On one method of numerical modeling of piezoconductive processes of a two-phase fluid system in a fractured-porous reservoir

A method of numerical modeling based on splitting by physical processes of two-phase fluid transfer in a formation with fractured-porous reservoirs is described. Reservoirs of this type have a natural fracture system and are described by the dual porosity model. A four-block mathematical model of the fluid redistribution between a pore-type matrix and a natural fracturing pattern is proposed and studied. The resulting system is complex and entails a number of difficulties associated with a large number of variables and the absence of important properties of a linearized system of equations, such as self-adjointness and symmetry, which are present in the description of piezoconductive processes. The complete splitting by physical processes is carried out to solve this problem. The resulting split model is differentially equivalent to the discrete initial balance equations of the system (conservation of the mass components of the fluids and the total energy of the system), written in divergent form. This approach is associated with a nonlinear approximation of the grid functions in time, which depends on the fraction of the volume occupied by the fluids in the pores, and is easy to implement.

Constructing Dual-Porosity Models from High-Resolution Discrete-Fracture Models Using Deep Neural Networks

Detailed geological description of fractured reservoirs is typically characterized by the discrete-fracture model (DFM), in which the rock matrix and fractures are explicitly represented in the form of unstructured grids. Its high computation cost makes it infeasible for field-scale applications. Traditional flow-based and static-based methods used to upscale detailed geological DFM to reservoir simulation model suffer from, to some extent, high computation cost and low accuracy, respectively. In this paper, we present a novel deep learning-based upscaling method as an alternative to traditional methods. This work aims to build an image-to-value model based on convolutional neural network to model the nonlinear mapping between the high-resolution image of detailed DFM as input and the upscaled reservoir simulation model as output. The reservoir simulation model (herein refers to the dual-porosity model) includes the predicted fracture-fracture transmissibility linking two adjacent grid blocks and fracture-matrix transmissibility within each coarse block. The proposed upscaling workflow comprises the train-validation samples generation, convolutional neural network training-validating process, and model evaluation. We apply a two-point flux approximation (TPFA) scheme based on embedded discrete-fracture model (EDFM) to generate the datasets. We perform trial-error analysis on the coupling training-validating process to update the ratio of train-validation samples, optimize the learning rate and the network architecture. This process is applied until the trained model obtains an accuracy above 90 % for both train-validation samples. We then demonstrate its performance with the two-phase reference solutions obtained from the fine model in terms of water saturation profile and oil recovery versus PVI. Results show that the DL-based approach provides a good match with the reference solutions for both water saturation distribution and oil recovery curve. This work manifests the value of the DL-based method for the upscaling of detailed DFM to the dual-porosity model and can be extended to construct generalized dual-porosity, dual-permeability models or include more complex physics, such as capillary and gravity effects.

A New Insight Into Seawater-Basalt Exchange Reactions Based on Combined δ18O—Δ′17O—87Sr/86Sr Values of Hydrothermal Fluids From the Axial Seamount Volcano, Pacific Ocean

The δ18O values of submarine vent fluids are controlled by seawater-basalt exchange reactions, temperature of exchange, and to a lesser extent, by phase separation. These variations are translated into the δ18O values of submarine hydrothermal fluids between ca. 0 and + 4‰, a range defined by pristine seawater and equilibrium with basalt. Triple oxygen isotope systematics of submarine fluids remains underexplored. Knowing how δ17O and δ18O change simultaneously during seawater-basalt reaction has a potential to improve i) our understanding of sub-seafloor processes and ii) the rock-based reconstructions of ancient seawater. In this paper, we introduce the first combined δ17O-δ18O-87Sr/86Sr dataset measured in fluids collected from several high-temperature smoker- and anhydrite-type vent sites at the Axial Seamount volcano in the eastern Pacific Ocean. This dataset is supplemented by measurements of major, trace element concentrations and pH indicating that the fluids have reacted extensively with basalt. The salinities of these fluids range between 30 and 110% of seawater indicating that phase separation is an important process, potentially affecting their δ18O. The 87Sr/86Sr endmember values range between 0.7033 and 0.7039. The zero-Mg endmember δ18O values span from -0.9 to + 0.8‰, accompanied by the Δ′17O0.528 values ranging from around 0 to −0.04‰. However, the trajectory at individual site varies. The endmember values of fluids from focused vents exhibit moderate isotope shifts in δ′18O up to +0.8‰, and the shifts in Δ′17O are small, about −0.01‰. The diffuse anhydrite-type vent sites produce fluids that are significantly more scattered in δ′18O—Δ′17O space and cannot be explained by simple isothermal seawater-basalt reactions. To explain the observed variations and to provide constraints on more evolved fluids, we compute triple O isotope compositions of fluids using equilibrium calculations of seawater-basalt reaction, including a non-isothermal reaction that exemplifies complex alteration of oceanic crust. Using a Monte-Carlo simulation of the dual-porosity model, we show a range of possible simultaneous triple O and Sr isotope shifts experienced by seawater upon reaction with basalt. We show the possible variability of fluid values, and the causal effects that would normally be undetected with conventional δ18O measurements.

Novel Dual-Tubing Technique to Eliminate the Shut-in Period in CO2 Huff-n-Puff Injection for Heavy Oil Carbonate Reservoirs

Some heavy oil production can be established using conventional methods; however, these methods are often somewhat ineffective with low recovery factors of less than 20%. Carbon dioxide (CO2) huff-n-puff or cyclic CO2 injection is one of the Enhanced oil recovery (EOR) methods that can be used in stimulating aging wells to recover some residual oil. The shut-in stage of this method results in a significant delay in the production time, and hence lower oil recovery. For the first time, in this paper, an attempt is made to overcome this issue by a novel approach, employing dual tubing completions. The aim of this is to increase the oil recovery with the production during soak time. Also, a majority of the remaining heavy oil reservoirs are carbonates, hence the research was focused on the same conditions. Numerical simulation is done using dual-tubing conditions in a dual-porosity model with conventional tubing as a base case. Optimization studies are done for injection rate, injection time, soaking time, production time, and huff-n-puff cycles. The results show that the recovery factor can increase significantly, with no discontinuity in production. Preliminary economic studies for the cases also showed a net increase in profit of 7% (1.3 million Dollars for the case chosen). This demonstrates the feasibility of the proposed method which can be implemented into conventional operations, for a more sustainable economy in the era of low oil prices.

Reactive Transport Modelling applied to Ni laterite ore deposits in New Caledonia : Impact of discrete fractures on Ni mineralization

<p>Laterite nickel-ore formation in New Caledonia is classically assumed to be governed by supergene processes, and downward migration of waters with Ni-enrichment at the basis of the laterite profile. However, Ni-ore distribution's heterogeneity seems to have been favoured by secondary processes controlled by the combined effects of inherited tectonics, geomorphological evolution and hydrologic systems since the primary laterite formation. Fluid flow and mass transfer processes are not purely downward at low-temperature conditions, but can also be related to lateral fluid circulations, and local drainage along damaged zones in the vicinity of faults (Cathelineau et al., 2016a; 2016b; Myagkiy et al., 2019). This study aims to investigate through reactive transport modelling the impact of discrete fracture on the Ni distribution.</p><p><br>We simulate the dissolution of olivine profile where fractures are the main channels of the fluid-flow. Olivine dissolution is assumed to be kinetically controlled whereas the precipitation of secondary weathering products is considered to occur according to local equilibrium. Results from two different numerical approaches are presented and discussed. The first one is based on a 1D dual-porosity model of a vertically oriented column of serpentinized olivine using PhreeqC associated with the llnl.dat thermodynamic database. The second one is a 2D modelling of hydro-chemical processes in fractured porous media based on the coupling of PhreeqC and Comsol Multiphysics through ICP. While the 1D model aims to describe the general trend of the progression of the weathering front and the global mineral redistribution, the 2D model focuses on particular fracture geometry and hotspot moments of the dissolution process to highlight crucial transition and redistribution of the different mineral phases in relation with the spatial distribution of fractures.</p><p><br>In the 1D dual-porosity model, the fractures are modelled as advective cells connected to a diffusive cell containing the main part of olivine. Two different geochemical models are thus designed. The first one describes the fracture and the advective area's geochemical behaviour, while the second one focuses on the matrix in the diffusive area. The 2D model extends the work initiated by Myagkiy et al. (2019) on simple configurations. The fractures are modelled herein as 1D discrete surfaces interacting with a porous matrix of olivine. Different fracture configurations are studied to assess their impact on mineral redistribution.</p><p><br>Results from both modellings are then compared with observed field data from New Caledonia and previous modelling of an olivine profile without fractures (Myagkiy et al., 2017) to validate the models and highlight the differences induced by the fracture network.</p>

Pressure-Transient Performances of Fractured Horizontal Wells in the Compartmentalized Heterogeneous Unconventional Reservoirs

In order to investigate pressure performance of multiple fractured horizontal wells (MFHWs) penetrating heterogeneous unconventional reservoir and avoid the high computational cost of numerical simulation, a semi-analytical model for MFHWs combining Green function solution and boundary element method has been obtained, where the reservoir is divided into different homogeneous substructures and coupled at interface boundaries by plane source function in a closed rectangular parallelepiped. Hydraulic fractures are assumed uniform flux and dual porosity model is used for natural fractures system. Then the model is validated by compared with analytical solution of MFHWs in a homogeneous reservoir and trilinear flow model, which shows that this model can achieve high accuracy even with a small interface discretization number, and it can consider the radial flow around each hydraulic fractures. Finally, the pressure responses with heterogeneous parameters of reservoirs are discussed including heterogeneous permeability, non-uniform block-length and fracture half-length distribution as well as dual porosity parameters like elastic storage ratio and crossflow ratio.