scholarly journals Tracking time with ricequakes in partially soaked brittle porous media

2018 ◽  
Vol 4 (10) ◽  
pp. eaat6961 ◽  
Author(s):  
Itai Einav ◽  
François Guillard
Keyword(s):  
Porous Media ◽  
Delay Time ◽  
Constant Pressure ◽  
Ice Shelves ◽  
Puffed Rice ◽  
Tracking Time ◽  
Chemomechanical Model

When brittle porous media interact with chemically active fluids, they may suddenly crumble. This has reportedly triggered the collapse of rockfill dams, sinkholes, and ice shelves. To study this problem, we use a surrogate experiment for the effect of fluid on rocks and ice involving a column of puffed rice partially soaked in a reservoir of liquid under constant pressure. We disclose localized crushing collapse in the unsaturated region that produces incremental global compaction and loud audible beats. These “ricequakes” repeat perpetually during the experiments and propagate upward through the material. The delay time between consecutive quakes grows linearly with time and is accompanied by creep motion. All those new observations can be explained using a simple chemomechanical model of capillary-driven crushing steps progressing through the micropores.

Wellbore Storage and Skin Effects During the Transient Flow of Non-Newtonian Power-Law Fluids in Porous Media

1980 ◽  
Vol 20 (01) ◽  
pp. 25-38 ◽  
Author(s):  
Chi U. Ikoku ◽  
Henry J. Ramey
Keyword(s):  
Porous Media ◽  
Power Law ◽  
Transient Flow ◽  
Constant Pressure ◽  
Outer Boundary ◽  
Petroleum Reservoirs ◽  
Storage Effect ◽  
Well Test ◽  
Wellbore Storage ◽  
Power Law Fluids

Abstract A model recently presented by Ikoku and Ramey for non-Newtonian power-law flow in porous media was extended to flow in finite circular reservoirs. A constant flow rate was stipulated at the wellbore, and two boundary conditions were considered: no-flow outer boundary and constant-pressure outer boundary. The results were used to derive a new expression for the stabilization time for power-law flow in porous media.Wellbore storage and skin effects always distort the transient pressure behavior of wells in petroleum reservoirs. It is important to investigate the consequences of these phenomena and be able to interpret real well test information. This paper considers the effects of skin and wellbore storage on the transient flow of non-Newtonian power-law fluids in petroleum reservoirs. petroleum reservoirs. A new numerical wellbore storage simulator was used to study the effects of skin and wellbore storage during the transient flow of power-law fluids in infinitely large and finite circular reservoirs. Results are presented both in tabular form and as log-log graphs of dimensionless pressures vs dimensionless times. The log-log graphs may be used in a type-Curve matching procedure to analyze short-time well test data.The early period is dominated by wellbore storage effect. A new expression was obtained for the duration of wellbore storage effect when skin exists for infinitely large reservoirs. This criterion is not valid for finite circular reservoirs with no-flow outer boundary or constant-pressure outer boundary. Results indicate that there is no apparent end of wellbore storage effect for the no-flow outer boundary condition for the values of external radius presented. New relationships were derived for skin presented. New relationships were derived for skin factor and "effective well radius" for power-law flow. Introduction Many papers in the petroleum engineering, chemical engineering, and rheology literature have addressed the subject of non-Newtonian flow in porous media. These studies have represented non-Newtonian flow with power-law models. Most of the results are similar. The main differences in the final expressions lie in the type of power-law model used.In the basic papers on the transient flow of non-Newtonian power-law fluids in porous media, wellbore storage effect was not considered. Ikoku and Ramey and Odeh and Yang presented techniques for calculating the skin factor from injection well test data. However, wellbore storage and skin effects always distort the transient pressure behavior of wells in petroleum reservoirs. It is important to investigate the consequences of these phenomena to be able to interpret real well test information properly.The flow geometries of interest to petroleum engineers in well test analysis usually involve bounded reservoirs. In most cases, a constant flow rate is stipulated at the well along with one of these outer boundary conditions: no flow across the outer boundary, or constant pressure at the outer boundary. Reservoirs with rectangular and other polygonal shapes often are encountered. Transient polygonal shapes often are encountered. Transient pressure behavior for these shapes may be obtained pressure behavior for these shapes may be obtained by applying the principle of superposition in space to the solutions of the infinitely large reservoir cases.In this paper we seek solutions for constant-rate injection into finite circular reservoirs with no-flow and constant-pressure outer boundaries. SPEJ P. 25

Physics Inspired Machine Learning for Solving Fluid Flow in Porous Media: A Novel Computational Algorithm for Reservoir Simulation

2021 ◽  
Author(s):  
Chico Sambo ◽  
Yin Feng
Keyword(s):  
Machine Learning ◽  
Porous Media ◽  
Fluid Flow ◽  
Boundary Conditions ◽  
Constant Pressure ◽  
Flow In Porous Media ◽  
Reservoir Engineering ◽  
Flow Boundary ◽  
Pressure Boundary Conditions ◽  
Source And Sink

Abstract The Physics Inspired Machine Learning (PIML) is emerging as a viable numerical method to solve partial differential equations (PDEs). Recently, the method has been successfully tested and validated to find solutions to both linear and non-linear PDEs. To our knowledge, no prior studies have examined the PIML method in terms of their reliability and capability to handle reservoir engineering boundary conditions, fractures, source and sink terms. Here we explored the potential of PIML for modelling 2D single phase, incompressible, and steady state fluid flow in porous media. The main idea of PIML approaches is to encode the underlying physical law (governing equations, boundary, source and sink constraints) into the deep neural network as prior information. The capability of the PIML method in handling reservoir engineering boundary including no-flow, constant pressure, and mixed reservoir boundary conditions is investigated. The results show that the PIML performs well, giving good results comparable to analytical solution. Further, we examined the potential of PIML approach in handling fluxes (sink and source terms). Our results demonstrate that the PIML fail to provide acceptable prediction for no-flow boundary conditions. However, it provides acceptable predictions for constant pressure boundary conditions. We also assessed the capability of the PIML method in handling fractures. The results indicate that the PIML can provide accurate predictions for parallel fractures subjected to no-flow boundary. However, in complex fractures scenario its accuracy is limited to constant pressure boundary conditions. We also found that mixed and adaptive activation functions improve the performance of PIML for modeling complex fractures and fluxes.

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