scholarly journals Facies and Petrophysical Modeling of Triassic Chang 6 Tight Sandstone Reservoir, Heshui Oil Field, Ordos Basin, China

Lithosphere ◽  
2021 ◽  
Vol 2021 (Special 1) ◽  
Author(s):  
Khawaja Hasnain Iltaf ◽  
Dali Yue ◽  
Wurong Wang ◽  
Xiaolong Wan ◽  
Shixiang Li ◽  
...  
Keyword(s):  
Indicator Kriging ◽  
Multiple Point ◽  
Low Permeability ◽  
Petrophysical Properties ◽  
Sequential Indicator Simulation ◽  
Tight Sandstone ◽  
Petrophysical Modeling ◽  
Indicator Simulation ◽  
Sandstone Reservoir

Abstract Tight sandstone reservoirs are widely distributed worldwide. The Upper Triassic Chang 6 member of the Yanchang Formation is characterized by low permeability and porosity. The facies model offers a unique approach for understanding the characteristics of various environments also heterogeneity, scale, and control of physical processes. The role of subsurface facies features and petrophysical properties was unclear. Notable insufficient research has been conducted based on facies and petrophysical modeling and that demands to refine the role of reservoir properties. To tackle this problem, a reservoir model is to be estimated using various combinations of property modeling algorithms for discrete (facies) and continuous (petrophysical) properties. Chang 6 member consists of three main facies, i.e., channel, lobe main body, and lobe margin facies. The current research is aimed at comparing the applicability and competitiveness of various facies and petrophysical modeling methods. Further, well-log data was utilized to interpret unique facies and petrophysical models to better understand the reservoir architecture. Methods for facies modeling include indicator kriging, multiple-point geostatistics, surface-based method, and sequential indicator simulation. Overall, the indicator kriging method preserved the local variability and accuracy, but some facies are smoothed out. The surface-based method showed far better results by showing the ability to reproduce the geometry, extent, connectivity, and facies association. The multiple-point geostatistics (MPG) model accurately presented the facies profiles, contacts, geometry, and geomorphological features. Sequential indicator simulation (SIS) honored the facies spatial distribution and input statistical parameters. The porosity model built using sequential Gaussian simulation (SGS) showed low porosity (74% values <2%). Gaussian random function simulation (GRFS) models showed very low average porosity (8%-10%) and low permeability (less than 0.1 mD). These methods indicate that Chang 6 member is a typical unconventional tight sandstone reservoir with ultralow values of petrophysical properties.

Characteristics of Nano-Micro Pore Networks and Petroleum Microscopic Occurrence State in Ultra-Low Permeability (Tight) Sandstone Reservoir

2017 ◽  
Vol 17 (9) ◽  
pp. 6039-6050 ◽  
Author(s):  
Juncheng Qiao ◽  
Jianhui Zeng ◽  
Xiao Feng ◽  
Zhifeng Yang ◽  
Yongchao Zhang ◽  
...  
Keyword(s):  
Low Permeability ◽  
Tight Sandstone ◽  
Pore Networks ◽  
Occurrence State ◽  
Sandstone Reservoir

Assessing spatial distribution and joint uncertainty of TPH-fractions: Indicator kriging and sequential indicator simulation

2007 ◽  
Vol 87 (5) ◽  
pp. 551-563
Author(s):  
Carol Luca ◽  
Bing C Si ◽  
Richard E Farrell
Keyword(s):  
Spatial Distribution ◽  
Petroleum Hydrocarbon ◽  
Indicator Kriging ◽  
Hydrocarbon Contamination ◽  
Contaminated Sites ◽  
Sequential Indicator Simulation ◽  
Maximum Probability ◽  
Dependent Case ◽  
Indicator Simulation ◽  
Independent Case

Petroleum hydrocarbon (PHC) contamination is one of the most common contaminants in soils and remediation of PHC-contaminated sites requires methods for characterizing the spatial distribution of PHC on a site. Few studies have compared the performance of indicator kriging (IK) and sequential indicator simulation (SIS) in site characterization of petroleum-contaminated sites, or the application of these methods given the fraction based guidelines. The objectives of this study were to determine if IK and SIS indicate similar contaminated areas and to examine how the probability of exceeding thresholds changes when multiple fractions are considered simultaneously. An abandoned refinery near Kamsack, Saskatchewan, characterized by clay-textured soils was sampled and analyzed for PHC fractions (F2 and F3). The probability of a location exceeding a fraction’s remediation criteria was determined using IK and SIS. Based on critical probability thresholds, IK indicated a greater area was contaminated by F2 (6.3%) and F3 (0.8%) than SIS (4.5 and 0.6%, respectively). When the remediation criteria for both F2 and F3 were considered simultaneously, “dependent” and “independent” cases were examined. The dependent case assumed perfect correlation and used the maximum probability of either F2 or F3 as the new estimate. The independent case assumed no correlation and evaluated the probability of F2 > 2500 mg kg–1 or F3 > 6600 mg kg–1. The dependent case resulted in a smaller contaminated area than the independent case in both IK and SIS. On this site the differences between the two methods were small, although IK did smooth the distribution. Key words: Sequential indicator simulation, indicator kriging, geostatics, petroleum hydrocarbon contamination, uncertainty

Sequential indicator simulation and indicator kriging estimation of 3-dimensional soil textures

Soil Research ◽  
2009 ◽  
Vol 47 (6) ◽  
pp. 622 ◽  
Author(s):  
Y. He ◽  
D. Chen ◽  
B. G. Li ◽  
Y. F. Huang ◽  
K. L. Hu ◽  
...  
Keyword(s):  
Structural Characteristics ◽  
General Pattern ◽  
Regional Scale ◽  
Vertical Direction ◽  
Absolute Error ◽  
Indicator Kriging ◽  
Soil Profiles ◽  
Sequential Indicator Simulation ◽  
Auto Correlation ◽  
Indicator Simulation

The complex distribution characteristics of soil textures at a large or regional scale are difficult to understand with the current state of knowledge and limited soil profile data. In this study, an indicator variogram was used to describe the spatial structural characteristics of soil textures of 139 soil profiles. The profiles were 2 m deep with sampling intervals of 0.05 m, from an area of 15 km2 in the North China Plain. The ratios of nugget-to-sill values (SH) of experimental variograms of the soil profiles in the vertical direction were equal to 0, showing strong spatial auto-correlation. In contrast, SH ratios of 0.48–0.81 in the horizontal direction, with sampling distances of ~300 m, showed weaker spatial auto-correlation. Sequential indicator simulation (SIS) and indicator kriging (IK) methods were then used to simulate and estimate the 3D spatial distribution of soil textures. The outcomes of the 2 methods were evaluated by the reproduction of the histogram and variogram, and by mean absolute error of predictions. Simulated results conducted on dense and sparse datasets showed that when denser sample data are used, complex patterns of soil textures can be captured and simulated realisations can reproduce variograms with reasonable fluctuations. When data are sparse, a general pattern of major soil textures still can be captured, with minor textures being poorly simulated or estimated. The results also showed that when data are sufficient, the reproduction of the histogram and variogram by SIS was significantly better than by the IK method for the predominant texture (clay). However, when data are sparse, there is little difference between the 2 methods.

Accumulation Mechanism of Ultro-Low Permeability Sandstone Reservoir, Huaqing Oilfield, Ordas Basin

2013 ◽  
Vol 868 ◽  
pp. 66-69
Author(s):  
Hai Yan Hu
Keyword(s):  
Oil And Gas ◽  
Sedimentary Basin ◽  
Ordos Basin ◽  
Low Permeability ◽  
Tight Sandstone ◽  
Buoyant Force ◽  
Accumulation Mechanism ◽  
Oil And Gas Resources ◽  
Porosity And Permeability ◽  
Sandstone Reservoir

Ordos Basin is the second largest sedimentary basin in China with very rich oil and gas resources. The exploration targets are typical reservoirs of low permeability, low pressure and low output. To determine the accumulation mechanism of tight sandstone reservoir, thin section, fluid inclusion, porosity and permeability measurement, numerical calculation were used. The result showed that sandstone became tight while oil filling, buoyant force is too small to overcome the resistance of capillary force. Therefore, overpressure induced by source rock generation is the accumulation drive force.

scholarly journals A reservoir quality evaluation approach for tight sandstone reservoirs based on the gray correlation algorithm: A case study of the Chang 6 layer in the W area of the as oilfield, Ordos Basin

2021 ◽  
pp. 014459872199851
Author(s):  
Yuyang Liu ◽  
Xiaowei Zhang ◽  
Junfeng Shi ◽  
Wei Guo ◽  
Lixia Kang ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Ordos Basin ◽  
Reservoir Quality ◽  
Pore Throat ◽  
Tight Sandstone ◽  
Evaluation Approach ◽  
Correlation Algorithm ◽  
Gray Correlation ◽  
Sandstone Reservoir

As an important type of unconventional hydrocarbon, tight sandstone oil has great present and future resource potential. Reservoir quality evaluation is the basis of tight sandstone oil development. A comprehensive evaluation approach based on the gray correlation algorithm is established to effectively assess tight sandstone reservoir quality. Seven tight sandstone samples from the Chang 6 reservoir in the W area of the AS oilfield in the Ordos Basin are employed. First, the petrological and physical characteristics of the study area reservoir are briefly discussed through thin section observations, electron microscopy analysis, core physical property tests, and whole-rock and clay mineral content experiments. Second, the pore type, throat type and pore and throat combination characteristics are described from casting thin sections and scanning electron microscopy. Third, high-pressure mercury injection and nitrogen adsorption experiments are optimized to evaluate the characteristic parameters of pore throat distribution, micro- and nanopore throat frequency, permeability contribution and volume continuous distribution characteristics to quantitatively characterize the reservoir micro- and nanopores and throats. Then, the effective pore throat frequency specific gravity parameter of movable oil and the irreducible oil pore throat volume specific gravity parameter are introduced and combined with the reservoir physical properties, multipoint Brunauer-Emmett-Teller (BET) specific surface area, displacement pressure, maximum mercury saturation and mercury withdrawal efficiency parameters as the basic parameters for evaluation of tight sandstone reservoir quality. Finally, the weight coefficient of each parameter is calculated by the gray correlation method, and a reservoir comprehensive evaluation indicator (RCEI) is designed. The results show that the study area is dominated by types II and III tight sandstone reservoirs. In addition, the research method in this paper can be further extended to the evaluation of shale gas and other unconventional reservoirs after appropriate modification.

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