bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transport of EOR Surfactant in Reservoirs: Impact of Polymer on Apparent Surfactant Inaccessible Pore Volume
Authors: Alves Fortunato Maira , Bekri Samir , Rousseau David , Courtaud Tiphaine , Wartenberg Nicolas 
Published: June 2023

Abstract
Designing chemical EOR processes requires reservoir simulations that need to be backed by a good understanding of the mechanisms at play when injecting surfactant-based solutions in porous media. One of the main challenges is that laboratory coreflood tests often show early surfactant breakthroughs that cannot be easily history matched. Indeed, contrary to polymer macromolecules, smaller surfactant molecules are not supposed to experience the inaccessible pore volume (IPV) effect.
The study's aim was to determine if, in surfactant-polymer flooding, the polymer could influence the transport of the surfactant in such a way that it would not be able to invade a fraction of the pore space. To that end, two multi-steps coreflood tests were performed with cores of outcrop rock in conditions representative of a reference field case. In the first test, the surfactant was injected without polymer and then, after a brine injection flush, with polymer. In the second test, the surfactant was directly injected with polymer.
For both tests, in order to bypass the adsorption effect, the surfactant injected volumes at breakthrough were determined on rocks having their surface already fully saturated by surfactant. Namely, a first surfactant slug was injected in order to fulfill maximum rock adsorption capacity, then, immediately after, a second at a higher concentration of which the breakthrough was potentially influenced by IPV only. The polymer IPV were estimated by the conventional two-slugs method.
In the first test, the result showed that, without polymer, the surfactant accessed all of the pore volume of the core while, in presence of polymer, the surfactant could not access about 2% of the pore volume, which corresponded to the polymer IPV. In the second test, the surfactant was not able to access 12% of the pore volume, which also corresponded to the polymer IPV. These outcomes stand as evidence that the presence of polymer impacts the transport of surfactant, leading it to experience an "apparent" surfactant IPV effect equal to the polymer's one. This suggests that interactions between polymer and surfactant molecules take place at the pore level.
This study illustrates that surfactant transport properties in reservoirs can be more complex than conventionally accounted for in dynamic reservoir simulation. As history-matching of the coreflood essays is needed to build a representative dataset for surfactant-based EOR processes, improvements of the simulation software appear required for cases where IPV cannot be neglected.
Forecasting Low Enthalpy Geothermal Heat Extraction from Saline Aquifers Under Uncertainty
Authors: Bayerl Mathias , Ebner Marcus , Clemens Torsten 
Published: June 2023

Abstract
District heating can be decarbonized by using low enthalpy geothermal heat. In this case study, water from a deep saline aquifer with a temperature of 90-110 °C is produced, heat extracted for district heating and the cold water re-injected into the aquifer. There are substantial subsurface uncertainties in the structure as well as porosity and permeability distribution of the saline aquifer that need to be addressed to optimize heat extraction under uncertainty.
The deep saline aquifer characterization is based on 3D seismic and a limited number of wells. Hence, substantial uncertainty exists in porosity/permeability distribution and dynamic and thermal properties. To address the uncertainty, different geological concepts need to be evaluated and parameter ranges for geostatistical and poro-perm relationships need to be used. To cover the uncertainty range, we constructed 600 geological models all honoring the limited existing data. However, dynamically simulating all the geological models including the ranges for the thermal properties is usually too costly.
We utilize a geo-screening workflow, which selects a subset of representative models based on dynamic (proxy) response, the workflow aims at keeping the same variability of the subset as for the full ensemble. This is achieved via a dimensionality reduction of the problem, by clustering of the models in multi-dimensional space. The centroids of these clusters are selected as representative models used for full-physics simulations to forecast heat extraction under uncertainty. To define a consistent method for selecting a representative subset of geologic realization we simulated the full ensemble and compared it to (i) subsets of different clustering approaches using static (heat in-place) and dynamic (tracer rate & flux pattern) proxy responses and (ii) subset sizes.
The results of the workflow show that the tracer rate is a better metric for the selection of the cluster centroids compared with flux-pattern and in particular heat in place. For this case 20-40 geological realizations were sufficient to cover the uncertainty space for forecasting low enthalpy heat extraction. The suggested workflow allows for addressing the subsurface uncertainty in static and dynamic parameters making use of streamline simulation to reduce simulation costs. The resulting model ensemble can be used for field development planning of low enthalpy heat extraction under uncertainty.
Simulations of Alkali-Polymer Experiments: Modeling of In-Situ Emulsion Generation and Transport of Oil-In-Water Emulsion in Porous Media
Authors: Perez-Perez Alfredo , Romero Carolina , Santanach-Carreras Enric , Skauge Arne 
Published: June 2023

Abstract
The injection of alkali in acidic viscous oils is known to promote the in-situ formation of emulsions during chemical oil recovery. Naphthenic acid components react with the alkali to form in-situ surfactants, which support oil emulsification at the water-oil interface. It is believed that emulsification and transport of the dispersed oil in the presence of polymer can significantly improve oil recovery.
In earlier work, we proposed a new mechanistic non-equilibrium model to simulate alkali-polymer processes for different oil viscosities (2000 – 3500 cP at 50°C) with an acid number of around 4 mg KOH/g. The model considers emulsion generation kinetics, polymer, and emulsion non-Newtonian viscosity through a straightforward modelling strategy. The emulsified oil was treated as a dispersed component in water phase (O/W emulsion), while the water phase mobility considered the apparent aqueous phase viscosity containing dispersed oil and polymer.
In the above referenced work, seven alkali-polymer corefloods performed with different alkali types and slug sizes were history matched. We showed that the model is capable of appropriately matching the experiments. Kinetics obtained by history match show that emulsion formation under the conditions here studied is alkali type dependent.
In the current work, we applied our alkali-polymer model in two displacement tests (Hele Shaw cell) with two different oil viscosities (2000 – 200 cP at 50°C). These new experiments included secondary water flood, tertiary polymer flood and quaternary alkali-polymer flood. The initial conditions of alkali-polymer (AP) flood were obtained after properly modelling the unstable immiscible floods and polymer floods. For modelling the polymer floods (2D slabs), three models were evaluated: 1) extension of relative permeability curves applied to water flood, 2) Killough method (hysteresis for the water phase) and relative permeability power-law extensions and 3) two relative permeability curves with polymer concentration dependency.
Our alkali-polymer model was employed for simultaneously history matching 1D and 2D experiments performed with 5 g/L of Na2CO3 and polymer. When comparing alkali-polymer results, a good agreement was found for the complete set of experiments. In addition, fitting parameters (kinetics and emulsion viscosity) were close to the parameters reported in the earlier study.
Finally, fitted alkali-polymer parameters were employed for predicting alkali-polymer outputs in the second slab (with similar alkali-polymer concentration but lower oil viscosity). Even if experimental observations are relatively well represented, a lower value of incremental oil recovery (&lt;3 % OOIP) was obtained. We believe that the use of a less viscous oil (diluted oil) in the experiments may influence the generation and transport of formed emulsions.
Simulation and Prediction of Countercurrent Spontaneous Imbibition at Early and Late Times Using Physics-Informed Neural Networks
Authors: Abbasi Jassem - , Andersen Pål Østebø 
Published: June 2023

Abstract
We investigated countercurrent spontaneous imbibition (COUCSI) of water displacing oil in a 1D linear system with one side open, and one side closed. The Physics-Informed Neural Networks (PINNs) technique was used to estimate saturation profiles along the core and recovery against time; based on the same input information as a reservoir simulator. We demonstrate the usefulness of Change-of-Variables as an approach to improve PINN solutions.
The problem was first normalized, where only a saturation-dependent diffusion coefficient results in different solutions. The initial condition was zero saturation, the open boundary had a saturation equal to one, and the closed boundary had a zero saturation gradient. We formulated the problem in three equivalent ways by Change-of-Variables: XT, YZ, and Z formulations. The first is the original normalized form and describes saturation as a function of normalized position X and time T. The second defines saturation as a function of Z=X/T^0.5 and Y=T^0.5. The third considers saturation as a sole function of Z=X/T^0.5 and is valid only at early times (ET), before water meets the no-flow boundary. The COUCSI problem was solved using a feed-forward neural network trained based on a weighted loss, including the physics-informed loss term and terms corresponding to initial and boundary conditions for all the formulations. No synthetical or experimental data were involved in the training. The generalization ability is tested by applying the workflow to two imbibition cases with different displacement profile behavior. The PINN solutions were tracked to determine if they followed the flow's theoretical properties, including self-similarity, square root of time behavior, and Total Variation (TV). We investigated the ability of the applied formulations to estimate the correct solution (compared to numerical simulations) at early and late times.
All the formulations could very closely converge to the correct solutions, with the water saturation mean absolute errors around 3.5 and 2.5 percent for XT and YZ formulations and 1.0 percent for the Z formulation at ET. The Z formulation almost perfectly captured the self-similarity properties of the system in the ET period (and in lower level, YZ), which only depends on X/T^0.5 at early time. The TV of saturation was successfully preserved in the Z formulation and YZ performed better than XT formulation. By performing a sensitivity analysis we demonstrate that Change-of-Variables can lead to a lower number of required collocation points and also smaller network sizes.
Fluid Identification from Mud Gas in the Overburden – A Case Study for the Snorre Field
Authors: Ungar Frode , McGill Andrew , Nygaard Marianne Therese , Dos Reis Teo Paiva , Kvilhaug Sigurd , Wagner Vincent , Yang Tao 
Published: June 2023

Abstract
Based on the successful utilization of advanced mud gas (AMG) for fluid identification in five production/injection wells in the Snorre field, the fluid identification while drilling technology was deployed for a seismic anomaly within the overburden at the Kyrre formation level. The main objective was to identify the reservoir fluid type (oil versus gas) within the anomaly and to use this information to potentially de-risk a similar shallower seismic anomaly - the Linga prospect at the top Shetland level.
Fluid identification while drilling is an award-winning innovation that has been broadly used in exploration and production wells at Equinor. The digital technology combines mud gas and PVT data for accurate reservoir fluid typing and property predictions. Snorre field is one of the first users of the technology and accumulated good experiences regarding the capacity and limitations in reservoir zones. Due to the lack of other good tools to identify the hydrocarbon in overburden in a cost-efficient manner, the Snorre field decided to deploy the fluid identification technology for the task.
Utilizing AMG data in the overburden for the four Snorre Expansion Project (SEP) wells showed satisfactory results. Reservoir oil was identified with confidence in the Kyrre formation for the first three wells, and no additional logging was necessary. The 4th well was drilled with higher ROP (above 30 m/hr) and proved a similar oil signature without compromising the data quality. The main objective was met, the fluid type in the Kyrre anomaly was confirmed, and this result was a de-risked Linga prospect. The probability of producing the Linga prospect has increased due to the accurate reservoir fluid type.
The experiences in the overburden from the Snorre field show fluid identification from mud gas is a cost-efficient tool and has the potential to be utilized broadly in the overburden. With an accurate fluid identification in the overburden, we can achieve safety assurance, reduced drilling costs, and matured production prospects.
Auto-Correction Algorithm of Multiphase Flowmeter Water Cut Measurements in Undersaturated Oil Wells
Authors: Alali Mohammed H. 
Published: June 2023

Abstract
Dual energy gamma ray attenuation in multiphase flow meters (MPFMs) are commonly used in the oil and gas industry to measure the flow rate of hydrocarbon producing wells. The low energy gamma ray attenuation is highly dependent on water salinity, making this type of MPFM very sensitive to water salinity. This challenge is evident in oil fields where lower salinity water is injected into the reservoir to maintain pressure for oil producing wells, imposing changes in water salinity with time. Hence, frequent fluid sampling and calibration is required to ensure high reliability measurements from such meters. In this paper, a new methodology is proposed to automatically correct the deviation in MPFM water cut measurements due to water salinity changes without the need to collect fluid samples.
The methodology proposed in this paper is a gas-oil ratio (GOR) based method that corrects the deviation in MPFM measurements due to the change in water salinity without the need to collect any fluid sample. In addition, the method does not require any additional information to be acquired from any other sources, other than the normal parameters acquired by the MPFM. The method is applicable to oil wells producing from undersaturated reservoirs. Furthermore, for the method to be reliable, the operating condition at the MPFM has to have adequate amount of free gas because the methodology is GOR based methodology.
The results from the proposed method were cross checked against data collected from multiphase separator tests and showed excellent agreement. It was also tested across multiple undersaturated oil reservoirs against a wide range of oil properties and water salinities.
The method will help identify the MPFM that require calibration and will eventually make MPFM measurements more reliable without the need for frequent fluid sampling for meter calibration. This method will also lead to reducing the need for rigless multiphase separator testing requirements resulting in substantial cost reduction.
Measurement of Effective Hydrogen-Hydrocarbon Gas Diffusion Coefficients in Reservoir Rocks
Authors: Arekhov Vladislav , Zhainakov Timur , Clemens Torsten , Wegner Jonas 
Published: June 2023

Abstract
If hydrogen is stored in depleted gas fields, the remaining hydrocarbon gas can be used as cushion gas. The composition of the back-produced gas depends on the magnitude of mixing between the hydrocarbon gas and the hydrogen injected. One important parameter that contributes to this process of mixing is molecular diffusion. Although diffusion models are incorporated in latest commercial reservoir simulators, effective diffusion coefficients for specific rock types, pressures, temperatures, and gas compositions are not available in literature. Thus, laboratory measurements were performed to improve storage performance predictions for an Underground Hydrogen Storage (UHS) project in Austria.
A high-pressure-high-temperature experimental setup was developed that enables measurements of effective multicomponent gas diffusion coefficients. Gas concentrations are detected using infrared light spectroscopy, which eliminates the necessity of gas sampling. To test the accuracy of the apparatus, binary diffusion coefficients were determined using different gases and at multiple pressures and temperatures. Effective diffusion coefficients were then determined for different rock types. Experiments were performed multiple times for quality control and to test reproducibility.
The measured binary diffusion coefficients without porous media show a very good agreement with the published literature data and available correlations based on the kinetic gas theory (Chapman-Enskog, Fuller-Schettler-Giddings). Measurements of effective diffusion coefficients were performed for three different rock types that represent various facies in a UHS project in Austria.
A correlation between static rock properties and effective diffusion coefficients was established and used as input to improve the numerical model of the UHS. This input is crucial for the simulation of back-produced gas composition and properties which are essential parameters for storage economics. In addition, the results show the impact of pressure on effective diffusion coefficients which impacts UHS performance
P/Z for CO2 Injection into Depleted Gas Reservoirs
Authors: de Kok Joop Hendrik , Huijskes Thijs Diederik 
Published: June 2023

Abstract
Pressure data can be used to identify possible leaks in a CO2 storage site. However, conventional diagnostic plots used during gas production cannot directly be used to interpret the data, because CO2 properties have a different pressure dependency compared to the hydrocarbon gas initially in place. This paper investigates the possibility of adjusting p/Z plots for CO2 storage into depleted gas reservoirs to make them suitable for monitoring during injection.
The p/Z method is explained analytically for both gas production and CO2 injection. A method is proposed to graphically ensure that the p/Z plot during injection overlies the p/Z plot during depletion – the injection line follows the p/Z plot backwards. The method proposes to use a volume-weighted Z-factor to scale both p/Z and injected volume. This method is verified with compositional thermal simulations in a homogeneous model.
The uncertainty of both pressure and Z-factor is investigated and the implications of these uncertainties are discussed. Additionally, the proposed method is tested for reservoirs that do not show volumetric depletion behavior.
For a volumetric gas reservoir (straight-line p/Z) without near-wellbore cooling it is possible to follow the original p/Z plot backwards with the proposed method. Cooling of the near-wellbore area causes a temperature induced increase of density. The impact of this phenomenon is less than 4% on the p/Z estimate in the described case. With an analytical estimate of the extent of the cooling area, the p/Z value can be corrected to an error of less than 1.5%.
Uncertainty in Z for natural gas and CO2 at reservoir conditions can be significant, but generally result in a low impact on the accuracy of the method. The uncertainty in static pressure is larger with CO2 injection due to the higher fluid viscosity and more uncertain downhole density.
For reservoirs with ‘slow gas’ behavior, the proposed method does not result in an overlap with the depletion p/Z plot. However, the method does reproduce the path that methane injection follows.
The proposed methodology indicates to what extent the storage is filled and has the potential to identify large leakage of CO2 (&gt;1% of GIIP) for volumetric gas reservoirs. To verify the observed potential leak, it is recommended to perform full field simulation.
Modeling hydrological responses of watershed under climate change scenarios using machine learning techniques
Authors: Karimizadeh Keivan , Yi Jaeeung 
Published: June 2023

Abstract
Climate change is the most important problem of the earth in the current century. In this study, the effects of climate change on precipitation, temperature, wind speed, relative humidity and surface runoff in Saghez watershed in Iran investigated. The main methods were using the Coupled Model Intercomparison Project phase 6 (CMIP6), the Soil and Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN) model under the Shared Socio-economic Pathway scenarios (SSPs) using the Linear Scaling Bias Correction (LSBC) for the future period (2021–2050) compared to the base period (1985–2014). MAE, MSE, RMSE and R2 indices used for model calibration and validation. The results of forecasting temperature, precipitation, wind speed and relative humidity showed the average percentage of precipitation decrease in the future period will be 6.1%. In terms of the temperature, 1.4, 1.5 and 1.6 Cº increase predicted for minimum, average and maximum temperatures, respectively. The results of studying the surface runoff changes using the SWAT model also illustrated that based on all three scenarios SSP1-2.6, SSP3-7.0 and SSP5-8.5 in the future period, the amount of surface runoff will decrease, which based on three mentioned scenarios is equals to 17.5%, 23.7% and 26.3% decrease, respectively. Furthermore, the assessment using the artificial neural network (ANN) also showed that the parameters of precipitation in the previous two days, wind speed and maximum relative humidity have the greatest effect on the watershed runoff.