Numerical study on determining formation porosity using a boron capture gamma ray technique and MCNP

Liu, Juntao; Zhang, Feng; Wang, Xinguang; Han, Fei; Yuan, Zhelong

doi:10.1016/j.apradiso.2014.08.013

Cited by 14 publications

(3 citation statements)

References 6 publications

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“…Gd 2 O 3 was added to the ceramic proppant. Monte Carlo 84,85 methods were used to establish a logging method If the surface of the proppant is coated with a magnetic material, the characteristics of the fracture can be detected by magnetic field measurement. 87 The key to using this method is improving the temperature and corrosion resistance of the magnetic materials and removing magnetic interference from underground equipment.…”

Section: Coated Proppantmentioning

confidence: 99%

“…Gd 2 O 3 was added to the ceramic proppant. Monte Carlo , methods were used to establish a logging method and formation model, which can be used to estimate proppant location and propped fracture height and has been successfully applied in the field. Duenckel et al proposed a ceramic tracer proppant, which permanently added thermal neutron compounds to the ceramic proppant at a low concentration that would not affect the performance of the ceramic proppant.…”

Section: Coated Proppantmentioning

confidence: 99%

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Review and Perspectives of Coated Proppant Technology

Liu

Huang

et al. 2023

Energy Fuels

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Conventional proppants have the problem of proppant flowback and the inability to fully distribute along long fractures. To solve these problems, coated proppants have emerged and have been successfully used in many oilfields. Polymers are widely used in the petroleum industry, and one of their functions is for proppant coatings. Polymer coatings can change the mechanical properties of the proppant, improve the fracture conductivity of the proppant, and give the proppant other properties, such as self-suspending, low-density, antiflowback, and hydrophobic properties. This paper reviews the polymers and polymer nanocomposites commonly used in proppant coatings, introduces the performance characteristics of various functional proppants, and describes the latest developments regarding coated proppants, which can be of reference for petroleum workers.

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Section: Coated Proppantmentioning

confidence: 99%

Section: Coated Proppantmentioning

confidence: 99%

Review and Perspectives of Coated Proppant Technology

Liu

Huang

et al. 2023

Energy Fuels

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“…Many research papers have demonstrated that academics are interested in utilizing the MCNP algorithm to model X-ray or gamma radiation-using structures [15][16][17][18]. The MCNP code simulation platform was used to mimic the framework suggested in this study [19].…”

Section: Simulation Setupmentioning

confidence: 99%

Application of the Fourier Transform to Improve the Accuracy of Gamma-Based Volume Percentage Detection System Independent of Scale Thickness

Mayet,

Guerrero,

Ijyas

et al. 2023

Separations

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With the passage of time, scale gradually forms inside the oil pipeline. The produced scale, which has a high density, strongly attenuates photons, which lowers the measurement accuracy of three-phase flow meters based on gamma radiation. It is worth mentioning that the need for multiphase flow metering arises when it is necessary or desirable to meter well stream(s) upstream of inlet separation and/or commingling. In this investigation, a novel technique based on artificial intelligence is presented to overcome the issue mentioned earlier. Initially, a detection system was comprised of two NaI detectors and a dual-energy gamma source (241 Am and 133 Ba radioisotopes) using Monte Carlo N particle (MCNP) code. A stratified flow regime with varying volume percentages of oil, water, and gas was modeled inside a pipe that included a scale layer with varying thicknesses. Two detectors record the attenuated photons that could travel through the pipe. Four characteristics with the names of the amplitude of the first and second dominant signal frequencies were extracted from the received signals by both detectors. The aforementioned obtained characteristics were used to train two Radial Basis Function (RBF) neural networks to forecast the volumetric percentages of each component. The RMSE value of the gas and oil prediction neural networks are equal to 0.27 and 0.29, respectively. By measuring two phases of fluids in the pipe, the volume of the third phase can be calculated by subtracting the volume of two phases from the total volume of the pipe. Extraction and introduction of suitable characteristics to determine the volume percentages, reducing the computational burden of the detection system, considering the scale value thickness the pipe, and increasing the accuracy in determining the volume percentages of oil pipes are some of the advantages of the current research, which has increased the usability of the proposed system as a reliable measuring system in the oil and petrochemical industry.

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