Recent Submissions

  • Evaluation of Detailed Reaction Models for the Modeling of Double Cellular Structures in Gaseous Nitromethane Detonation

    Chi, Dunstan Y.; Chatelain, Karl P.; Lacoste, Deanna (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
  • Flame-controlling continuation method for extinction of counterflow sooting flames with detailed chemistry

    Quadarella, Erica; Guo, Junjun; Cuoci, Alberto; Im, Hong G. (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    The generation of S-curves for the extinction of counterflow sooting flames has been accomplished by implementing a flame-controlling continuation method inclusive of soot model. The code can generate solutions for augmented flamelets databases, including soot scalars, useful for Flamelet Progress Variable (FPV) tabulations for sooting turbulent simulations. Indeed, the inclusion of all S-curve's branches brings substantial improvements in the reproduction of extinction/re-ignition regimes or flame/acoustic interactions. In this context, developing a reliable tool for S-curve generation, with coupled reproduction of gas-phase and soot characteristics, is of great importance. The algorithm calculates the flamelet states through a 2-point flame-controlling continuation method with control on species mass fractions. Soot calculation is coupled with gas kinetics at every continuation so that flamelet states are inclusive of soot formation effects on precursors' consumption and flame temperature. The flame and soot features can be correctly predicted along the whole curve with smooth transitions between branches. A brief introduction on general S-curve properties is given, using the implementation on hydrogen flames with different oxidizer's inlet temperatures. Besides, soot characteristics are thoroughly investigated on ethylene flames at different pressures.
  • Flame-controlling continuation method for extinction of counterflow sooting flames with detailed chemistry

    Quadarella, Erica; Guo, Junjun; Cuoci, Alberto; Im, Hong G. (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    The generation of S-curves for the extinction of counterflow sooting flames has been accomplished by implementing a flame-controlling continuation method inclusive of soot model. The code can generate solutions for augmented flamelets databases, including soot scalars, useful for Flamelet Progress Variable (FPV) tabulations for sooting turbulent simulations. Indeed, the inclusion of all S-curve's branches brings substantial improvements in the reproduction of extinction/re-ignition regimes or flame/acoustic interactions. In this context, developing a reliable tool for S-curve generation, with coupled reproduction of gas-phase and soot characteristics, is of great importance. The algorithm calculates the flamelet states through a 2-point flame-controlling continuation method with control on species mass fractions. Soot calculation is coupled with gas kinetics at every continuation so that flamelet states are inclusive of soot formation effects on precursors' consumption and flame temperature. The flame and soot features can be correctly predicted along the whole curve with smooth transitions between branches. A brief introduction on general S-curve properties is given, using the implementation on hydrogen flames with different oxidizer's inlet temperatures. Besides, soot characteristics are thoroughly investigated on ethylene flames at different pressures.
  • Deconfliction and Escape Considerations for Commercial Aircraft Formations

    Saber, Safa I.; Feron, Eric (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    Interest in commercial aircraft formations is growing as a way to reduce airspace congestion and carbon footprint. The realization of these formations requires serious consideration of formation contingencies and safety during closer-in maneuvering of large commercial air- craft. This paper presents considerations and requirements for commercial aircraft formation operations, a sample contingency plan for a formation of up to 7 commercial aircraft based on these considerations and areas for further research. It provides a solid base, inspired by proven military practice, from which further development may proceed.
  • Large eddy simulation of multi-regime burner: a reaction mechanism sensitivity analysis

    Angelilli, Lorenzo; Ciottoli, Pietro Paolo; Hernandez Perez, Francisco; Valorani, Mauro; Im, Hong G.; Malpica Galassi, Riccardo (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    High Reynolds number jets and mixture inhomogeneities enhance the presence of local reaction zones at different combustion regimes. From a modeling perspective, the multi-regime process requires ad-hoc models to be accurately described. In this work, highly resolved large eddy simulations of the Darmstadt multi-regime burner, which spans regimes from a fully non-premixed flame in the core jet region to an outer premixed flame as well as local extinction and re-ignition, are conducted using the eddy dissipation concept. Three different reaction mechanisms for methane are considered to study the effects of the kinetics model on the solution, including the detailed GRI Mech 3.0 and two reduced ones. The averages and fluctuations of the main scalars are compared against experimental data, and the mixing lines and conditional averages in the mixture fraction-progress variable space are also contrasted. The results highlight that a detailed description of chemical kinetics leads to a shrinkage of the predicted non-premixed flame and improves the prediction of the carbon monoxide mass fraction, when compared to the predictions obtained with the reduced chemistry models.
  • Uncertainty Quantification and Sensitivity Analysis for In-plane Thermo-mechanical Properties of 3-D Textile Composites

    Nasution, Muhammad Ridlo Erdata; Palar, Pramudita S.; Hadi, Bambang K.; Widagdo, Djarot; Zuhal, Lavi; Yudhanto, Arief (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    In this paper, uncertainty quantification and sensitivity analysis are performed for investigating the equivalent in-plane thermo-mechanical properties of 3-D orthogonal interlock composites. The composite properties are calculated based on the asymptotic expansion homogenization method omitting out-of-plane periodicity. The analysis herein employs 17 independent properties of constituents as inputs whereby six homogenized properties of composites become the quantity of interests (QOIs). Polynomial chaos expansion (PCE) is used to quantify the output uncertainty and the variance-based sensitivity indices. Two cases are investigated to understand the effects of material variation of constituents on each output of interest. The results show that the PCE model is highly accurate in quantifying the statistical outputs. Furthermore, acceptable accuracy for all QOIs is obtained by 100 sampling points. It is also found that material selection of constituents will determine the importance of input parameters in the calculation of QOIs.
  • Effect of O2/CO2ratio on stability and near field structure of oxyfuel jet diffusion flames at atmospheric pressure.

    Bukar, Muhammad; Basnet, Suman; Kim, Taesung; Magnotti, Gaetano (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    This paper presents an experimental study on the stability and structure of non-premixed CO2 diluted oxyfuel jet flames. DSLR imaging and OH Planar Laser-Induced Fluorescence (PLIF) were used to investigate the nearfield structure of a series of methane jet flames. Three oxidizer compositions (O2/CO2 ratios of 50/50, 40/60, and 32/68) were considered for a fixed co-flow velocity of 0.35 m/s. The PLIF Images were post-processed using MATLAB to obtain OH layer thickness, flame attachment height, and radius. Results show that increasing the CO2 level in the co-flow leads to a reduction in the OH layer thickness and sooting propensity. Both attachment radius and height were found to increase with increased CO2 content in the oxidizer. Furthermore, it was also observed that the flame attachment radius decreased as jet velocity increased while the flame attachment height tended to increase with higher jet velocity.
  • Diagnostic Investigation of Streamtube Flow Choking Effects on the Aerodynamic Performance of Transonic Aircraft

    Rajendran, Vigneshwaran; Shankaran B, Sai; Nandhan, Akshay Kumar; K, Deviparameswari; Sankar, Vigneshwaran; Saravanan, Vignesh; Sanal Kumar, VR (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    The phenomenological manifestation of the nanoscale Sanal flow choking [V.R.S.Kumar et al., Nature Scientific Reports, 2021, DOI: 10.1038/s41598-021-94450-8] and streamtube flow choking [V.R.S.Kumar et al., Physics of Fluids, 2021, DOI:10.1063/5.0040440] is a paradigm shift in the design optimization of transonic aircraft. In the first phase, the proof of the concept of boundary-layer-blockage (BLB) persuaded flow-choking at aircraft-in-ground (AIG)-effect is reviewed and streamtube flow choking effects are discussed. When the ground clearance of an aircraft is relatively small, the developing BLB factor from both planes (the ground and the bottom surface of the aircraft) makes a transient fluid-throat, heading to the Sanal flow choking and supersonic flow development in the channel flow region. In this physical situation, the pressure ratio (Ptotal/Pstatic) at the region of flow choking is entirely a function of the heat capacity ratio of the fluid. In the second phase, streamtube flow choking effects on the aerodynamics performance of transonic aircraft is examined through in silico methodology. The 2D in silico simulations are carried out for stationary airfoils in ground effect and cruise conditions. Different types of airfoils are chosen for the diagnostic investigation to establish the phenomenon of streamtube flow choking during the transonic flying conditions of aircraft. We observed that the flow choking is more susceptible to the low wing aircraft flying in close proximity to the ground and/or sea with relatively high subsonic Mach number (M > 0.56) and the low angle of attack. At this flying condition, the underneath of the transonic aircraft (wing and/or fuselage) and the ground creates the convergent-divergent (CD) channel flow effect leading to Sanal flow choking at the critical total-to-static pressure ratio. We observed that streamtube compression and flow choking is more prone in regions where turbulent viscosity is relatively high. We conjectured that injecting microfluid jets with the high heat capacity ratio at the region ahead of streamtube flow choking can delay or negate the shock wave generation and can improve the aerodynamic performance of transonic aircraft. This diagnostic investigation is a pointer towards for increasing the drag divergence Mach number for the lucrative design optimization of high-performance transonic vehicles with improved propulsion and aerodynamic performances.
  • Knock propensity in a thermally inhomogeneous DME/air mixture: a DNS study

    Luong, Minh Bau; Im, Hong G. (American Institute of Aeronautics and Astronautics, 2022-01-03) [Conference Paper]
    Superknock propensity in a stoichiometric dimethyl-ether (DME)/air mixture with temperature inhomogeneities under realistic IC engine conditions is investigated using two-dimensional direct numerical simulations (DNS). The developing detonation regime at different conditions is identified by varying the initial mean temperature lying in the low-, intermediate-, and high-temperature chemistry regimes, the level of temperature fluctuations, and its characteristic length scale. We found that the cool flame from the first-stage ignition induces synergistic effects on promoting knock tendency. First, it significantly decreases a minimum run-up distance requirement for developing detonation due to the low-temperature chemistry. Second, analyzing the temporal evolution of the spatial distribution of the ignition delay field reveals that the heat release rate from the first-stage ignition effectively modifies the initial field of the ignition delay time, thereby shifting the mixture towards the developing detonation regime. The interaction of multiple ignition kernels is also found to play an important role in enhancing the onset of detonation.
  • Document-Level Relation Extraction with Entity Enhancement and Context Refinement

    Zou, Meng; Yang, Qiang; Qu, Jianfeng; Li, Zhixu; Liu, An; Zhao, Lei; Chen, Zhigang (Springer International Publishing, 2022-01-01) [Conference Paper]
    Document-level Relation Extraction (DocRE) is the task of extracting relational facts mentioned in the entire document. Despite its popularity, there are still two major difficulties with this task: (i) How to learn more informative embeddings for entity pairs? (ii) How to capture the crucial context describing the relation between an entity pair from the document? To tackle the first challenge, we propose to encode the document with a task-specific pre-trained encoder, where three tasks are involved in pre-training. While one novel task is designed to learn the relation semantic from diverse expressions by utilizing relation-aware pre-training data, the other two tasks, Masked Language Modeling (MLM) and Mention Reference Prediction (MRP), are adopted to enhance the encoder’s capacity in text understanding and coreference capturing. For addressing the second challenge, we craft a hierarchical attention mechanism to refine the context for entity pairs, which considers the embeddings from the encoder as well as the sequential distance information of mentions in the given document. Extensive experimental study on the benchmark dataset DocRED verifies that our method achieves better performance than the baselines.
  • Enhancing both Local and Global Entity Linking Models with Attention

    Li, Jinliang; Liu, Haoyu; Zhang, Yulong; Zhang, Li; Yang, Qiang; Qu, Jianfeng; Li, Zhixu (Springer International Publishing, 2022-01-01) [Conference Paper]
    Entity linking aims at mapping the mentions in a document to their corresponding entities in a given knowledge base, which involves two continuous steps, i.e., local step which focuses on modeling the semantic meaning of the context around the mention, and global step which optimizes the refereed entities coherence in the document. Upon the existing great efforts on both steps, this paper would like to enhance both local and global entity linking models with several attention mechanisms respectively. Particularly, we propose to leverage self-attention mechanism and LSTM-based attention mechanism to better capture the inter-dependencies between tokens in the mention context for the local entity linking models. We also adopt a hierarchical attention network with a multi-head attention layer to better represent documents with one or multiple topics for the global entity linking models, which could help alleviate the side effect of error accumulation. Extensive empirical study on standard benchmarks proves the effectiveness of the proposed models.
  • Fluids, soils and rocks: Electromagnetic and NMR signatures

    Hakiki, Farizal; Santamarina, Carlos (Society of Exploration Geophysicists, 2021-12-24) [Conference Paper]
    Electromagnetic phenomena support the development of exceptional methods for non-destructive, non-contact geomaterial characterization and subsurface process monitoring. Such phenomena include Ohmic conduction, electromagnetic wave propagation and nuclear magnetic resonance. The physical parameters involved include DC conductivity σ, complex permittivity ε*(ω) and complex permeability μ*(ω) spectra, and nuclear magnetic resonance relaxation. These parameters reflect mineralogy, particle and pore size distributions, pore network topology and anisotropy, fluid composition, state and fluid-mineral interaction. Proper data interpretation requires careful understanding of underlying physical concepts and measurement methods.
  • Field Assessment of Camera Based Drilling Dynamics

    Koulidis, Alexis; Abdullatif, Mohamed; Abdel-Kader, Ahmed Galal; Ayachi, Mohammed Ilies; Ahmed, Shehab; Gooneratne, Chinthaka; Magana-Mora, Arturo; Affleck, Mike; Alsheikh, Mohammed (SPE, 2021-12-15) [Conference Paper]
    Surface data measurement and analysis are an established mean of detecting drillstring low-frequency torsional vibration or stick-slip. The industry has also developed models that link surface torque and downhole drill bit rotational speed. Cameras provide an alternative noninvasive approach to existing wired/wireless sensors used to gather such surface data. The results of a preliminary field assessment of drilling dynamics utilizing camera-based drillstring monitoring are presented in this work. Detection and timing of events from the video are performed using computer vision techniques and object detection algorithms. A real-time interest point tracker utilizing homography estimation and sparse optical flow point tracking is deployed. We use a fully convolutional deep neural network trained to detect interest points and compute their accompanying descriptors. The detected points and descriptors are matched across video sequences and used for drillstring rotation detection and speed estimation. When the drillstring's vibration is invisible to the naked eye, the point tracking algorithm is preceded with a motion amplification function based on another deep convolutional neural network. We have clearly demonstrated the potential of camera-based noninvasive approaches to surface drillstring dynamics data acquisition and analysis. Through the application of real-time object detection algorithms on rig video feed, surface events were detected and timed. We were also able to estimate drillstring rotary speed and motion profile. Torsional drillstring modes can be identified and correlated with drilling parameters and bottomhole assembly design. A novel vibration array sensing approach based on a multi-point tracking algorithm is also proposed. A vibration threshold setting was utilized to enable an additional motion amplification function providing seamless assessment for multi-scale vibration measurement. Cameras were typically devices to acquire images/videos for offline automated assessment (recently) or online manual monitoring (mainly), this work has shown how fog/edge computing makes it possible for these cameras to be "conscious" and "intelligent," hence play a critical role in automation/digitalization of drilling rigs. We showcase their preliminary application as drilling dynamics and rig operations sensors in this work. Cameras are an ideal sensor for a drilling environment since they can be installed anywhere on a rig to perform large-scale live video analytics on drilling processes.
  • Uncertainty Quantification and Optimization of Deep Learning for Fracture Recognition

    Santoso, Ryan; He, Xupeng; Alsinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-12-15) [Conference Paper]
    Automatic fracture recognition from borehole images or outcrops is applicable for the construction of fractured reservoir models. Deep learning for fracture recognition is subject to uncertainty due to sparse and imbalanced training set, and random initialization. We present a new workflow to optimize a deep learning model under uncertainty using U-Net. We consider both epistemic and aleatoric uncertainty of the model. We propose a U-Net architecture by inserting dropout layer after every "weighting" layer. We vary the dropout probability to investigate its impact on the uncertainty response. We build the training set and assign uniform distribution for each training parameter, such as the number of epochs, batch size, and learning rate. We then perform uncertainty quantification by running the model multiple times for each realization, where we capture the aleatoric response. In this approach, which is based on Monte Carlo Dropout, the variance map and F1-scores are utilized to evaluate the need to craft additional augmentations or stop the process. This work demonstrates the existence of uncertainty within the deep learning caused by sparse and imbalanced training sets. This issue leads to unstable predictions. The overall responses are accommodated in the form of aleatoric uncertainty. Our workflow utilizes the uncertainty response (variance map) as a measure to craft additional augmentations in the training set. High variance in certain features denotes the need to add new augmented images containing the features, either through affine transformation (rotation, translation, and scaling) or utilizing similar images. The augmentation improves the accuracy of the prediction, reduces the variance prediction, and stabilizes the output. Architecture, number of epochs, batch size, and learning rate are optimized under a fixed-uncertain training set. We perform the optimization by searching the global maximum of accuracy after running multiple realizations. Besides the quality of the training set, the learning rate is the heavy-hitter in the optimization process. The selected learning rate controls the diffusion of information in the model. Under the imbalanced condition, fast learning rates cause the model to miss the main features. The other challenge in fracture recognition on a real outcrop is to optimally pick the parental images to generate the initial training set. We suggest picking images from multiple sides of the outcrop, which shows significant variations of the features. This technique is needed to avoid long iteration within the workflow. We introduce a new approach to address the uncertainties associated with the training process and with the physical problem. The proposed approach is general in concept and can be applied to various deep-learning problems in geoscience.
  • Multi-Fidelity Bayesian Approach for History Matching in Reservoir Simulation

    Santoso, Ryan; He, Xupeng; Alsinan, Marwa; Figueroa Hernandez, Ruben; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-12-15) [Conference Paper]
    History matching is a critical step within the reservoir management process to synchronize the simulation model with the production data. The history-matched model can be used for planning optimum field development and performing optimization and uncertainty quantifications. We present a novel history matching workflow based on a Bayesian framework that accommodates subsurface uncertainties. Our workflow involves three different model resolutions within the Bayesian framework: 1) a coarse low-fidelity model to update the prior range, 2) a fine low-fidelity model to represent the high-fidelity model, and 3) a high-fidelity model to re-construct the real response. The low-fidelity model is constructed by a multivariate polynomial function, while the high-fidelity model is based on the reservoir simulation model. We firstly develop a coarse low-fidelity model using a two-level Design of Experiment (DoE), which aims to provide a better prior. We secondly use Latin Hypercube Sampling (LHS) to construct the fine low-fidelity model to be deployed in the Bayesian runs, where we use the Metropolis-Hastings algorithm. Finally, the posterior is fed into the high-fidelity model to evaluate the matching quality. This work demonstrates the importance of including uncertainties in history matching. Bayesian provides a robust framework to allow uncertainty quantification within the reservoir history matching. Under uniform prior, the convergence of the Bayesian is very sensitive to the parameter ranges. When the solution is far from the mean of the parameter ranges, the Bayesian introduces bios and deviates from the observed data. Our results show that updating the prior from the coarse low-fidelity model accelerates the Bayesian convergence and improves the matching convergence. Bayesian requires a huge number of runs to produce an accurate posterior. Running the high-fidelity model multiple times is expensive. Our workflow tackles this problem by deploying a fine low-fidelity model to represent the high-fidelity model in the main runs. This fine low-fidelity model is fast to run, while it honors the physics and accuracy of the high-fidelity model. We also use ANOVA sensitivity analysis to measure the importance of each parameter. The ranking gives awareness to the significant ones that may contribute to the matching accuracy. We demonstrate our workflow for a geothermal reservoir with static and operational uncertainties. Our workflow produces accurate matching of thermal recovery factor and produced-enthalpy rate with physically-consistent posteriors. We present a novel workflow to account for uncertainty in reservoir history matching involving multi-resolution interaction. The proposed method is generic and can be readily applied within existing history-matching workflows in reservoir simulation.
  • High-Resolution Micro-Continuum Approach to Model Matrix-Fracture Interaction and Fluid Leakage

    He, Xupeng; Alsinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-12-15) [Conference Paper]
    Understanding the fundamental mechanism of fracture-matrix fluid exchange is crucial for the modeling of fractured reservoirs. Traditionally, high-resolution simulations for flow in fractures often neglect the matrix-fracture leakage influence on the fracture hydraulic properties, i.e., assuming impermeable fracture walls. This work introduces a micro-continuum approach to capture the matrix-fracture leakage interaction and its effect on the rock fractures’ hydraulic properties. Because of the multiscale nature of fractured media, full physics Navier-Stokes (NS) representation everywhere in the whole domain is not feasible. We thus employ NS equations to describe the flow in the fracture, and Darcy’s law to model the flow in the surrounding porous rocks. Such hybrid modeling is achieved using the extended Darcy-Brinkman-Stokes (DBS) equation. With this approach, a unified conservation equation for flow in both media is applied by choosing appropriate parameters (e.g., porosity and permeability) for the corresponding domains. We apply an accurate Mixed Finite Element approach to solve the extended DBS equation. Various sensitivity analyses are conducted to explore the leakage effects on the fracture hydraulic properties by varying surrounding matrix permeability, fracture roughness, and Reynolds number (Re). Streamline profiles show the presence of back-flow phenomena, where in-flow and out-flow are possible between the matrix and the fractures. Further, zones of stagnant (eddy) flow are observed around locations with large asperities of sharp corners under high Re conditions. Numerical results show the significant effects of roughness and inertia on flow predictions in fractures for both impermeable and leaky wall cases. Besides, the side-leakage effect can create non-uniform flow behavior within the fracture that may differ significantly from the case with impermeable wall conditions. And this matrix-fracture leakage influence on hydraulic properties of rock fractures matters especially for cases with high matrix permeability, high fracture roughness, and low Re values. In summary, we present a high-resolution micro-continuum approach to explore the flow exchange behavior between the fracture and rock matrix, and further investigate the static and dynamic effects, including variable Reynold numbers, mimicking flow near and away from the wellbore. The approach and results provide significant insights into the flow of fluids through fractures within permeable rocks and can be readily applied in field-scale reservoir simulations.
  • An Accurate Cubic Law for the Upscaling of Discrete Natural Fractures

    He, Xupeng; AlSinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-12-15) [Conference Paper]
    Abstract Modeling fluid flow in fractured reservoirs requires an accurate evaluation of the hydraulic properties of discrete fractures. Full Navier-Stokes simulations provide an accurate approximation of the flow within fractures, including fracture upscaling. However, its excessive computational cost makes it impractical. The traditionally used cubic law (CL) is known to overshoot the fracture hydraulic properties significantly. In this work, we propose an alternative method based on the cubic law. We first develop geometric rules based on the fracture topography data, by which we subdivide the fracture into segments and local cells. We then modify the aperture field by incorporating the effects of flow direction, flow tortuosity, normal aperture, and local roughness. The approach is applicable for fractures in 2D and 3D spaces. This paper presented almost all existing CL-based models in the literature, which include more than twenty models. We benchmarked all these models, including our proposed model, for thousands of fracture cases. High-resolution simulations solving the full-physics Navier-Stokes (NS) equations were used to compute the reference solutions. We highlight the behavior of accuracy and limitations of all tested models as a function of fracture geometric characteristics, such as roughness. The obtained accuracy of the proposed model showed the highest for more than 2000 fracture cases with a wide range of tortuosity, roughness, and mechanical aperture variations. None of the existing methods in the literature provide this level of accuracy and applicability. The proposed model retains the simplicity and efficiency of the cubic law and can be easily implemented in workflows for reservoir characterization and modeling.
  • Novel Analytical Solution and Type-Curves for Lost-Circulation Diagnostics of Drilling Mud in Fractured Formation

    Albattat, Rami; Hoteit, Hussein (SPE, 2021-12-15) [Conference Paper]
    Loss of circulation is a major problem that often causes interruption to drilling operations, and reduction in efficiency. This problem often occurs when the drilled wellbore encounters a high permeable formation such as faults or fractures, leading to total or partial leakage of the drilling fluids. In this work, we present a novel semi-analytical solution and type-curves that offer a quick and accurate diagnostic tool to assess the lost-circulation of Herschel-Bulkley fluids in fractured media. Based on the pressure and mud loss trends, the tool can estimate the effective fracture conductivity, the cumulative mud-loss volume, and the leakage period. The behavior of lost-circulation into fractured formation can be assessed using analytical methods that can be deployed to perform flow diagnostics, such as the rate of fluid leakage and the associated fracture hydraulic properties. In this study, we develop a new semi-analytical method to quantify the leakage of drilling fluid flow into fractures. The developed model is applicable for non-Newtonian fluids with exhibiting yield-power-law, including shear thickening and thinning, and Bingham plastic fluids. We propose new dimensionless groups and generate novel dual type-curves, which circumvent the non-uniqueness issues in trend matching of type-curves. We use numerical simulations based on finite-elements to verify the accuracy of the proposed solution, and compare it with existing analytical solutions from the literature. Based on the proposed semi-analytical solution, we propose new dimensionless groups and generate type-curves to describe the dimensionless mud-loss volume versus the dimensionless time. To address the non-uniqueness matching issue, we propose, for the first time, complimentary derivative-based type-curves. Both type-curve sets are used in a dual trend matching, which significantly reduced the non-uniqueness issue that is typically encountered in type-curves. We use data for lost circulation from a field case to show the applicability of the proposed method. We apply the semi-analytical solver, combined with Monte-Carlo simulations, to perform a sensitivity study to assess the uncertainty of various fluid and subsurface parameters, including the hydraulic property of the fracture and the probabilistic prediction of the rate of mud leakage into the formation. The proposed approach is based on a novel semi-analytical solution and type-curves to model the flow behavior of Herschel-Bulkley fluids into fractured reservoirs, which can be used as a quick diagnostic tool to evaluate lost-circulation in drilling operations.
  • Artificial Intelligence Aided Geologic Facies Classification in Complex Carbonate Reservoirs

    Katterbauer, Klemens; Marsala, Alberto; Zhang, Yanhui; Hoteit, Ibrahim (SPE, 2021-12-15) [Conference Paper]
    Facies classification for complex reservoirs is an important step in characterizing reservoir heterogeneity and determining reservoir properties and fluid flow patterns. Predicting rock facies automatically and reliably from well log and associated reservoir measurements is therefore essential to obtain accurate reservoir characterization for field development in a timely manner. In this study, we present an artificial intelligence (AI) aided rock facies classification framework for complex reservoirs based on well log measurements. We generalize the AI-aided classification workflow into five major steps including data collection, preprocessing, feature engineering, model learning cycle, and model prediction. In particular, we automate the process of facies classification focusing on the use of a deep learning technique, convolutional neural network, which has shown outstanding performance in many scientific applications involving pattern recognition and classification. For performance analysis, we also compare the developed model with a support vector machine approach. We examine the AI-aided workflow on a large open dataset acquired from a real complex reservoir in Alberta. The dataset contains a collection of well-log measurements over a couple of thousands of wells. The experimental results demonstrate the high efficiency and scalability of the developed framework for automatic facies classification with reasonable accuracy. This is particularly useful when quick facies prediction is necessary to support real-time decision making. The AI-aided framework is easily implementable and expandable to other reservoir applications.
  • Internet of Things IoT Edge Computer Vision Systems on Drilling Rigs

    Alsheikh, Mohammed; Gooneratne, Chinthaka; Magana-Mora, Arturo; Ibrahim, Mohamad; Affleck, Mike; Contreras, William; Zhan, Guodong David; Jamea, Musab Al; Umairin, Isa Al; Zaghary, Ahmed; Ayachi, Mohammed Ilies; Abdelkader, Ahmed Galal; Ahmed, Shehab; Makowski, Greg; Kapoor, Hitesh (SPE, 2021-12-15) [Conference Paper]
    This study focuses on the design and infrastructure development of Internet-of-Things (IoT) edge platforms on drilling rigs and the testing of pilot IoT-Edge Computer Vision Systems (ECVS) for the optimization of drilling processes. The pilot technology presented in this study, Well Control Space Out System (WC-SOS), reduces the risks associated with hydrocarbon release during drilling by significantly increasing the success and time response for shut-in a well. Current shut-in methods that require manual steps are prone to errors and may take minutes to perform, which is enough time for an irreversible escalation in the well control incident. Consequently, the WC-SOS enables the drilling rig crew to shut-in a well in seconds. The IoT-ECVS deployed for the WC-SOS can be seamlessly expanded to analyze drillstring dynamics and drilling fluid cuttings/solids/flow analysis at the shale shakers in real-time. When IoT-ECVSs communicate with each other, their value is multiplied, which makes interoperability essential for maximizing benefits in drilling operations.

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