Facies architectural analysis and three-dimensional modeling of Wen79 fault block, Wenliu oilfield, Dongpu depression, China

Liu, L onglong; Zhang, Jinliang; Wang, Ruoshan; Wang, Jinkai; Yu, Jiangtao; Sun, Zhe; Wang, Guangqun; Guo, Jiaqi; Li, Shasha; Zhang, Penghui; Li, Cunlei

doi:10.1007/s12517-016-2749-3

Cited by 11 publications

(9 citation statements)

References 50 publications

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“…The direction of source materials influences the distribution of sedimentary microfacies. 30 The distribution of the clastic structure and the component maturity reflect the transport direction and distance of clastic sediments. In this case, the compositional maturity and heavy minerals of the Zhiluo Formation decrease from southeast to northwest, which indicates that the source materials in the study area mainly came from the northwestern portion of the basin.…”

Section: Results—a Case Study Of the Hongliu Coalmine Ordos Basin Chinamentioning

confidence: 99%

“…A sedimentological analysis method was used to distinguish and divide the sedimentary subfacies and determine the 3D spatial distribution of aquifers. 30 In this study, the core records from 89 boreholes in the Hongliu coalmine were collected. Sedimentary studies were performed using all the borehole data, which included information regarding color, variations in the grain size, and sedimentary bedding.…”

Section: Experimental Section and Computational Methodsmentioning

confidence: 99%

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Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China

Wei

Xia

et al. 2021

ACS Omega

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Accurate and reliable evaluations of potential groundwater areas are of significance in the hydrogeological assessments of coalfields because water inrush disasters may be caused by unclear groundwater potential. A three-dimensional geological model of porosity based on deterministic modeling and a facies-controlled method are used to determine the groundwater potential of the coal measure aquifer. The modeling processes are as follows: based on the interlayer and discontinuity (faults) data extracted from boreholes and geological maps, an integrated sequence framework model is developed. Using the results of sedimentary microfacies identification and the method of deterministic modeling, a sedimentary microfacies model is successfully established. Finally, based on facies-controlled and sequential Gaussian methods, an effective porosity model is established that can predict the groundwater potential. The predicted results show that sandstones sedimented in channel, point bar, and batture environments possess high effective porosity and strong groundwater potential; however, the sandstones sedimented in interdistributary bays, flood plains, and sand sheets possess low effective porosity. Model validation was performed based on the hydrological pumping test data collected from observation boreholes, drainage water inflow data from dewatered boreholes in the tunnel around workface, and the mine water inflow in tunnels and the workfaces. The validation analysis results show that the effective porosity and sedimentary facies were correlated with the actual flux. The predicted results are consistent with the actual flux data, validating the predicted model.

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Section: Results—a Case Study Of the Hongliu Coalmine Ordos Basin Chinamentioning

confidence: 99%

Section: Experimental Section and Computational Methodsmentioning

confidence: 99%

Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China

Wei

Xia

et al. 2021

ACS Omega

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“…One application in reservoir modeling can be found in Liu et al (2016) for stochastic modeling of eight lithofacies in an oilfield. Beucher and Renard (2016) also explained precisely how this methodology is incorporated for digital modeling of geological phenomena.…”

Section: Plurigaussian Simulationmentioning

confidence: 99%

Lithofacies uncertainty modeling in a siliciclastic reservoir setting by incorporating geological contacts and seismic information

Madani

Biranvand²,

Naderi³

et al. 2018

J Petrol Explor Prod Technol

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Deterministic modeling lonely provides a unique boundary layout, depending on the geological interpretation or interpolation from the hard available data. Changing the interpreter's attitude or interpolation parameters leads to displacing the location of these borders. In contrary, probabilistic modeling of geological domains such as lithofacies is a critical aspect to providing information to take proper decision in the case of evaluation of oil reservoirs parameters, that is, applicable for quantification of uncertainty along the boundaries. These stochastic modeling manifests itself dramatically beyond this occasion. Conventional approaches of probabilistic modeling (object and pixel-based) mostly suffers from consideration of contact knowledge on the simulated domains. Plurigaussian simulation algorithm, in contrast, allows reproducing the complex transitions among the lithofacies domains and has found wide acceptance for modeling petroleum reservoirs. Stationary assumption for this framework has implications on the homogeneous characterization of the lithofacies. In this case, the proportion is assumed constant and the covariance function as a typical feature of spatial continuity depends only on the Euclidean distances between two points. But, whenever there exists a heterogeneity phenomenon in the region, this assumption does not urge model to generate the desired variability of the underlying proportion of facies over the domain. Geophysical attributes as a secondary variable in this place, plays an important role for generation of the realistic contact relationship between the simulated categories. In this paper, a hierarchical plurigaussian simulation approach is used to construct multiple realizations of lithofacies by incorporating the acoustic impedance as soft data through an oil reservoir in Iran.

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“…The overall structural model was upscaled into six smaller models for the subdivided zones, and subsequently, 1-D sandstone and mudstone data were discretized into each stratigraphic framework for data analysis. The SIS method was applied to sandstone and mudstone modeling based on variograms generated from lithofacies curves that represent both the horizontal and vertical distributions of proportions for each layer [11,16]. The spherical variogram model was chosen to simulate the range and 3-D spatial frequency of the sandstone and mudstone.…”

Section: Sandstone and Mudstone Modeling For Subdivided Zonesmentioning

confidence: 99%

“…Pyrcz et al designed an event-based and conditioning-flexibility program, ALLUVSIM, especially for fluvial depositional settings [6]. So far, more and more stochastic modeling methods have been created, and they have been applied to many case studies [7][8][9][10][11][12]. For the Sulige gas field, the largest onshore tight gas field, numerous reservoir geological modeling studies using different methods have been published.…”

Section: Introductionmentioning

confidence: 99%

Geostatistical Three-Dimensional Modeling of a Tight Gas Reservoir: A Case Study of Block S6 of the Sulige Gas Field, Ordos Basin, China

2017

Self Cite

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In this study, three-dimensional (3-D) geostatistical models were constructed to quantify distributions of sandstone and mudstone. We propose a new method that employs weight coefficients to balance the sandstone and mudstone data from irregular well patterns during stochastic modeling. This new method begins with classifying well groups according to well distribution patterns; areas with similar well distribution patterns are classified within the same zone. Then, the distributions of sandstone and mudstone for each zone are simulated separately using the sequential indicator simulation (SIS) method, and the relevant variogram parameters for each zone are computed. In this paper, we used block S6 of the Sulige Gas Field in Ordos Basin in China as a case study. We evaluated the quality of each set of parameters through the vacuation checking method; certain wells were removed to generate equiprobable realizations using different seed numbers. Subsequently, the variogram parameters for the entire S6 area were obtained by assigning different weight coefficients to the parameters of each zone. Finally, a quality assessment of the sandstone and mudstone models of the S6 area was conducted using the horizontal wells, which were not involved in the stochastic modeling process. The results show that these variogram parameters, which were calculated using weight coefficients, are reliable.

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Facies architectural analysis and three-dimensional modeling of Wen79 fault block, Wenliu oilfield, Dongpu depression, China

Cited by 11 publications

References 50 publications

Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China

Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China

Lithofacies uncertainty modeling in a siliciclastic reservoir setting by incorporating geological contacts and seismic information

Geostatistical Three-Dimensional Modeling of a Tight Gas Reservoir: A Case Study of Block S6 of the Sulige Gas Field, Ordos Basin, China

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