PhD Student for Geothermal Energy and Geofluids
Geothermal Energy & Geofluids
Institute of Geophysics
NO F 55
CH-8092 Zurich Switzerland
|Phone||+41 44 6338903|
|Dominique Ballarin Dolfin|
|Phone||+41 44 632 3465|
REFEREED PUBLICATIONS IN JOURNALS
Ahkami, M., A. Parmigiani, P.R. Di Palma, M.O. Saar, and X.-Z. Kong A lattice-Boltzmann study of permeability-porosity relationships and mineral precipitation patterns in fractured porous media Computational Geosciences, 2020. [Download PDF] [View Abstract]Mineral precipitation can drastically alter a reservoir’s ability to transmit mass and energy during various engineering/natural subsurface processes, such as geothermal energy extraction and geological carbon dioxide sequestration. However, it is still challenging to explain the relationships among permeability, porosity, and precipitation patterns in reservoirs, particularly in fracture-dominated reservoirs. Here, we investigate the pore-scale behavior of single-species mineral precipitation reactions in a fractured porous medium, using a phase field lattice-Boltzmann method. Parallel to the main flow direction, the medium is divided into two halves, one with a low-permeability matrix and one with a high-permeability matrix. Each matrix contains one flow-through and one dead-end fracture. A wide range of species diffusivity and reaction rates is explored to cover regimes from advection- to diffusion-dominated, and from transport- to reaction-limited. By employing the ratio of the Damköhler (Da) and the Peclet (Pe) number, four distinct precipitation patterns can be identified, namely (1) no precipitation (Da/Pe < 1), (2) near-inlet clogging (Da/Pe > 100), (3) fracture isolation (1 < Da/Pe < 100 and Pe > 1), and (4) diffusive precipitation (1 < Da/Pe < 100 and Pe < 0.1). Using moment analyses, we discuss in detail the development of the species (i.e., reactant) concentration and mineral precipitation fields for various species transport regimes. Finally, we establish a general relationship among mineral precipitation pattern, porosity, and permeability. Our study provides insights into the feedback loop of fluid flow, species transport, mineral precipitation, pore space geometry changes, and permeability in fractured porous media.
Ahkami, M., T. Roesgen, M.O. Saar, and X.-Z. Kong High-resolution temporo-ensemble PIV to resolve pore-scale flow in 3D-printed fractured porous media Transport in Porous Media, 129/2, pp. 467-483, 2019. [Download PDF] [View Abstract]Fractures are conduits that can enable fast advective transfer of (fluid, solute, reactant, particle, etc.) mass and energy. Such fast transfer can significantly affect pore-scale physico-chemical processes, which can in turn affect macroscopic mass and energy transport characteristics. Here, flooding experiments are conducted in a well-characterized fractured porous medium, manufactured by 3D printing. Given steady-state flow conditions, the micro-structure of the two-dimensional (2D) pore fluid flow field is delineated to resolve fluid velocities on the order of a sub-millimeter per second. We demonstrate the capabilities of a new temporo-ensemble Particle Image Velocimetry (PIV) method by maximizing its spatial resolution, employing in-line illumination. This method is advantageous as it is capable of minimizing the number of pixels, required for velocity determinations, down to one pixel, thereby enabling resolving high spatial resolutions of velocity vectors in a large field of view (FOV). While the main goal of this study is to introduce a novel experimental and velocimetry framework, this new method is then applied to specifically improve the understanding of fluid flow through fractured porous media. Histograms of measured velocities indicate log-normal and Gaussian-type distributions of longitudinal and lateral velocities in fractures, respectively. The magnitudes of fluid velocities in fractures and the flow interactions between fractures and matrices are shown to be influenced by the permeability of the background matrix and the orientation of the fractures.
Katika, K., M. Ahkami, P.L. Fosbol, A.Y. Halim, A. Shapiro, K. Thomsen, I. Xiarchos, and I.L. Fabricius Comparative analysis of experimental methods for quantification of small amounts of oil in water Journal of Petroleum Science and Engineering, 147, pp. 459-467, 2016. [Download PDF] [View Abstract]During core flooding experiments where water is injected into oil bearing core plugs, the produced fluids can be sampled in a fraction collector. When the core approaches residual oil saturation, the produced amount of oil is typically small (can be less than a few microliters) and the quantification of oil is then difficult. In this study, we compare four approaches to determine the volume of the collected oil fraction in core flooding effluents. The four methods are: Image analysis, UV/visible spectroscopy, liquid scintillation counting, and low-field nuclear magnetic resonance (NMR) spectrometry. The procedure followed to determine the oil fraction and a summary of advantages and disadvantages of each method are given. Our results show that all four methods are reproducible with high accuracy. The NMR method was capable of direct quantification of both oil and water fractions, without comparison to a pre-made standard curve. Image analysis, UV/visible spectroscopy, and liquid scintillation counting quantify only the oil fraction by comparing with a pre-made standard curve. The image analysis technique is reliable when more than 0.1 ml oil is present, whereas liquid scintillation counting performs well when less than 0.6 ml oil is present. Both UV/visible spectroscopy and NMR spectrometry produced high accuracy results in the entire studied range (0.006–1.1 ml). In terms of laboratory time, the liquid scintillation counting is the fastest and least user dependent, whereas the NMR spectrometry is the most time consuming.
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Ahkami, M. Smart waterflooding of petroleum reservoirs: verifying the models with experimental data, MSc Thesis, 129 pp., 2015. [View Abstract]Water-flooding is one of the most well-known methods of Enhanced Oil Recovery (EOR). So far, it is widely accepted that a certain percentage of oil (known as residual oil) will remain in the porous media regardless of amounts of injected water. This oil is claimed to be trapped by complicated physical mechanisms (Chatzis et al. 1983). Many EOR methods are claimed to be able to free up residual oils and increase the oil recovery. One of the promising methods is the modification of injection brine composition. Its application was discussed by Yildiz and Morrow 1996 based on the works of Jadhunadan and Morrow 1995. Tang and Morrow 1999 observed an increase in oil recovery in the case of different salinities between injection brine and connate water. Zhang and Morrow 2006 performed flooding experiments with mixed-wet cores and reported an increase in both tertiary and secondary mode, however they indicate that the reservoir rocks show better response than outcrops, Zhang et al. 2007 water flooded two consolidated reservoir cores with cycles of high salinity forma- tion brine of 29.690 ppm, low salinity brine of 1.479 ppm and two concentrations of sodium chloride. They reported that injection of low salinity brine increases both secondary and tertiary recovery, the presence of divalent ions also increases the recovery. The effect of water composition on the oil recovery was also investi- gated within the near well-bore region of a reservoir by Web et al. 2004, they injected 10-15 pore volumes of high salinity brine into the ’volume of interest’ to obtain residual oil saturation, which was followed by the injection of diluted water. The log measurement of saturation showed 25 - 50% reduction in residual oil saturation and certifies the experimental investigations. Yousef et al. 2011 also certified the previous experimental observations and reported the effect of water salinity and ion composition on oil recovery. They tagged it as “Smart Wa- terFlood” which will be used in this work. Smart WaterFlooding EOR will be mentioned as Sw-EOR in this work. The authors reported a change in pressure drop and also a change in effluent’s pH during the Sw-EOR, they also mentioned rock properties, oil properties, ion composition, divalent ions concentration, pres- ence of clay contents and mobile particles, initial wettability, and temperature as the affecting factors on Sw-EOR. The mechanism or mechanisms of the Sw-EOR is not fully understood and have brought a discussion in the literature. Several authors have proposed different chemical and physical mechanisms but none of them have been globally accepted. These contradictions can be due to the varia- tion in experimental materials and procedures as the oil production is affected by complicated chemical and physical interactions of rock/connate water/injecting water/oil. The proposed mechanisms and experimental investigation of Sw-EOR are dis- cussed in chapter 2, it will be discussed in section 2.1.8 and section 2.2.5 that the suggested mechanism can be divided in two main categories, where the former ex- plains the wettability alteration and the later emphasizes the importance of other mechanisms such as increase in sweep efficiency by fine formation and precipita- tion. One upcoming question is whether they have equal weight on the increase in oil recovery or one of the mechanisms overweights the other one. In addition as will be discussed in chapter 2, experimental observations showed an increase in pressure difference and a decrease in residual oil saturation; the former is be- lieved to be an effect of fine formation and the later is explained by wettability alteration of the rock. In this manner, this study is to develop a numerical model- ing of the Sw-EOR with arbitrary number of reactions to represent the mentioned mechanisms. The governing equations and the implicit approach of solving equations is described in chapter 3. Further it is illustrated that one reaction is dedicated to the formation of particles and rock dissolution where ions in the injecting water and formation water participate in a reaction to form particles. Then produced particles precipitate and in this way modify the local porosity of the system. This affects the absolute permeability of the system as well. The reaction is a two way reaction so either precipitation or dissolution can happen in the system based on reaction rates and reactant concentrations. The second reaction is dedicated to wettability alteration, however the numerical modeling of wettability is not easily possible because of its complex concept and algorithm. Wettability alteration is modeled through the decrease in residual oil saturation. The reaction is assumed to happen between an ion in the injecting water and a mineral on the rock surface. Its product changes the rock wettability by decreasing the residual oil saturation. The modification of residual oil saturation results in the change of relative permeability of oil and relative permeability of water as well. Numerical solution of different scenarios are illustrated in chapter 4. Oil re- covery and other determining factors such as saturation and pressure are illustrated to compare the different waterflooding scenarios. The normal water flooding with- out any reaction is brought in section 4.1 while wettability alteration and fine formation are investigated in section 4.2 and section 4.3 respectively. Formation of particles are also divided into three scenarios where injection water compo- sition and reaction rates vary from each other, detailed explanation of each part is brought in section 4.3. Finally a cyclic waterflooding experiment is simulated where five pore volumes of water injection with wettability alteration came after five pore volumes of water injection without any reaction. Numerical results show the potential of wettability alteration to increase oil recovery both in secondary mode and tertiary mode. However its effect on pres- sure gradient is not completely correlated with the wettability modification rate and increase in oil recovery. On the other hand, formation and precipitation in a homogeneous medium such as the one in this study does not contribute to oil recovery. While it increases pressure gradient and this increase is correlated with precipitation rate and amount.