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Journal of Petroleum Science & Engineering
Elsevier Science B.V.
Journal of Petroleum Science & Engineering

Elsevier Science B.V.

0920-4105

Journal of Petroleum Science & Engineering/Journal Journal of Petroleum Science & Engineering
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    An improved rock typing method for tight sandstone based on new rock typing indexes and the weighted fuzzy kNN algorithm

    Ji, LiliLin, MianJiang, WenbinCao, Gaohui...
    16页
    查看更多>>摘要：Petrophysical rock typing is a very important problem in flow unit interpretation and reservoir characterization. Unlike the sandstone, the presence of numerous nanopores in tight sandstone can cause strong gas and liquid non-linear flow. And this makes the traditional rock typing indexes derived from Darcy'law unsuitable for tight sandstone. In this paper, new rock typing indexes, including the Darcy index (Fi), the gas non-Darcy index (Kc) and the liquid non-Darcy index (Sr), have been proposed to describe the non-linear flow characteristics in tight sandstone. In addition, the limit pore ranges for gas and liquid non-Darcy flow have been determined based on these indexes. Then the weighted fuzzy kNN algorithm, which can consider the weight differences between different rock typing indexes, is combined with three indexes to improve the accuracy of rock typing. In order to test the rock typing indexes and the weighted fuzzy kNN algorithm, the tight sandstone dataset in Upper Triassic Yanchang Formation, Ordos Basin, NW China has been constructed with RES (representative element surface) random pore network and experiment data. The results show that the new rock typing indexes and the weighted fuzzy kNN algorithm have better performance in typing tight sandstone than the traditional methods. Moreover, 30 mercury injection capillary pressure (MICP) curves measured on highly inhomogeneous tight sandstone samples from the research area have also been used to validate our method. All the results have proved that the proposed new rock typing indexes and weighted fuzzy kNN algorithm can type the tight sandstone very well, and they play a significant role in permeability prediction, reservoir modeling and simulation.
      原文链接:
    • NSTL
    • Elsevier

    Constructing sub-scale surrogate model for proppant settling in inclined fractures from simulation data with multi-fidelity neural network

    Tang, PengfeiZeng, JunshengZhang, DongxiaoLi, Heng...
    15页
    查看更多>>摘要：Particle settling in inclined channels is an important phenomenon that occurs during hydraulic fracturing of shale gas production. In order to accurately simulate the large-scale (field-scale) proppant transport process, constructing a fast and accurate sub-scale proppant settling model, or surrogate model, becomes a critical issue. However, mapping between physical parameters and proppant settling velocity is complex, which makes the model construction difficult. Previously, particle settling has usually been investigated via high-fidelity experiments and meso-scale numerical simulations, both of which are time-consuming. In this work, we propose a new method, i.e., the multi-fidelity neural network (MFNN), to construct a settling surrogate model, which could greatly reduce computational cost while preserving accuracy. The results demonstrate that constructing the settling surrogate with the MFNN can reduce the need for high-fidelity data and thus computational cost by 80%, while the accuracy lost is less than 5% compared to a high-fidelity surrogate. Moreover, the investigated particle settling surrogate is applied in macro-scale proppant transport simulation, which shows that the settling model is significant to proppant transport and yields accurate results. The framework opens novel pathways for rapidly predicting proppant settling velocity in reservoir applications. Furthermore, the method can be extended to almost all numerical simulation tasks, especially high-dimensional tasks.
      原文链接:
    • NSTL
    • Elsevier

    Modeling of microflow during viscoelastic polymer flooding in heterogenous reservoirs of Daqing Oilfield

    Zhong, HuiyingHe, YuanyuanYang, ErlongBi, Yongbin...
    10页
    查看更多>>摘要：Viscoelastic polymer flooding has been extensively used in oilfield development as an enhanced oil recovery method. Understanding the microflow mechanism is necessary to promote the polymer displacement effect and design the polymer flooding scheme. Previous studies have investigated polymer flooding mechanisms, such as a favorable mobility ratio and increasing sweep efficiency; however, the elasticity effect on displacement efficiency is still unclear, particularly in a heterogeneous reservoir. Class II reservoirs, which have an effective thickness between 1 and 4 m and a permeability greater than 100 mD, have recently become the target zones of polymer flooding in the Daqing Oilfield. Class II reservoirs are subdivided into type A and B oil layers. Compared with the type A oil layer, type B has a larger permeability contrast, more severe heterogeneity, and worse connectivity. There are considerable differences between types A and B in the actual development of polymer flooding as well as between type B oil layers of different oilfield blocks. Thus, it is necessary to investigate the factors that influence the micro-oil displacement mechanism. In this study, local and global micro-pore models are established based on a computed tomography scan slice of Class II reservoir cores, and mathematical models of the viscoelastic polymer and oil two-phase flow in porous media are established. The log conformation method is used, which can effectively enhance convergence, owing to a high relaxation time inducing high non-linear of equation. The volume-of-fluid method is used to track the interface between the two phases. The governing equations are solved using the OpenFOAM platform, which is open-source software written in C++. Then, the influences of pore structure and polymer elasticity on displacement characteristics are studied. The simulation results revealed that owing to the pore structure, the micro-oil displacement efficiencies of B_GI and B_PII, which belong to the type B oil layer, are lower than that of A_SIII, which belongs to type A, by 26.8% and 10.9%, respectively. The oil displacement efficiency of a commingled production comprising B_PII and B_GI is 4.0% and 15.6% lower than that of single-layer productions of B_PII and B_GI, respectively. The oil displacement efficiency increases by 6.45% when the relaxation time increases from 0.5 to 2 s and decreases when the relaxation time increases from 2 to 10 s. Therefore, by combining the micro-oil displacement efficiency and injectivity of a high-molecular-weight polymer, the optimum relaxation time is determined to be 2 s. The obtained results are significant for the design strata of a commingled production scheme and the optimization of polymer solutions in the type B oil layer of the Daqing Oilfield.
      原文链接:
    • NSTL
    • Elsevier

    Production rate of multi-fractured wells modeled with Gaussian pressure transients

    Weijermars, Ruud
    24页
    查看更多>>摘要：This study presents new pressure transient solutions, illustrated with some examples of the vast practical application potential. Gaussian pressure transients (GPT) are derived here to quantify the temporal and spatial propagation of instantaneous pressure changes in porous media, as initiated from cylindrical sources (vertical wells) and planar sources (hydraulic fractures). After solving the scalar pressure field in the reservoir space, and adequately accounting for the interference of the various pressure fronts by mathematical integration and superposition, the resulting pressure gradients solve for the velocity field in the reservoir space. Unique for GPT solutions is that the well rate, unlike in the traditional well-testing equations, does not appear as an input. Applying Darcy's Law, the fluid flux from the reservoir into the well and hydraulic fractures can be directly computed from the GPT solutions. The closed-form production-forecasting model can be implemented either in matrix-coded flow-visualizations of pressure depletion and flow paths for reservoir sections or in grid-less spreadsheet solutions to instantaneously generate production profiles for wells in any type of fluid injection/ extraction project (water production, geothermal energy extraction, hydrocarbon production, and fluid disposal wells). Additionally, the Gaussian method also is suitable for physics-based decline curve analysis. The practical examples included in this study are for Eagle Ford shale oil and Marcellus dry gas wells. The hydraulic diffusivities are constrained by the field data, and range between 2.36 x10(-10) and 3.48 x10(-10) m(2) s(-1) for the Eagle Ford Formation; for the Marcellus the range is 3.64x10(-9) to 5.67x10(-8) m(2) s(-1). The breakthrough solution method of Gaussian pressure transients is placed in the context of past and present modeling approaches for shale plays developed with multi-fractured wells.
      原文链接:
    • NSTL
    • Elsevier

    A generalized machine learning workflow to visualize mechanical discontinuity

    Liu, RuiMisra, Siddharth
    14页
    查看更多>>摘要：Accurate detection and mapping of mechanical discontinuity in materials has widespread industrial and research applications. We developed a generalized machine-learning framework for visualizing single mechanical discontinuity embedded in material of any composition, velocity, density, porosity, and size with limited data. The proposed visualization of discontinuity requires accurate estimations of the length, location, and orientation of the embedded discontinuity by processing multipoint wave-transmission measurements. k-Wave simulator is used to create a large dataset of elastic waveforms recorded during multi-point wave-transmission measurements through materials containing single mechanical discontinuity. k-Wave simulator considers the wave attenuation, dispersion, and mode conversion in wave motion. Discrete wavelet transform (DWT) and statistical feature extraction are essential for data preprocessing prior to the data-driven model development. DWT also minimizes the effect of noise. Using hyper-parameter tuning and cross validation, gradient boosting regression can visualize the mechanical discontinuity with an accuracy of 0.85, in terms of coefficient of determination. A double-layered neural network-based regression has better performance with an accuracy of 0.95. Use of convolutional neural network converts the predictive task from a waveform processing to an image processing problem. Convolutional neural network achieved a generalization performance of 0.91. The proposed generalized workflow requires robust simulation of wave propagation, signal processing, feature engineering, and model evaluation. Sensors closest to the source and those located opposite the source are the most significant for the desired visualization. Notably, the sensors closest to the source capture the non-linear associations, whereas the sensor on the border opposite to the source capture the linear associations between the measured waveforms and the properties of the mechanical discontinuity.
      原文链接:
    • NSTL
    • Elsevier

    A hybrid partial least squares regression-based real time pore pressure estimation method for complex geological drilling process

    Chen, XiCao, WeihuaGan, ChaoWu, Min...
    13页
    查看更多>>摘要：Accurate real-time estimation of pore pressure is essential for the geomechanical analysis of wellbore stability. Conventional empirical methods may find it difficult to capture pore pressure trends, especially in the complex geological environments. In this study, a data-driven pore pressure estimation method is developed on the basis of hybrid partial least squares regression. This method, which combines empirical methods, comprised three stages: data preprocessing, depth series segmentation, and model establishment and switching. First, concerning the existence of outliers and noises, an outlier detection and wavelet filtering algorithm are introduced to obtain reliable model parameters. Additionally, Pearson correlation-analysis is employed to determine strongly correlated attributes with pore pressure in the data preprocessing stage. Afterward, an online principal component analysis similarity method is proposed for depth series segmentation, considering the varying drilling depth. Finally, a real-time data-driven pore pressure estimation model that integrates conventional empirical methods is established on the basis of partial least squares regression, and a model switching strategy is further developed and will be activated when performance deteriorates. The proposed method can be applied to a wide range of formations, and a real case study is conducted using actual data from a drilling site in Utah. The mean absolute error and root mean square error of the proposed method achieve 0.5128 and 0.8056 in the online condition, and achieved 1.4592 and 2.0100 in the offline condition, which are at least 45% less than those of other nine well-known methods. The results indicate the superior performance of our method on this well.
      原文链接:
    • NSTL
    • Elsevier

    Biopolymeric formulations for filtrate control applications in water-based drilling muds: A review

    Ali, ImtiazAhmad, MaqsoodGanat, Tarek
    15页
    查看更多>>摘要：The forthcoming future of environmental protection mandates the utilization of naturally abundant, biodegradable, sustainable and ecofriendly materials for a wide variety of applications. Fluid loss behavior is considered the most severe problem in oil and gas well drilling operations. Because several other issues are associated with it. As a working way out, viscosifiers and fluid loss additives are introduced to the mud for rheology and filtration characteristics improvements, respectively. Polymers and starches are commonly added to base fluid to increase viscosity and reduce fluid loss of a mud. In this paper, the utilization of biopolymers used in the drilling fluid industry for filtrate reduction has been addressed. This review further emphasizes on the recent developments in native and modified starches utilization in drilling fluids extracted from various sources and the present research gaps for future developments. The utilization of biopolymers as potential additive in nondamaging water-based muds have been addressed to reduce the impacts of mud filtrate in the exposed formations. Moreover, various factors that influence the effectiveness of biopolymers and the utilization of such polymers in different muds are also discussed. The filtration characteristics in terms of filtrate volume and filtercake thickness generally showed improvements by using biopolymers. Filtercakes generated from starchcontaining muds have been found to be thinner and more compact, resulting in reduced formation damage due to lower mud particle penetration.
      原文链接:
    • NSTL
    • Elsevier

    Effect of temporary plugging agent concentration and fracturing fluid infiltration on initiation and propagation of hydraulic fractures in analogue tight sandstones

    Zhang, YinYu, RangangYang, WendongTian, Yong...
    15页
    查看更多>>摘要：Temporary plugging agent (TP) fracturing has been widely used in many cases as an efficient technology to improve well production performance. In particular, the initiation and propagation of hydraulic fractures are vital to the evaluation of fracturing effect. Hence, the research of its influencing factors and laws is crucial for successful design of fracturing operation. As a productive research method, TP fracturing laboratory experiments have been broadly applied by innumerable scientists. Despite of the great achievements, those experiments mainly focus on the plugging ability of TP in unconsolidated and high permeability reservoirs in order to promote initiation and refracturing. However, studies are limited in light of tight low permeability reservoirs, in which TP not only function in plugging but also achieves changing the induced stress field. Especially for tight sandstone reservoirs, TP concentration and fracturing fluid infiltration are key factors affecting the initiation and propagation of hydraulic fractures of tight sandstones, and the laws have not been fully mastered. In this work, we poured artificial analogue rock samples (AARS) according to physical and mechanical parameters of tight sandstone reservoir in Shengli Oilfield, China. And true triaxial TP fracturing experiments under different TP concentrations were carried out on AARS. Aided by nano-organoboron crosslinking agent (NBC) and sleeves, different fracturing fluid infiltrations were achieved with the acoustic emission (AE) system monitoring the initiation and propagation of hydraulic fractures. In addition, the injection pressure curves, the geometries, forms and propagation process of hydraulic fractures were investigated in detail. The results show that: TP accretion, fracturing fluid infiltration and hydraulic fractures generation can produce innumerable AE energy that matches with the fluctuating injection pressure. TP fracturing leads to extension pressure higher than initiation pressure and slow down fracturing rate at relatively low TP concentration. TP concentration is positively correlated with both initiation pressure and average pressurization rate, but negatively correlated with the time for initiation, and such regularity is better reflected in weaker infiltration. 1.2% is the optimal TP concentration to increase initiation pressure and shorten the time for initiation. On the middle cross section of AARS, single-wing fractures, bi-wing fractures and multiple fractures are formed. Inside AARS, the main and branch fractures are formed. The synergy of TP, NBC and sleeves generates a complex fracture system composed of main fractures and branch ones, which reduces the influence of sand on fracture propagation. In short, properly weakening fracturing fluid infiltration by using NBC and sleeves, combined with a reasonable selection of TP concentration, have proved to be a productive way of improving hydraulic fracturing effect of tight sandstone. The findings contribute to a more comprehensive understanding of the initiation and propagation laws of hydraulic fractures of tight sandstone and conduce to the optimization of fracturing parameters.
      原文链接:
    • NSTL
    • Elsevier

    Efficient application of stochastic Discrete Well Affinity (DiWA) proxy model with adjoint gradients for production forecast

    Tian, XiaomingVoskov, Denis
    14页
    查看更多>>摘要：In this paper, we describe adjoint gradient formulation for the Operator-Based Linearization modeling approach. Adjoint gradients are implemented in Delft Advanced Research Terra Simulator (DARTS) framework and applied for history matching using a proxy methodology. Due to the application of adjoint gradients, the computational efficiency of the discrete well affinity (DiWA) proxy model for production forecast is significantly improved. That allows us to derive several important extensions. The proxy methodology is further extended and validated for 3D three-phase black-oil problems. The results show that the gradient-based regression can provide good history matching and reconstruct a true petrophysical characterization when the initial guess is generated based on highly reliable geological information. For cases with a limited or not sufficient geological characterization, an efficient stochastic application of DiWA proxy model is proposed. This approach consists of massive sampling procedures for collecting different realizations based on high-fidelity statistics with filtering. These realizations are generated stochastically because they are not conditioned to any production information but the basic geological statistics of the reservoir. The trained DiWA proxy model demonstrates a small deviation between the model response and the observation data. When applying the refined DiWA model for the training, the error between the model response and observation data can be further reduced. The forecast based on the trained model has slightly larger variability but the deviation is still reasonable. The enhanced DiWA methodology presents an efficient and robust technique for creating an ensemble of stochastic proxy models that can be used in production forecast, flow diagnostic, and optimization.
      原文链接:
    • NSTL
    • Elsevier

    Insights into the pore-scale mechanism of low salinity water injection using a clay-coated micromodel

    Shahmohammadi, BorhanChahardowli, MohammadSimjoo, Mohammad
    14页
    查看更多>>摘要：This study aims to provide new insights into the interactions among an acidic crude-oil, brine with different salinities and clay using flow experiments in montmorillonite-coated micromodels. To this end, a series of oildisplacement experiments are performed in a transparent clay - coated micromodel. In addition, salinityscreening tests, pH and IFT measurements are performed to support the results of flow-experiments. It is shown that during water injection into a clay-coated micromodel, polar components of crude oil partition between oil/water phases and form an emulsified phase. With the 90% reduction in water salinity, the partitioning of crude oil polar components in the aqueous phase is increased. Such partitioning lead to a significant reduction in the pH of the aqueous phase. This observation is supported by an increase in the IFT of oil/brine due to the decrease of crude oil polar components. Salinity screening tests show that there is a critical water salinity, i.e., below the critical point, a large amount of crude oil polar components is partitioned between phases, which can be attributed to the polarization effect. Overall, results show that low salinity water injection benefits from formation of an emulsified phase and wettability alteration to improve oil recovery in the microscale.
      原文链接:
    • NSTL
    • Elsevier