Petrophysical analysis and hydrocarbon potential of the lower Cretaceous Yageliemu Formation in Yakela gas condensate field, Kuqa Depression of Tarim Basin, China

Hussain, Wakeel; Ali, Nafees; Sadaf, Rakhshanda; Hu, Chuanyu; Nykilla, Edwin E.; Ullah, Arif; Iqbal, Sayed Muhammad; Hussain, Altaf; Hussain, Sadam

doi:10.1016/j.geogeo.2022.100106

Cited by 11 publications

(4 citation statements)

References 34 publications

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“…Conversely, the influence of clay conductivity on the resistivity index was more significant. According to Equation (11), the resistivity index of pure sandstone was independent of the formation water conductivity. Thus, although there was a large temperature difference between the surface and the subsurface, the Archie equation parameters calculated from laboratory experiments could be used for downhole situations.…”

Section: Factors Affecting the Electrical Properties Of Sandstonementioning

confidence: 99%

“…In recent years, scholars have carried out a large number of HPHT rock electrical experiments, developed rock conductivity measurement methods suitable for different HPHT laboratory equipment, and studied the possible factors that may affect rock electrical properties under HPHT conditions. They systematically studied the changes in rock electrical parameters under HPHT conditions, mainly from the aspects of temperature, pressure, mineral composition, water saturation, particle size, and boundary thickness, and conducted in situ measurements of the electrical conductivity of geological materials, such as hornblende gabbro, gabbro, diorite, water-bearing melt basalt, molten andesite, and carbonated melts, under HPHT conditions [5][6][7][8][9][10][11]. In the field of resource exploration, there have been many research results on the influence of pressure and temperature on rock electrical properties through laboratory measurements [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Simulation of Rock Electrical Properties in Deep Reservoirs Based on Digital Rock Technology

et al. 2023

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Deep reservoirs are in a high-pressure and high-temperature (HPHT) environment, while the experimental conditions for rock electrical properties that meet the deep reservoir conditions are harsh and costly. Although digital rock technology can simulate the electrical properties of rocks, it is limited to electrical simulation studies under normal temperature and pressure conditions (NPT), which limits their ability to capture the electrical characteristics of deep hydrocarbon reservoirs. This limitation affects the accuracy of saturation prediction based on resistivity logging. To simulate the rock electrical properties under HPHT conditions, we proposed a low-cost and high-efficiency HPHT digital rock electrical simulation workflow. Firstly, samples from deep formations were CT-scanned and used to construct multi-component digital rocks that reflect the real microstructure of the samples. Then, mathematical morphology was used to simulate the overburden correction under high-pressure conditions, and the changes in the conductivity of formation water and clay minerals at different temperatures were used to simulate the conductivity changes of rock components under high-temperature conditions. To carry out the electrical simulation of digital rock in deep reservoirs, a numerical simulation condition for HPHT in deep layers was established, and the finite element method (FEM) was used. Finally, based on the equivalent changes in the conductivity of different components, the effects of clay minerals and formation water under HPHT conditions on rock electrical properties were studied and applied to predict the water saturation based on well logging data. We found that considering the influence of temperature, salinity, and clay type, the saturation index (n) of the rock depends on the ratio of the clay conductivity to the formation water conductivity. The larger the ratio is, the smaller the value of n. In addition, the average relative error between the predicted water saturation under HPHT conditions and the sealed coring analysis was 6.8%, which proved the accuracy of the proposed method. Overall, this method can effectively simulate the pressure and temperature environment of deep formations, reveal the electrical conductivity mechanisms of rocks under formation pressure and temperature conditions, and has promising prospects for the study of rock physical properties and reservoir evaluation in deep formations.

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Section: Factors Affecting the Electrical Properties Of Sandstonementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulation of Rock Electrical Properties in Deep Reservoirs Based on Digital Rock Technology

et al. 2023

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“…It entails delineation of the geological formation associated with hydrocarbon accumulation in the field, identification of hydrocarbon reservoirs and fluid type, determination of fluid contacts; as well as estimation of effective porosity, water saturation, hydrocarbon saturation, and hydrocarbon volume per unit reservoir volume. The generated information is employed in post-discovery review seismic mapping to locate appraisal wells for ascertaining extent of the penetrated reservoirs and estimating the reserve [1,2,3]. The aim of this project is to qualitatively and quantitatively estimate petrophysical parameters in AA field with a view to accurately determine the hydrocarbon inplace.…”

Section: Introductionmentioning

confidence: 99%

Petrophysical analysis to determine the hydrocarbon prospectivity of sands in AA field, Niger Delta

Adagunodo,

Akinlabi

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Petrophysical analysis is a crucial process in the oil and gas industry. It entails the analysis and interpretation of well logs, fluid samples or core smaples to understand the behaviour of the embedded reservoirs in the subsurface. Three well logs from AA field were provided for this study, but two well data were finally loaded to the workstation due to absence of key well logs (such as gamma ray and density logs) from the third well. The quality control check of the data was done prior to the uploading of data. Delineation of lithologies and identification of hydrocarbon reservoirs were done; the identified reservoirs were correlated across the two wells; and the petrophysical evaluation (such as estimations of shale volume, porosity, permeability and water/hydrocarbon saturation) of the three pay zones (that is, Sand A, B and C) in AA field were done. The porosity of Sands A, B and C varied from 0.27 to 0.28, 0.24 to 0.30 and 0.27. The permeability of Sands A, B and C varied from 1012 to 1314 md, 884 to 1013 md and 692 to 892 md. Meanwhile, the hydrocarbon saturation for Sands A, B and C varied from 1 to 89%, 45 to 80% and 79 to 80%, respectively. It can be concluded that the order of hydrocarbon prospectivity of the reservoir sands correlated across Well AA-1 and Well AA-2 is Sand C > Sand B > Sand A.

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“…While the Tarim Basin is rich in oil and natural gas reserves [ 1 , 2 , 3 ], its role in China’s energy structure continues to grow and expand. Most of the wells are ultra-deep wells [ 4 , 5 ], and the lithology varies greatly from top to bottom in the Keshen block [ 6 ]. Some stratum fractures developed under the action of the complex pressure system [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

A Nano-Cleaning Fluid for Downhole Casing Cleaning

Song

Zhang

et al. 2023

Polymers

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In drilling and completion projects, sludge is formed as a byproduct when barite and oil are mixed, and later sticks to the casing. This phenomenon has caused a delay in drilling progress, and increased exploration and development costs. Since nano-emulsions have low interfacial surface tension, wetting, and reversal capabilities, this study used nano-emulsions with a particle size of about 14 nm to prepare a cleaning fluid system. This system enhances stability through the network structure in the fiber-reinforced system, and prepares a set of nano-cleaning fluids with adjustable density for ultra-deep wells. The effective viscosity of the nano-cleaning fluid reaches 11 mPa·s, and the system is stable for up to 8 h. In addition, this research independently developed an indoor evaluation instrument. Based on on-site parameters, the performance of the nano-cleaning fluid was evaluated from multiple angles by heating to 150 °C and pressurizing to 3.0 Mpa to simulate downhole temperature and pressure. The evaluation results show that the viscosity and shear value of the nano-cleaning fluid system is greatly affected by the fiber content, and the cleaning efficiency is greatly affected by the concentration of the nano-emulsion. Curve fitting shows that the average processing efficiency could reach 60–85% within 25 min and the cleaning efficiency has a linear relationship with time. The cleaning efficiency has a linear relationship with time, where R2 = 0.98335. The nano-cleaning fluid enables the deconstruction and carrying of the sludge attached to the well wall, which accomplishes the purpose of downhole cleaning.

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Petrophysical analysis and hydrocarbon potential of the lower Cretaceous Yageliemu Formation in Yakela gas condensate field, Kuqa Depression of Tarim Basin, China

Cited by 11 publications

References 34 publications

Simulation of Rock Electrical Properties in Deep Reservoirs Based on Digital Rock Technology

Simulation of Rock Electrical Properties in Deep Reservoirs Based on Digital Rock Technology

Petrophysical analysis to determine the hydrocarbon prospectivity of sands in AA field, Niger Delta

A Nano-Cleaning Fluid for Downhole Casing Cleaning

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