Three-Phase Pore-Network Modeling for Reservoirs With Arbitrary Wettability

SPE Journal ◽  
2012 ◽  
Vol 18 (02) ◽  
pp. 285-295 ◽  
Author(s):  
Adnan Al-Dhahli ◽  
Sebastian Geiger ◽  
Marinus I.J. van Dijke
Keyword(s):  
Network Model ◽  
Relative Permeability ◽  
Oil Recovery ◽  
Network Modeling ◽  
Pore Scale ◽  
Residual Oil ◽  
Oil Saturation ◽  
Pore Network Modeling ◽  
Three Phase ◽  
Flow Functions

Summary Oil reservoirs have structural heterogeneities across multiple length scales and, particularly in carbonates, complexly distributed wettabilities. The interplay of structural and wettability heterogeneities is the fundamental control for sweep efficiency and oil recovery. This interplay must be captured in physically robust flow functions, such as relative permeability and capillary pressure functions. Such flow functions then allow us to choose the best improved-oil-recovery (IOR) or enhanced-oil-recovery (EOR) process and forecast oil recovery with adequate precision. Obtaining flow functions for reservoir rocks with varying wettability is a challenging task, especially when three fluid phases coexist. In this work, we use pore-network modeling, a reliable and physically based simulation tool, to predict three-phase flow functions. We have developed a new pore-scale network model for rocks with variable wettability. Unlike other models, this model combines three new and important features. (1) Our network model comprises a novel thermodynamic criterion for the formation and collapse of oil layers. This captures film/layer flow of oil adequately, which affects the oil relative permeability at low oil saturation. We can therefore predict residual oil more accurately. (2) We implemented multiple displacement chains, in which injection of one phase at the inlet triggers a chain of interface displacements throughout the network. This allows us to accurately model the mobilization of disconnected phase clusters that arise during higher-order [water-alternating-gas (WAG)] floods. Again, this feature is key to a better prediction of residual oil saturation (ROS). (3) Our model takes realistic 3D pore networks extracted from pore-space reconstruction methods and X-ray computerized-tomography (CT) images as input. This preserves both topology and pore shape of the rock, providing better estimates of phase conductivities and relative permeability. We have validated our model by use of available experimental data for a range of wettabilities and demonstrated the impact of single vs. multiple displacement on residual oil. We also used a proof-of-concept study in which we use flow functions for different wettabilities that have been computed with our model in field-scale reservoir simulations to forecast oil recovery during tertiary gas injection. These results are compared with predictions that used empirical flow functions. Flow functions computed by our network model gave higher oil recovery than corresponding flow functions calculated by empirical models; oil recovery increases with decreasing water-wetness. This shows that the pore-scale physics encapsulated in our new network model leads to the right emergent behavior at the reservoir scale.

Relationship between Residual Saturations and Wettability using Pore-Network Modeling

2021 ◽  
Author(s):  
Prakash Purswani ◽  
Russell T. Johns ◽  
Zuleima T. Karpyn
Keyword(s):  
Contact Angle ◽  
Oil Recovery ◽  
Network Modeling ◽  
Pore Network ◽  
Residual Oil ◽  
Residual Saturation ◽  
Oil Saturation ◽  
Pore Network Modeling ◽  
Residual Oil Saturation ◽  
Eor Processes

Abstract The relationship between residual saturation and wettability is critical for modeling enhanced oil recovery (EOR) processes. The wetting state of a core is often quantified through Amott indices, which are estimated from the ratio of the saturation fraction that flows spontaneously to the total saturation change that occurs due to spontaneous flow and forced injection. Coreflooding experiments have shown that residual oil saturation trends against wettability indices typically show a minimum around mixed-wet conditions. Amott indices, however, provides an average measure of wettability (contact angle), which are intrinsically dependent on a variety of factors such as the initial oil saturation, aging conditions, etc. Thus, the use of Amott indices could potentially cloud the observed trends of residual saturation with wettability. Using pore network modeling (PNM), we show that residual oil saturation varies monotonically with the contact angle, which is a direct measure of wettability. That is, for fixed initial oil saturation, the residual oil saturation decreases monotonically as the reservoir becomes more water-wet (decreasing contact angle). Further, calculation of Amott indices for the PNM data sets show that a plot of the residual oil saturation versus Amott indices also shows this monotonic trend, but only if the initial oil saturation is kept fixed. Thus, for the cases presented here, we show that there is no minimum residual saturation at mixed-wet conditions as wettability changes. This can have important implications for low salinity waterflooding or other EOR processes where wettability is altered.

scholarly journals Mysteries behind the Low Salinity Water Injection Technique

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Emad Waleed Al-Shalabi ◽  
Kamy Sepehrnoori ◽  
Gary Pope
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
History Matching ◽  
Water Injection ◽  
Residual Oil ◽  
Oil Saturation ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water ◽  
Low Salinity Water Injection

Low salinity water injection (LSWI) is gaining popularity as an improved oil recovery technique in both secondary and tertiary injection modes. The objective of this paper is to investigate the main mechanisms behind the LSWI effect on oil recovery from carbonates through history-matching of a recently published coreflood. This paper includes a description of the seawater cycle match and two proposed methods to history-match the LSWI cycles using the UTCHEM simulator. The sensitivity of residual oil saturation, capillary pressure curve, and relative permeability parameters (endpoints and Corey’s exponents) on LSWI is evaluated in this work. Results showed that wettability alteration is still believed to be the main contributor to the LSWI effect on oil recovery in carbonates through successfully history matching both oil recovery and pressure drop data. Moreover, tuning residual oil saturation and relative permeability parameters including endpoints and exponents is essential for a good data match. Also, the incremental oil recovery obtained by LSWI is mainly controlled by oil relative permeability parameters rather than water relative permeability parameters. The findings of this paper help to gain more insight into this uncertain IOR technique and propose a mechanistic model for oil recovery predictions.

Issue with Stone-II Three Phase Permeability Model, and A Novel Robust Fundamentals-Based Alternative to It

2021 ◽  
Author(s):  
Subodh Gupta
Keyword(s):  
Relative Permeability ◽  
Phase Flow ◽  
Residual Oil ◽  
Relative Permeabilities ◽  
Phase Permeability ◽  
Permeability Model ◽  
Oil Saturation ◽  
Three Phase ◽  
Three Phase Flow ◽  
Relative Permeability Curves

Abstract The objective of this paper is to present a fundamentals-based, consistent with observation, three-phase flow model that avoids the pitfalls of conventional models such as Stone-II or Baker's three-phase permeability models. While investigating the myth of residual oil saturation in SAGD with comparing model generated results against field data, Gupta et al. (2020) highlighted the difficulty in matching observed residual oil saturation in steamed reservoir with Stone-II and Baker's linear models. Though the use of Stone-II model is very popular for three-phase flow across the industry, one issue in the context of gravity drainage is how it appears to counter-intuitively limit the flow of oil when water is present near its irreducible saturation. The current work begins with describing the problem with existing combinatorial methods such as Stone-II, which in turn combine the water-oil, and gas-oil relative permeability curves to yield the oil relative permeability curve in presence of water and gas. Then starting with the fundamentals of laminar flow in capillaries and with successive analogical formulations, it develops expressions that directly yield the relative permeabilities for all three phases. In this it assumes a pore size distribution approximated by functions used earlier in the literature for deriving two-phase relative permeability curves. The outlined approach by-passes the need for having combinatorial functions such as prescribed by Stone or Baker. The model so developed is simple to use, and it avoids the unnatural phenomenon or discrepancy due to a mathematical artefact described in the context of Stone-II above. The model also explains why in the past some researchers have found relative permeability to be a function of temperature. The new model is also amenable to be determined experimentally, instead of being based on an assumed pore-size distribution. In that context it serves as a set of skeletal functions of known dependencies on various saturations, leaving constants to be determined experimentally. The novelty of the work is in development of a three-phase relative permeability model that is based on fundamentals of flow in fine channels and which explains the observed results in the context of flow in porous media better. The significance of the work includes, aside from predicting results more in line with expectations and an explanation of temperature dependent relative permeabilities of oil, a more reliable time dependent residual oleic-phase saturation in the context of gravity-based oil recovery methods.

Capillary Pressure Effects on Estimating the Enhanced-Oil-Recovery Potential During Low-Salinity and Smart Waterflooding

SPE Journal ◽  
2019 ◽  
Vol 25 (01) ◽  
pp. 481-496 ◽  
Author(s):  
Pål Østebø Andersen
Keyword(s):  
Capillary Pressure ◽  
Relative Permeability ◽  
Oil Recovery ◽  
Wettability Alteration ◽  
Residual Oil ◽  
Oil Saturation ◽  
Residual Oil Saturation ◽  
Low Salinity ◽  
Smart Water ◽  
Relative Permeability Curves

Summary Many experimental studies have investigated smart water and low-salinity waterflooding and observed significant incremental oil recovery after changes in the injected-brine composition. The common approach to model such enhanced-oil-recovery (EOR) mechanisms is by shifting the input relative permeability curves, particularly including a reduction of the residual oil saturation. Cores that originally display oil-wetness can retain much oil at the outlet of the flooded core because of the capillary pressure being zero at a high oil saturation. This end effect is difficult to overcome in highly permeable cores at typical laboratory rates. Injecting a brine that changes the wetting state to less-oil-wet conditions (represented by zero capillary pressure at a lower oil saturation) will lead to a release of oil previously trapped at the outlet. Although this is chemically induced incremental oil, it represents a reduction of remaining oil saturation, not necessarily of residual oil saturation. This paper illustrates the mentioned issues of interpreting the difference in remaining and residual oil saturation during chemical EOR and hence the evaluation of potential smart water effects. We present a mathematical model representing coreflooding that accounts for wettability changes caused by changes in the injected composition. For purpose of illustration, this is performed in terms of adsorption of a wettability-alteration (WA) component coupled to the shifting of relative permeability curves and capillary pressure curves. The model is parameterized in accordance with experimental data by matching brine-dependent saturation functions to experiments where wettability alteration takes place dynamically because of the changing of one chemical component. It is seen that several effects can give an apparent smart water effect without having any real reduction of the residual oil saturation, including changes in the mobility ratio, where the oil already flowing is pushed more efficiently, and the magnitude of capillary end effects can be reduced because of increased water-wetness or because of a reduction in water relative permeability giving a greater viscous drag on the oil.

Pore-Scale Investigations on the Dynamics of Gravity-Driven Steam-Displacement Process for Heavy-Oil Recovery and Development of Residual Oil Saturation: A 2D Visual Analysis

SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 1943-1959 ◽  
Author(s):  
Francisco J. Argüelles-Vivas ◽  
Tayfun Babadagli
Keyword(s):  
Particle Size ◽  
Oil Recovery ◽  
Heavy Oil ◽  
Heavy Oil Recovery ◽  
Pore Scale ◽  
Residual Oil ◽  
Lateral Expansion ◽  
Oil Saturation ◽  
Steam Chamber ◽  
Gravity Driven

Summary The dynamics of a gravity-driven injection process for heavy-oil recovery at the pore scale and the mechanisms leading to the formation of residual oil saturation (ROS) were investigated. The 10 × 15-cm and 5 × 5-cm 2D visual sandpack models (a single layer of sintered microscale glass beads) were prepared and placed into a transparent vacuum chamber to prevent heat loss. The processes were recorded with a high-speed camera to obtain visual data at the pore scale. This process represents the lateral spreading of the steam chamber (half symmetric chamber growth) during steam-assisted gravity drainage (SAGD) for heavy-oil recovery. Oil-trapping mechanisms yielding to the formation of ROS were described and analyzed because of (1) lateral expansion, (2) simultaneous vertical and lateral expansion, (3) pore and particle size, (4) heterogeneities (pore- and particle-size distribution), and (5) wettability. Attention was also given to the ceiling region of the steam chamber and its interaction with the mobilized region at the lateral boundaries of the chamber.

scholarly journals Quantifying the Low Salinity Waterflooding Effect

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1979
Author(s):  
Omar Chaabi ◽  
Mohammed Al Kobaisi ◽  
Mohamed Haroun
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
Laboratory Scale ◽  
Residual Oil ◽  
Oil Saturation ◽  
Low Salinity ◽  
Low Salinity Waterflooding ◽  
Reservoir Conditions ◽  
Salinity Water ◽  
Relative Permeability Curves

Low salinity waterflooding (LSW) has shown promising results in terms of increasing oil recovery at laboratory scale. In this work, we study the LSW effect, at laboratory scale, and provide a basis for quantifying the effect at field scale by extracting reliable relative permeability curves. These were achieved by experimental and numerical interpretation of laboratory core studies. Carbonate rock samples were used to conduct secondary and tertiary unsteady-state coreflooding experiments at reservoir conditions. A mathematical model was developed as a research tool to interpret and further validate the physical plausibility of the coreflooding experiments. At core scale and a typical field rate of ~1 ft/day, low salinity water (LS) resulted in not only ~20% higher oil recovery compared to formation water (FW) but also recovered oil sooner. LS water also showed capability of reducing the residual oil saturation when flooded in tertiary mode. The greater oil recovery caused by LSW can be attributed to altering the wettability of the rock to less oil-wet as confirmed by the numerically extracted relative permeability curves.

scholarly journals Pore-Scale Simulation of Particle Flooding for Enhancing Oil Recovery

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2305
Author(s):  
Xiangbin Liu ◽  
Le Wang ◽  
Jun Wang ◽  
Junwei Su
Keyword(s):  
Oil Recovery ◽  
Flow Behavior ◽  
Ct Scanning ◽  
Water Flooding ◽  
Pore Scale ◽  
Simulation Techniques ◽  
Three Phase ◽  
Remaining Oil ◽  
Three Phase Flow ◽  
Displacement Force

The particles, water and oil three-phase flow behaviors at the pore scale is significant to clarify the dynamic mechanism in the particle flooding process. In this work, a newly developed direct numerical simulation techniques, i.e., VOF-FDM-DEM method is employed to perform the simulation of several different particle flooding processes after water flooding, which are carried out with a porous structure obtained by CT scanning of a real rock. The study on the distribution of remaining oil and the displacement process of viscoelastic particles shows that the capillary barrier near the location with the abrupt change of pore radius is the main reason for the formation of remaining oil. There is a dynamic threshold in the process of producing remaining oil. Only when the displacement force exceeds this threshold, the remaining oil can be produced. The flow behavior of particle–oil–water under three different flooding modes, i.e., continuous injection, alternate injection and slug injection, is studied. It is found that the particle size and the injection mode have an important influence on the fluid flow. On this basis, the flow behavior, pressure characteristics and recovery efficiency of the three injection modes are compared. It is found that by injecting two kinds of fluids with different resistance increasing ability into the pores, they can enter into different pore channels, resulting in the imbalance of the force on the remaining oil interface and formation of different resistance between the channels, which can realize the rapid recovery of the remaining oil.

scholarly journals SURFACTANT-POLYMER FLOODING PERFORMANCE IN HETEROGENEOUS TWO-LAYERED POROUS MEDIA

2011 ◽  
Vol 12 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Muhammad Taufiq Fathaddin ◽  
Asri Nugrahanti ◽  
Putri Nurizatulshira Buang ◽  
Khaled Abdalla Elraies
Keyword(s):  
Porous Media ◽  
Oil Recovery ◽  
Polymer Flooding ◽  
Water Flooding ◽  
Residual Oil ◽  
Oil Saturation ◽  
Reservoir Heterogeneity ◽  
Residual Oil Saturation ◽  
Layered Porous Media ◽  
Multiple Porosity

In this paper, simulation study was conducted to investigate the effect of spatial heterogeneity of multiple porosity fields on oil recovery, residual oil and microemulsion saturation. The generated porosity fields were applied into UTCHEM for simulating surfactant-polymer flooding in heterogeneous two-layered porous media. From the analysis, surfactant-polymer flooding was more sensitive than water flooding to the spatial distribution of multiple porosity fields. Residual oil saturation in upper and lower layers after water and polymer flooding was about the same with the reservoir heterogeneity. On the other hand, residual oil saturation in the two layers after surfactant-polymer flooding became more unequal as surfactant concentration increased. Surfactant-polymer flooding had higher oil recovery than water and polymer flooding within the range studied. The variation of oil recovery due to the reservoir heterogeneity was under 9.2%.

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