Water flooding flowing area identification for oil reservoirs based on the method of streamline clustering artificial intelligence

Jia, Hu; Deng, Lihui

doi:10.1016/s1876-3804(18)30036-3

Cited by 18 publications

(3 citation statements)

References 18 publications

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“…It is easy to realize the linear normalization method with the powerful matrix operation of MATLAB, but in the transverse comparative analysis of multiple Wells, the difference of normalization results will be caused by the different selection of maximum and minimum values, thus affecting the analysis results. Therefore, data expansion or shift processing is carried out in this paper according to the value situation (Zhou et al, 2019;Jia & Deng, 2018). For example, after analyzing logging and core data, it can be seen that a certain reservoir is located in the second section, which is dominated by grayish-white medium-grain lithic sandstone, and its density (DEN) value is mostly around 2~3 g/cc.…”

Section: Application Research On Reservoir Oil Logging Location Predictionmentioning

confidence: 99%

Application of Artificial Intelligence in Lithology Recognition of Petroleum Logging in Low Permeability Reservoirs

2021

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In low permeability reservoirs, the conversion accuracy of the existing petroleum logging lithology identification method to small pore capillary pressure curve is not high, resulting in a low rock mass identification accuracy. Therefore, artificial intelligence technology is considered in this study to enhance the accuracy of lithology identification in low permeability reservoirs. Firstly, the radar mapping program is used to predict the position of reservoir oil logging, and then the small pore capillary pressure curve is converted by using the conversion method of piecewise power function scale to obtain the pore characteristics of low-permeability reservoir rocks. On this basis, the crossplot method is used to gather the pore characteristic data in well logging and form a plan, and the response parameters of well logging rock mass are obtained to realize the identification and analysis of lithology. The experimental results show that, compared with the existing identification methods, the accuracy of lithology identification in low-permeability reservoir logging is significantly increased after the application of artificial intelligence technology, and the identification process takes less time, which fully proves that the application of artificial intelligence technology is conducive to improving the performance of lithology identification.

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Section: Application Research On Reservoir Oil Logging Location Predictionmentioning

confidence: 99%

Application of Artificial Intelligence in Lithology Recognition of Petroleum Logging in Low Permeability Reservoirs

2021

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“…Another important measure to enhance oil recovery is well pattern adjustment (WPA) (Sayyafzadeh et al 2010;Zhu et al 2018;Guo et al 2019;Wu et al 2020). WPA technology can adjust change streamline distribution and reduce the streamline density in the original main streamline areas, which can improve the sweep efficiency and achieve the purpose of improving development performance (Choudhuri et al 2015;Jia and Deng 2018). A field test of WPA technology has been implemented in WH5-917 and WH7-117 well groups of Shuanghe oilfield.…”

Section: Introductionmentioning

confidence: 99%

Synergistic mechanism of well pattern adjustment and heterogeneous phase combined flooding on enhancing oil recovery in mature fault-block reservoirs

Liu

Chen³

et al. 2022

J Petrol Explor Prod Technol

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With the maturity of fault-block reservoirs, the water percolation channels are formed after long-term waterflooding, which leads to large amounts remaining oil unrecovered and low recovery efficiency. Thus, it is imperative to seek for enhancing oil recovery methods to improve the development performance of mature fault-block reservoirs. Well pattern adjustment and heterogeneous phase combined flooding are both feasible technologies for enhancing oil recovery in mature fault-block reservoirs. Nevertheless, both technologies have their limitations. Thus, a hybrid approach combining WPA and HPCF was proposed. In this study, the large-scale plate sand-pack model flooding experiments were conducted to investigate whether hybrid strategy has better EOR ability than the single WPA or HPCF. Thereafter, on the basis of incremental oil recovery and distribution of remaining oil, the mechanism of the synergistic effect of WPA and HPCF was illustrated. Finally, the influence of reservoir inclination on development performance was proposed. The results show that EOR of hybrid strategy is the highest, followed by single HPCF, and single WPA is the least. The HPCF mainly recovers remaining oil on both sides of main streamline after water flooding, and it prolongs the period of EOR validity. WPA can change the fluid flow direction and force the subsequent liquid enters the un-swept non-main streamline areas in the water flooding stage. Furthermore, by combining WPA and HPCF, the HPCF can enter the non-main streamline areas to expand sweep volume and improve oil displacement efficiency under the induction of WPA. Besides, the reservoir inclination has an obvious influence on the development performance of fault-block reservoir. With the increase of reservoir inclination, the incremental oil recovery of the single strategy or hybrid strategy decreases. Thus, these findings of this study can help for better understanding the synergetic effect of HPCF and WPA, which can provide a hybrid strategy for enhancing oil recovery in mature fault-block reservoir.

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“…It can promote water flooding while causing the injection water to flow around the heterogeneous reservoirs, which leads to the low swept efficiency of injected water and the formation of the aggregated remaining oil . Fixed seepage channels formed after long-term water injection in low-permeability reservoirs not only will cause ineffective circulation of injected water between injection and production wells, but also will make it difficult to recover the remaining oil in areas where the injection water cannot be affected. , The difference in components of the interfacial tension as the resistance counteract the partial shear driving force leading to the increase of capillary number and formation of wall-type oil droplet in an oil-wet reservoir . The study shows that the oil displacement efficiency is the highest in neutral wetting reservoirs .…”

Section: Introductionmentioning

confidence: 99%

Characterization of Ultrasonic-Induced Wettability Alteration under Subsurface Conditions

et al. 2021

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Understanding and manipulating wettability alterations has tremendous implications in theoretical research and industrial applications. This study proposes a novel idea of applying ultrasonic for wettability alterations and also provides its quantitative characterizations and in-depth analyses. More specifically, with pretreatment of ultrasonic, mechanisms of wettability alteration were characterized from the contact angle measurements, as well as the in-depth analyses from atomic force microscopy (AFM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR). After ultrasonic treatments, the wettability of mineral with low permeability is determined to altered from strong hydrophilic to intermediate wettability. The mechanism interpretations are conducted by means of the AFM, XRD, and FTIR. Basically, as the time of ultrasonic treatment increases, the AFM results indicate that the roughness of rock surface and oil/rock interface (contact area) with surroundings of brine is enhanced. Meanwhile, the XRD results show the diffusions of clays from the rock surface to the aqueous phase, and FTIR indicates that the number of functional groups of Si–O–Si, C–O–C, C–O, CO, and OH decreases while the number of COOH and CCO groups increases. This study clearly reveals the surface chemistry of oil-rock wettability alteration in the subsurface conditions, which would provide technical support for subsurface usage of geo-energy productions and carbon sequestrations.

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Water flooding flowing area identification for oil reservoirs based on the method of streamline clustering artificial intelligence

Cited by 18 publications

References 18 publications

Application of Artificial Intelligence in Lithology Recognition of Petroleum Logging in Low Permeability Reservoirs

Application of Artificial Intelligence in Lithology Recognition of Petroleum Logging in Low Permeability Reservoirs

Synergistic mechanism of well pattern adjustment and heterogeneous phase combined flooding on enhancing oil recovery in mature fault-block reservoirs

Characterization of Ultrasonic-Induced Wettability Alteration under Subsurface Conditions

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