Eduardo Gildin

Texas A&M University

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An Open-Source Enabled Drilling Simulation Consortium for Academic and Commercial Applications

SPE Latin American and Caribbean Petroleum Engineering Conference (2020)

Enrique Z. Losoya Eduardo Gildin Samuel Noynaert Zenon Medina‐Cetina Tim Crain

Abstract Simulation of drilling processes involves the seamless integration of strongly coupled physics, numeric, and economic models. Operators desire advanced drilling simulation software that can mimic reality and yet be practical for daily operations. At the same time, academic researchers are devoting time and effort to develop robust and accurate models of every module of an integrated drilling environment but are challenged with translating their original contributions into the operational setting. We seek to solve both of these issues through a distinctive collaboration consortium based on an open-source paradigm. We describe and propose an advanced drilling simulation developed through a joint industry consortium at Texas A&M University. The simulator provides free access to sophisticated and reliable drilling dynamics solvers. This includes drill string dynamics, torque and drag analysis, geologic modeling, hydraulics, and wellbore pressure modeling, visualization, and operator interfaces. The simulator is written in C++ and is built on top of high-performance open source libraries that leverages parallel computing, GPU acceleration, multibody, and computational fluid dynamics solvers as well as other tools (see figure for further details). We will assist industry and academic users to employ our open-source tool. In addition, we will help said parties further develop our framework into proprietary and protected business software via the addition of custom functionality. The simulator core was successfully developed and has been used to model horizontal drilling, while providing near real-time performance. The framework has been used in several applications successfully, including modeling shallow horizontal jetting, rock drilling, and steering; as well as reconstructing spatial data from high fidelity downhole signals for borehole evaluation, and the development of improved downhole navigation algorithms. We believe that a collaborative development effort between academia and industry will bring solutions to complex modeling needs faster and more economically than any individual endeavor. To this end, the authors will also show how one can partner with Texas A&M University to obtain access to the open-source enabled drilling simulation framework and platform to collaborate, improve and create solutions for new and existing problems.

Drill pipe

Simulation software

10.2118/198943-ms

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Citations (4)

A Control Perspective to Adaptive Time-Stepping in Reservoir Simulation

SPE Reservoir Simulation Conference (2017)

Dany Akakpo Eduardo Gildin

Reservoir Simulation

Time stepping

10.2118/182601-ms

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Citations (7)

Log-Log Analysis for Compaction Damage Evaluation Caused by Pores Collapse in Depletion-Dependent Oil Reservoirs

50th U.S. Rock Mechanics/Geomechanics Symposium (2024)

Fernando Bastos Fernandes Eduardo Gildin Arthur M. B. Braga M. C. Duarte

ABSTRACT: The impact of the mechanical formation damage in the production curve caused by the transient permeability hysteresis in pressure-sensitive reservoirs has an important role in oilfield developments. Hence, the petroleum industry has continuously sought new analytical approaches to provide adequate, well-reservoir performance management and surveillance. This work proposes anew transient two-dimensional (2-D) analytical solution for modeling the oil flow in a permeability hysteretic pressure-dependent reservoir during alternating loading/unloading cycles. The nonlinear hydraulic diffusivity equation (NHDE) is perturbed through a first-order asymptotic series expansion technique. The reservoir engineering literature shows that this first-order expansion represents the magnitude of the nonlinear phenomena regarding pressure-sensitive rock and fluid properties. A new hysteretic deviation factor is presented for flow (drawdown) and buildup periods. This deviation factor represents the permeability deviation during the drawdown and its partial restoration in the buildup period. A set of pressure and permeability field data is used as input to the computational code. The model calibration is performed by a porous media numerical oil flow simulator named CMG IMEX®, broadly used in formation evaluation and reservoir engineering literature. The results presented high accuracy for the drawdown and buildup of hysteretic and non-hysteretic cases. 1 INTRODUCTION The mathematical modeling of the production loss caused by the reservoir compaction damage is essential to prevent premature well abandonment and field disinvestment (Fernandes, 2022; Fernandes and Braga, 2023). The Hydraulic Diffusivity Equation (HDE) models the isothermal, single, and multi-phase flow in porous media. It is derived from the coupling of Darcy's law, continuity equation, and porous media constitutive equations for rock and fluid properties (Matthews and Russell, 1967). Often in the petroleum engineering and dynamics of fluids in porous media scientific literature, the Linear Hydraulic Diffusivity Equation (LHDE) is solved through Laplace and Fourier transform or Boltzmann transformation, (Everdingen and Hurst, 1949; Matthews and Russell, 1967; Peres et al., 1989). In order to achieve cost savings and accurate model demand, analytical solutions for the Nonlinear Hydraulic Diffusivity Equation (NHDE) have been studied for many years by geoscientists, well-testing, and reservoir engineers.

10.56952/arma-2024-0028

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Citations (0)

Two-Step Predict and Correct Non-Intrusive Parametric Model Order Reduction for Changing Well Locations Using a Machine Learning Framework

Energies (2021)

Hardikkumar Zalavadia Eduardo Gildin

The objective of this paper is to develop a two-step predict and correct non-intrusive Parametric Model Order Reduction (PMOR) methodology for the problem of changing well locations in an oil field that can eventually be used for well placement optimization to gain significant computational savings. In this work, we propose a two-step PMOR procedure, where, in the first step, a Proper Orthogonal Decomposition (POD)-based strategy that is non-intrusive to the simulator source code is introduced, as opposed to the convention of using POD as a simulator intrusive procedure. The non-intrusiveness of the proposed technique stems from formulating a novel Machine Learning (ML)-based framework used with POD. The features of the ML model (Random Forest was used here) are designed such that they take into consideration the temporal evolution of the state solutions and thereby avoid simulator access for the time dependency of the solutions. The proposed PMOR method is global, since a single reduced-order model can be used for all the well locations of interest in the reservoir. We address the major challenge of the explicit representation of the well location change as a parameter by introducing geometry-based features and flow diagnostics-inspired physics-based features. In the second step, an error correction model based on reduced model solutions is formulated to correct for discrepancies in the state solutions at well grid blocks expected from POD basis for new well locations. The error correction model proposed uses Artificial Neural Networks (ANNs) that consider the physics-based reduced model solutions as features, and is proved to reduce the error in QoI (Quantities of Interest), such as oil production rates and water cut, significantly. This workflow is applied to a simple homogeneous reservoir and a heterogeneous channelized reservoir using a section of SPE10 model that showed promising results in terms of model accuracy. Speed-ups of about 50×–100× were observed for different cases considered when running the test scenarios. The proposed workflow for Reduced-Order Modeling is “non-intrusive” and hence can increase its applicability to any simulator used. Additionally, the method is formulated such that all the simulation time steps are independent and hence can make use of parallel resources very efficiently and also avoid stability issues that can result from error accumulation over time steps.

Representation

Model order reduction

Basis (linear algebra)

Code (set theory)

10.3390/en14061765

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Citations (4)

Model and controller reduction of large-scale structures based on projection methods

Eduardo Gildin

Source

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Citations (8)

Model-Order Reduction for Coupled Flow and Linear Thermal-Poroplasticity with Applications to Unconventional Reservoirs

Springer eBooks (2022)

Horacio Flórez Eduardo Gildin Patrick Morkos

Geomechanics

Multiphysics

Reservoir Simulation

10.1007/978-3-030-95157-3_21

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Citations (0)

Mesoscopic Simulation of Slip Motion for Gas Flow in Nanochannels

Kingsley I. Madiebo Hadi Nasrabadi Eduardo Gildin

In this paper the Lattice Boltzmann method (LBM) was used to investigate gas flow in nano-channels, the critical region beyond which indefinite slip motion occurs in this channel and its effect on the deduced permeability. We defined a parallel-bounded planar two-dimensional domain for our simulation and calculated the system velocity profile. Numerical conformity was achieved when compared with the Hagen-Poiseuille’s equation. Good agreement was also established between the simulation and existing models reported in literature. A closer look at the region of full slip motion was also done and we observed that above a critical slip coefficient, a sudden significant increase in slip motion sets-in indefinitely with respect to the system time scale. The results indicate that when the LBM is used in gas flow simulation in nano-channels, if the slip effect is increased there is an effective increase in the fluid velocity and this affects the deduced permeability.

Hagen–Poiseuille equation

Mesoscopic physics

Lattice Boltzmann methods

Lattice gas automaton

Slip ratio

10.1115/imece2015-53696

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Citations (2)

Parametrized Model Order Reduction Applied to Reservoir Simulation

Proceedings (2010)

Eduardo Gildin

The development of efficient numerical reservoir simulation is an essential step in devising advanced production optimization strategies and uncertainty quantification methods applied to porous media flow. In this case, a highly accurate and detailed description of the underlying models lead to a solution of a set of partial differential equations, which after discretization, induce dynamical systems of very large dimensions. In order to overcome the computational costs associated with these large-scale models, several forms of model-order reduction have been proposed in the literature. In porous media flow, two different approaches are used: (1) a "coarsening" of the discretization grid in a process called upscaling; and (2) a reduction in the number of state variables (i.e., pressure and saturation) directly in a process called approximation of dynamical systems. Recently, the the idea of combining both approaches have been proposed using the control-relevant upscaling (CRU) methodology. In this paper, we investigate the use of the so-called parametric model order reduction (PMOR) techniques applied to porous media flow simulation in a system-theoretical framework. PMOR entails the generation of reduced-order models which retains the functional dependency on specific parameters of the original large-scale system. In particular, this work focuses on the the application of PMOR to the case of single-phase flow, in which the dependencies of the porous media properties, such as, permeability, and the discretization parameter, such as, grid sizes, is investigated. The the main ideas behind model order reduction will be reviewed, including the general framework of interpolatory projection techniques and applications to single-phase flow test cases will be developed.

Reservoir Simulation

Model order reduction

10.3997/2214-4609.20145001

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Citations (3)

Progress Toward an Open-Source Drilling Community: Contributing and Curating Models

IADC/SPE International Drilling Conference and Exhibition (2022)

Roman Shor Shanti Swaroop Kandala Eduardo Gildin Samuel Noynaert Enrique Z. Losoya

Abstract As a follow-up to the challenge set forth by (Pastusek et al, 2019) to create an open-source drilling community for modelling and data, this paper presents the charter, contribution methods, workflows, and interoperability standards of the open source drillstring modelling community. A series of examples, ranging from simple drillstring and fluids models to coupled drillstring dynamics models are included. They demonstrate the coding styles, validation, and verification necessary to submit a model to the repository. These models include a torsional drillstring model, a coupled axial-torsional drillstring dynamics model with integrated control system responses, an advanced fluid model for drilling fluids, and a bottomhole assembly dynamics model. The drillstring modelling and overall optimization communities are invited to make use of these models and contribute their own to create an active ecosystem that promotes progress.

Drill pipe

10.2118/208794-ms

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Citations (8)

Efficient Fractured Reservoir Simulation Using Lattice Boltzmann Method

SPE Latin American and Caribbean Petroleum Engineering Conference (2015)

Z. Benamram A. Tarakanov Hadi Nasrabadi Eduardo Gildin

Abstract In this paper, for the first time, a comprehensive methodology for the application of a generalized lattice Boltzmann model towards simulation of fluid flow within a hydrocarbon fractured reservoir is presented to validate its use as a reservoir simulation tool. The lattice Boltzmann method simulates fluid flow by defining a system with microscopic flow characteristics. In this method, the fluid consists of fictitious particles (mass fractions). These particles propagate (stream) and collide. The method assumes discretization of the physical system in both space and time. In space, the particles are allowed to move on lattice nodes. Interaction (possible collision) of particles is evaluated at these time steps. The interaction step is designed in such a way that the generalized Navier-Stokes equation is valid for the time-average motion of the particles. The focus of this work is the formulation of precise boundary conditions on the surface of fractures and the wellbore. In addition, the set of dimensionless parameters that govern the evolution of the pressure profile is redefined. Pressure profiles are presented visually throughout this paper to provide the reader insight how such a product would be utilized by the petroleum engineer. Most importantly, the methodology is tested against commercial software and results show excellent agree-ment for both homogenous and heterogenous reservoir cases. This strong agreement provides motivation for the oil and gas community to expand this model towards more complex subsurface conditions.

Lattice Boltzmann methods

Lattice (music)

Dimensionless quantity

10.2118/177263-ms

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Citations (3)