Techniques for effective simulation, optimization, and uncertainty quantification of the in-situ upgrading process

Alpak, Faruk O.; Vink, Jeroen C.; Gao, Guohua; Mo, Wenjian

doi:10.1016/j.juogr.2013.09.001

Cited by 39 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…(3) The low-viscosity oil (<10 cP) in the MES shales occupies a considerable proportion under lab conditions, which is beneficial for oil flow in the MES shales. (4) The low-maturity MES shales could be heated underground by using the development of in situ conversion process technology, − which could fortify the hydrocarbon potential and reduce the viscosity to facilitate hydrocarbon flow. (5) The geological conditions of MES shales are similar to those of other shales oil-producing areas.…”

Section: Discussionmentioning

confidence: 99%

Shale Oil Potential and Mobility of Low-Maturity Lacustrine Shales: Implications from NMR Analysis in the Bohai Bay Basin

et al. 2021

View full text Add to dashboard Cite

A vital factor influencing shale oil exploration in lacustrine shale reservoirs is oil mobility, which is closely associated with the shale pore structure and fluid properties, especially for the low-maturity lacustrine shales in China. In this study, the oil mobility and shale oil potential in the Middle Eocene Shahejie Formation lacustrine shales (MES shales) of the Nanpu Sag in the Bohai Bay Basin are evaluated by using nuclear magnetic resonance (NMR) experiments. The low-maturity MES shales have low porosity with NMR porosity ranging from 4.29–7.41%, and the oil saturation ranges from 9.35–36.09%. The pore types are various including intergranular and dissolution pores and fractures. The pore space size spans the range from nano- to microscale, and they are predominantly mesopres. The pore structure for fluid flow is complex and has good self-similarity with high fractal dimensions. The abundant brittle minerals with a relatively high brittleness index value benefit the fracturing of MES shales. Due to the high viscosity and heavy oil in low-maturity shales, bulk relaxation is proposed to analyze the oil properties in this study. The oil viscosity of MES shales mainly ranges from 2 to 70 cP. The movable oil with a viscosity lower than 10 cP accounts for 53.66% of the total oil-filling pore space. For the black mud-shales dominating MES shales, the thermal maturity influences the porosity, viscosity, free hydrocarbon content, and oil saturation in the rocks. Higher thermal maturity would facilitate pore space development with higher porosity, enhance the free hydrocarbon content and oil saturation, and reduce the oil viscosity to some extent. Moreover, MES shales have geological conditions similar to and better brittleness than those of other shale oil producing areas, which further supports the considerable and promising shale oil potential in this formation, especially for deposits located in deeper positions of the Nanpu Sag. The technologies of in situ conversion process and hydraulic fracturing make the resource potential of shale oil in the Nanpu Sag more attractive.

show abstract

Section: Discussionmentioning

confidence: 99%

Shale Oil Potential and Mobility of Low-Maturity Lacustrine Shales: Implications from NMR Analysis in the Bohai Bay Basin

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The CART algorithm has selected R λ 4 − R λ 5 as the best discrimination index. However, such kinds of algorithms are known to be local and unstable [50]. In fact, the proposed decisions tree by the CART is optimal for the used training database, but not unique.…”

Section: The Ensemble-based Classifier Developmentmentioning

confidence: 99%

How Accurate Is an Unmanned Aerial Vehicle Data-Based Model Applied on Satellite Imagery for Chlorophyll-a Estimation in Freshwater Bodies?

et al. 2021

View full text Add to dashboard Cite

Optical sensors are increasingly sought to estimate the amount of chlorophyll a (chl_a) in freshwater bodies. Most, whether empirical or semi-empirical, are data-oriented. Two main limitations are often encountered in the development of such models. The availability of data needed for model calibration, validation, and testing and the locality of the model developed—the majority need a re-parameterization from lake to lake. An Unmanned aerial vehicle (UAV) data-based model for chl_a estimation is developed in this work and tested on Sentinel-2 imagery without any re-parametrization. The Ensemble-based system (EBS) algorithm was used to train the model. The leave-one-out cross validation technique was applied to evaluate the EBS, at a local scale, where results were satisfactory (R2 = Nash = 0.94 and RMSE = 5.6 µg chl_a L−1). A blind database (collected over 89 lakes) was used to challenge the EBS’ Sentine-2-derived chl_a estimates at a regional scale. Results were relatively less good, yet satisfactory (R2 = 0.85, RMSE= 2.4 µg chl_a L−1, and Nash = 0.79). However, the EBS has shown some failure to correctly retrieve chl_a concentration in highly turbid waterbodies. This particularity nonetheless does not affect EBS performance, since turbid waters can easily be pre-recognized and masked before the chl_a modeling.

show abstract

“…1,20,21 In situ conversion can be implemented by electric heating, gas heating, molten salt heating, microwave heating, or combustion heating; 22,23 electric heating is the most mature and popular technique in the industry. 24,25 During the in situ conversion of shale, complex physical reactions cause dynamic changes in reservoir physical properties, 26−30 which can affect reservoir mechanics 31,32 and the fluid flow in fractures, 33,34 change from a seal layer to a permeable layer in which fluids can flow. 35 Comprehensively exploring and quantifying the evolution of the pore structure with increasing pyrolysis temperature are crucial to investigate the hydrocarbon recovery during shale in situ conversion.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Evolution Mechanism of Reservoir Physical Properties during Oil Shale In Situ Conversion

Hou,

Tian,

et al. 2024

Energy Fuels

View full text Add to dashboard Cite

Oil shale in situ conversion is a process where the generated crude oil and the unconverted solid organic matter in immature to lowly mature shales are converted to light oil and gas via artificial heating. The focus of this study was to solve the engineering problems in shale oil production and establish quantitative evaluation models of the dynamic physical properties of reservoirs during shale in situ conversion. Based on thermal pyrolysis experiments, it is concluded that the total organic carbon (TOC) coupled with temperature controls the dynamic reservoir physical properties during shale in situ conversion. After heating, the porosity and permeability can increase 4-fold and 10fold, respectively. The physical properties of the shale reservoir at the same thermal pyrolysis temperature show a good power positive correlation with the TOC. In addition, the permeability anisotropy value showed that the horizontal permeability (K h ) is larger than the vertical permeability (K v ). K h /K v increased as the temperature increased. Furthermore, K h /K v shows a good positive exponential correlation with porosity. The evaluation model of porosity with the TOC and temperature has been established based on the thermal pyrolysis data. There is a good positive correlation between permeability and porosity, and the evaluation model of permeability and K v has been established using porosity. The results provide models for reservoir dynamic physical property prediction during shale in situ conversion. Furthermore, the results provide guidance on shale mechanics anisotropy for furthering fracturing engineering.

show abstract

Techniques for effective simulation, optimization, and uncertainty quantification of the in-situ upgrading process

Cited by 39 publications

References 20 publications

Shale Oil Potential and Mobility of Low-Maturity Lacustrine Shales: Implications from NMR Analysis in the Bohai Bay Basin

Shale Oil Potential and Mobility of Low-Maturity Lacustrine Shales: Implications from NMR Analysis in the Bohai Bay Basin

How Accurate Is an Unmanned Aerial Vehicle Data-Based Model Applied on Satellite Imagery for Chlorophyll-a Estimation in Freshwater Bodies?

Dynamic Evolution Mechanism of Reservoir Physical Properties during Oil Shale In Situ Conversion

Contact Info

Product

Resources

About