2015
DOI: 10.1016/j.orggeochem.2015.07.010
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Is organic pore development in gas shales influenced by the primary porosity and structure of thermally immature organic matter?

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Cited by 312 publications
(149 citation statements)
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“…4b). Three-dimensional reconstruction of the kerogen and porosity distribution shows that the OM pores have great potential to form connected pore networks, where 26–67% of the pore volume can be connected 25 . Valenza et al .…”
Section: Resultsmentioning
confidence: 99%
“…4b). Three-dimensional reconstruction of the kerogen and porosity distribution shows that the OM pores have great potential to form connected pore networks, where 26–67% of the pore volume can be connected 25 . Valenza et al .…”
Section: Resultsmentioning
confidence: 99%
“…In addition to sorption on particle surfaces, petroleum storage in the pores of either 29 organic (Loucks et al, 2009) or inorganic (Han et al, 2015) origin have been documented, as well as natural 30 fractures (Lopatin et al, 2003;Pollastro, 2010). 31 Organic pore development is believed to be largely due to the thermal cracking of kerogen (Jarvie et al,32 2007; Loucks et al, 2009) and/or bitumen (Bernard et al, 2012b), though primary organic pores have been 33 observed within immature organic matter as well (Löhr et al, 2015;Pommer and Milliken, 2015). The ability 34 to predict the porosity evolution of shales as a function of thermal maturation is critical for successful well 35 placement during the production of gas from shale resource plays, yet a comprehensive literature review 36 reveals that the formation of secondary organic pores is only poorly understood.…”
mentioning
confidence: 99%
“…To resolve this issue, Equations (2) and (4) need to be applied in a piecewise fashion, which means using different DCA curves for different production time intervals. The hyperbolic decline function, Equation (4), is applied in the early stage; after the decline rate reaches a certain value, the exponential decline function, Equation (2), is used. This process could be achieved by applying computer programs to determine the switch point, which is the point when the decline rate is smaller than a certain limit (5% is often used).…”
Section: Modified Hyperbolic Decline Modelmentioning
confidence: 99%
“…Note that when β → 1 , Equation (5) is equivalent to Equation (4); when N → ∞ , Equation (5) is equivalent to Equation (2) ( [26]). Another equivalent way to express the modified hyperbolic model was proposed in Seshadri and Mattar [27], where hyperbolic decline in the early life of a well is shifted to exponential decline in the late life by imposing a predetermined decline rate, D * .…”
Section: Modified Hyperbolic Decline Modelmentioning
confidence: 99%
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