit behavior, non-Newtonian influence on heat transfer and mass transfer, among others. Wax deposition is a complex topic that has been reviewed over and over. In this review, however, we focus on both presenting what has been discussed in the literature and make a critical analysis. The goal is to increase the general knowledge by highlighting a number of gaps and challenges related to this complex and financially exorbitant issue.

Selection of Representative Scenarios Using Multiple Simulation Outputs for Robust Well Placement Optimization in Greenfields

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In greenfield projects, robust well placement optimization under different scenarios of uncertainty technically requires hundreds to thousands of evaluations to be processed by a flow simulator. However, the simulation process for so many evaluations can be computationally expensive. Hence, simulation runs are generally applied over a small subset of scenarios called representative scenarios (RS) approximately showing the statistical features of the full ensemble. In this work, we evaluated two workflows for robust well placement optimization using the selection of (1) representative geostatistical realizations (RGR) under geological uncertainties (Workflow A), and (2) representative (simulation) models (RM) under the combination of geological and reservoir (dynamic) uncertainties (Workflow B). In both workflows, an existing RS selection technique was used by measuring the mismatches between the cumulative distribution
of multiple simulation outputs from the subset and the full ensemble. We applied the Iterative Discretized Latin Hypercube (IDLHC) to optimize the well placements using the RS sets selected from each workflow and maximizing the expected monetary value (EMV) as the objective function. We evaluated the workflows in terms of (1) representativeness of the RS in different production strategies, (2) quality of the defined robust strategies, and (3) computational costs. To obtain and validate the results, we employed the synthetic UNISIM-II-D-BO benchmark case with uncertain variables and the reference fine- grid model, UNISIM-II-R, which works as a real case. This work investigated the overall impacts of the robust well placement optimization workflows considering uncertain scenarios and application on the reference model. Additionally, we highlighted and evaluated the importance of geological and dynamic uncertainties in the RS selection for efficient robust well placement optimization.

A multi-scale mixed method for a two-phase flow in fractured reservoirs considering passive tracer

Publicado em por .

In this research, the mathematical model represents a two-phase flow in a fractured porous reservoir media, where the Darcy law represents the flow in both fractures and matrix. The flux/pressure of the fluid flow is approximated using a hybridized mixed formulation coupling the fluid in the volume with the fluid flow through th fractures. The spatial dimension of the rock matrix is three and and is coupled with two-dimensional discrete frac- tures. The transport equation is approximated using a lower order finite volume system solved through an upwind scheme. The C++ computational implementation is made using the NeoPZ framework, an object oriented finite element library. The generation of the geometric meshes is done with the software Gmsh. Numerical simulations in 3D are presented demonstrating the advantages of the adopted numerical scheme and these approximations are compared with results of other methods.

A posteriori error estimates for primal hybrid finite element methods

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We present new fully computable a posteriori error estimates for the primal hybrid finite element methods based on equilibrated flux and potential reconstructions. The reconstructed potential is obtained from a local L2 orthogonal projection of the gradient of the numerical solution, with a boundary continuous restriction that comes from a smoothing process applied to the trace of the numerical solution over the mesh skeleton. The equilibrated flux is the solution of a local mixed form problem with a Neumann boundary condition given by the Lagrange multiplier of the hybrid finite element method solution. To establish the a posteriori estimates we divide the error into conforming and non-conforming parts. For the former one, a slight modification of the a posteriori error estimate proposed by Vohral ́ık [1] is applied, whilst the latter is bounded by the difference of the gradient of the numerical solution and the reconstructed potential. Numerical results performed in the environment PZ Devloo [2], show the efficiency of this strategy when it is applied for some test model problems.