Research progress and prospect of Ordovician carbonate rocks in Tahe oilfield: karst feature

Xu, Xinyu; Chen, Qinghua; Yinguo, Zhang; Wang, Jing; Yang, Li; Kang, Zhi‐Hui; Wei, Hehua; Zhang, Yun

doi:10.1007/s13202-021-01268-1

Cited by 7 publications

(3 citation statements)

References 24 publications

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“…The reservoir zone is dominated by karst caves and large fractures, in which the caves are large in scale and have various connectivity forms, complex spatial distribution, and strong heterogeneity (for geological information, please refer to Figure 2 in [10]). After long-term, water-driving exploitation, the fractured-vuggy reservoirs have issues with low response and low recovery degrees [11,12]. Consequently, it is urgent to expand the water-driving-related volume of fractured-vuggy reservoirs and improve the oil recovery efficiency of fracturedvuggy reservoirs.…”

Section: Introductionmentioning

confidence: 99%

CFD−DEM Simulation of a Jamming Mechanism and Influencing Factors of a Fracture-Shrinking Model

Zhang,

Lu,

Zhang

et al. 2024

Processes

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Fractured-vuggy reservoirs are crucial for increasing unconventional oil storage and production, but the controlling mechanism of this dominant flow channel remains vague, and the jamming mechanism of modulator particles is unclear. This study explores the filling and jamming processes of particles in the fractures by conducting a computational fluid dynamics−discrete element method (CFD−DEM) coupled simulation, considering the variation of fracture width, fluid velocity, particle size, and concentration. Results suggest that four sealing modes are proposed: normal filling, local jamming, complete sealing, and sealing in the main fracture. The ratio of particle size to the main fracture width exerts the primary role, with the ratio having a range of 0.625 < D/W ≤ 0.77 revealing complete jamming. Furthermore, an optimal particle size for achieving stable sealing is observed when the particle size varies from 2 to 2.5 mm. A higher concentration of particles yields better results in the fracture-shrinking model. Conversely, a greater velocity worsens the sealing effect on fractures. This research can offer technical support for the large-scale dissemination of flow regulation technology.

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Section: Introductionmentioning

confidence: 99%

CFD−DEM Simulation of a Jamming Mechanism and Influencing Factors of a Fracture-Shrinking Model

Zhang,

Lu,

Zhang

et al. 2024

Processes

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“…The Tahe Oilfield, located at the axis of Akekule uplift, Tarim Basin, is a typical fractured-vuggy carbonate reservoir with 9.35 × 108 t of oil and gas reserves [18]. The Tahe Oilfield is mainly composed of Ordovician carbonate fractured-vuggy reservoirs, with oil and gas resources mainly accumulated in caverns and fractures of different sizes [13,19]. The reservoir bodies have different types and in the Yingmai 32-7 plot in the Talimu Oilfield, Xu et al [35,36] divided water breakthrough into slow ascending, benched ascending, and rapid ascending.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Water Invasion Mode and Remaining Oil Utilization Rules of Fractured-Vuggy Reservoirs: A Case Study of the Intersection Region of S99 Unit in Tahe Oilfield

et al. 2023

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Fractured-vuggy reservoirs are a new target in carbonate oil and gas exploration and development. Because of well-developed reservoir bodies, including fractures and caverns, bottom water invasion can be observed in oilfield development, with low utilization efficiency of crude oil in the reservoir. Accordingly, this study focused on the intersection region of the S99 unit of the Tahe fractured-vuggy reservoirs. Based on seismic data, the reservoir bodies can be divided into three types—caverns, fractures, and broken solution pores. Using the same location condition assignment algorithm, four single-type models are fused into a multi-scale discrete three-dimensional geological model of fractured and cavernous reservoirs, and the corresponding fractured-vuggy reservoir model was established for numerical simulation. The single-well historical fitting precision exceeded 85%. Furthermore, the development can be divided into four stages—initial stage of production, peak production stage, liquid control and oil stabilization stage, and scale gas injection stable. Streamlining sweep analysis determined the utilization and distribution characteristics of the remaining oil in the reservoir. It can be concluded that structure, caverns, and fractures were the main controlling factors affecting the remaining oil distribution in the fractured-vuggy reservoir. The fluid exchange among single-well reserve zones was calculated using streamline-based quantitative sweep analysis and interwell flow quantitative analysis method. Through source-sink quantitative analysis, interwell flow relations were derived, and three water breakthrough modes were further concluded: violent flooding, slow ascending of water cut, and low cut or intermittent water production.

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“…During the last decades, many hundreds of studies about Tahe karst cave reservoirs have been reported, ranging from structural geology, karstification, reservoir characterization, geomodeling, etc. Xu et al (2021) present a review of these progresses.…”

mentioning

confidence: 99%

GANSim‐3D for Conditional Geomodeling: Theory and Field Application

Song

Mukerji

Zhang

et al. 2022

Water Resources Research

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Geomodeling, or quantitatively predicting the distribution of subsurface reservoirs, is of great significance for evaluation and exploitation of underground water and energy resources as well as for geological sequestration of CO 2 (CCS). Generally, various types of information (data) about the subsurface are incorporated using geostatistical approaches for geomodeling. Such information includes sparse well data, geophysical data, global features (e.g., facies proportion), and spatial geological patterns, among which geological patterns may be the most challenging to incorporate. In traditional geostatistics-based geomodeling approaches, geological patterns can be partially expressed by simple variogram functions (e.g., in the Sequential Indicator Simulation method; Pyrcz & Deutsch, 2014) or local multiple points statistics (MPS) (in MPS-based approaches; Mariethoz & Caers, 2014). Such partial representations may be unable to completely express complicated spatial geological patterns, and thus there is a lack of realism (expected geological patterns) to different extents in the simulated results of these approaches, for example, facies models produced by variogram-based approaches cannot exhibit sinuous channel-like shapes, while MPS-based approaches may produce discontinuous channels. In addition, due to the incompleteness and imperfectness of the incorporated information (e.g., the sparse nature of well data and low-resolution nature of geophysical data), uncertainty exists in geomodeling results, and thus a number of reservoir realizations are generally produced to represent the potential distribution of subsurface reservoirs.Generative Adversarial Networks (GANs) (Goodfellow et al., 2014) in deep learning are effective at capturing complete spatial patterns (structures) of 2D images or 3D objects using a generator Convolutional Neural Network (CNN), with the assistance of another discriminator CNN. With the captured pattern knowledge, the generator CNN can map a random latent vector into a realistic image or a realistic 3D object (e.g., Wu et al., 2016). Text S1 in Supporting Information S1 provides additional details about the basic methodology of GANs.

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Research progress and prospect of Ordovician carbonate rocks in Tahe oilfield: karst feature

Cited by 7 publications

References 24 publications

CFD−DEM Simulation of a Jamming Mechanism and Influencing Factors of a Fracture-Shrinking Model

CFD−DEM Simulation of a Jamming Mechanism and Influencing Factors of a Fracture-Shrinking Model

Investigation on Water Invasion Mode and Remaining Oil Utilization Rules of Fractured-Vuggy Reservoirs: A Case Study of the Intersection Region of S99 Unit in Tahe Oilfield

GANSim‐3D for Conditional Geomodeling: Theory and Field Application

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