The diagnostic criteria of borehole electrical imaging log for volcanic reservoir interpretation: An example from the Yingcheng Formation in the Xujiaweizi Depression, Songliao Basin, China

Nian, Tao; Wang, Guiwen; Cang, Dan; Tan, Chengqian; Tan, Yuhan; Zhang, Fengsheng

doi:10.1016/j.petrol.2021.109713

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…With the increasing drilling depth, the difficulty of drilling gradually rises due to complex geological conditions, the traditional mechanical drilling methods show the characteristics of high energy consumption, low efficiency, long period, and high cost, especially in the deep volcanic rock drilling process. Through the field data analysis, it is found that during the deep volcanic rock [1][2][3][4], drilling process, the mechanical drilling speed shows a significant downward trend with the increase of the abrasive property of strata. For example, the formation compaction degree is high, the rock drillability is low, the abrasiveness is high, the average drillability extreme value is more than 8 grade, and the mechanical drilling speed in deep formation is only 1/4~1/10 of that in upper and middle stratainXushen block of Songliao Basin.…”

Section: Introductionmentioning

confidence: 99%

High Voltage Electric Pulse Drilling: A Study of Variables through Simulation and Experimental Tests

Wang

Pan

et al. 2023

Energies

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With the deepening of drilling depth, the difficulty of drilling engineering increases gradually due to the complex geological conditions. The traditional mechanical drilling method shows the problems of high energy consumption, low efficiency, long cycle and high cost. Because of the characteristics of rock, the high abrasiveness of rock causes great wear to the bit, which becomes an important factor affecting the drilling rate. High voltage electric pulse (Abbreviated as HVEP later in this paper) drilling technology is a new technology developed in the past several decades. The technology uses plasma channel, water jet or shock wave generated by high voltage electric pulse discharge to break rock. It has the characteristics of environmental protection, directional breaking, easy control of rock breaking process and fast speed in the face of complex hard rock. In this paper, the mechanism and technology of rock breaking by high voltage electric pulse method in deep drilling are studied, and the functional test is carried out.

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Section: Introductionmentioning

confidence: 99%

High Voltage Electric Pulse Drilling: A Study of Variables through Simulation and Experimental Tests

Wang

Pan

et al. 2023

Energies

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“…Recently, China found volcanic oil and gas reservoirs in Songliao, the Junggar, Sichuan, Liaohe, and many other basins which have great exploration prospects [1][2][3][4]. In recent years, significant progress has been made in the study of volcanic rock reservoirs, particularly in the identification of lithology and lithofacies, as well as their control effect on reservoirs [5][6][7][8]. Furthermore, analyses have been performed on the genetic relationship between pore evolution and the reservoir space, microscopic pore structures, the influences of alteration and diagenesis, and reservoir formation mechanisms [9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Study on the Reservoir Heterogeneity of Different Volcanic Facies Based on Electrical Imaging Log in the Liaohe Eastern Sag

Liu

Wu²,

Zhang

et al. 2023

Processes

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The volcanic rocks of the Es3 Formation (the third member of the Eocene Shahejie) in the Liaohe Eastern Sag can be divided into four facies and twelve subfacies. The porosity spectrum, porosity bin, variation coefficient (VC), and porosity width derived from electrical imaging log data were applied to study and characterize the heterogeneity of four facies and nine subfacies, both qualitatively and quantitatively. However, the VC and porosity width cannot be used to quantitatively classify heterogeneity when the VC is small and the porosity width is large. In the present study, the authors propose a new parameter, Pvcd = variation coefficient × porosity width. Based on this parameter, using a combination of porosity spectra, porosity bin features, VC, and porosity width, lithofacies heterogeneity is divided into three categories. The first is weak heterogeneity, which has a Pvcd < 1.1, a VC < 0.15, and a porosity width < 6. The second is moderate heterogeneity, which has a Pvcd 1.1–1.6, a VC 0.15–0.25, and a porosity width 6–9. The third is strong heterogeneity, which has a Pvcd > 1.6, a porosity VC > 0.25, and a porosity width > 9. In these three cases, the porosity spectra mainly display unimodal features, the porosity bins are concentrated, the bimodal features with tails and porosity bins are less concentrated, or the multimodal features with tails and porosity bins are scattered, respectively. Favorable reservoirs of volcanic rocks are controlled by lithofacies. In the study area, the favorable reservoirs appear to be the diatreme subfacies with low or medium heterogeneity, the pyroclastic flow subfacies with low heterogeneity, the compound lava flow subfacies with low or medium heterogeneity, and the outer zone subfacies with strong heterogeneity.

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“…For example, Pan et al, 2019a established a local fracture network model of a limestone mine using outcrop fracture measurements obtained using non-contact measurement techniques (such as 3D laser scanning and photometry). For deep reservoirs, image logging can be used to identify fractures more accurately and can provide important parameters such as the linear fracture density, direction, and pore diameter (Ozkaya, 2021;Nian et al, 2022). Tang et al (2020) obtained statistics of the distribution characteristics of image logging fractures and gained a better understanding of the fractures in the Wumishan geothermal reservoir in the Jixian system in the Xiong'an new area.…”

Section: Introductionmentioning

confidence: 99%

Fracture Characteristics and Reservoir Inhomogeneity Prediction of the Gaoyuzhuang Formation in the Xiong’an New Area: Insights From a 3D Discrete Fracture Network Model

Yue

Wang

et al. 2022

Front. Earth Sci.

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The Xiong’an new area in northern China is rich in geothermal resources. The Gaoyuzhuang Formation in the Proterozoic Jixian system is an important recently discovered geothermal reservoir. The Gaoyuzhuang reservoir has been affected by multiple stages of tectonic movement. The fractures are very well developed, resulting in strong heterogeneity in the reservoir’s porosity and permeability. Few studies have been conducted on the fractures and heterogeneity of the Gaoyuzhuang reservoir. In this study, interpretation of data from image logs was used to summarize the characteristics of the fractures, including the fractures’ strikes, dips, and lengths. The permeability distribution of the reservoir in the vicinity of the borehole was predicted. The hydro-thermal (TH) coupling model was used to reproduce the process of pumping tests, and the simulation results were found to be in good agreement with the field test data. In addition, the relationship between the fracture aperture and length was obtained, dmax=4.2×10−5⋅L0.5. The results of this study provide data and technical support for further reservoir research and evaluation of the geothermal resources of the Gaoyuzhuang reservoir.

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The diagnostic criteria of borehole electrical imaging log for volcanic reservoir interpretation: An example from the Yingcheng Formation in the Xujiaweizi Depression, Songliao Basin, China

Cited by 8 publications

References 19 publications

High Voltage Electric Pulse Drilling: A Study of Variables through Simulation and Experimental Tests

High Voltage Electric Pulse Drilling: A Study of Variables through Simulation and Experimental Tests

Study on the Reservoir Heterogeneity of Different Volcanic Facies Based on Electrical Imaging Log in the Liaohe Eastern Sag

Fracture Characteristics and Reservoir Inhomogeneity Prediction of the Gaoyuzhuang Formation in the Xiong’an New Area: Insights From a 3D Discrete Fracture Network Model

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