Reservoir Fluid Research Articles

An Upscaling Machine Learning Method Based On Physical Information

Objective: The objective of this study is to investigate a machine learning methodology based on the physics of dynamic fluid flow, with the aim of incorporating the knowledge of physical laws into learning algorithms to estimate precise results with lower computational cost. Theoretical Framework: This section presents the main concepts and theories that underpin the research. Key theories include nonlinear partial differential equations (PDEs), Darcy's Law, and the conservation of mass and energy, providing a solid foundation for understanding the research context. Method: The methodology adopted for this research involves modeling a one-dimensional two-phase fluid flow problem in a porous medium, governed by a first-order hyperbolic nonlinear equation. Data collection was conducted through numerical simulations, using micro and macro grids to evaluate permeability and boundary conditions. Results and Discussion: The results revealed that considering learning only in absolute permeability yielded good estimates of reservoir pressures. However, small discrepancies were observed in the estimation of saturations. The discussion contextualizes these results in light of the theoretical framework, highlighting the identified implications and relationships, as well as the study's limitations. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of reservoir modeling and fluid flow simulations. These implications may include optimizing oil extraction processes and improving predictive models in reservoir engineering. Originality/Value: This study contributes to literature by presenting an innovative approach that integrates physical laws into machine learning algorithms, resulting in more accurate and efficient estimates. The relevance and value of this research are evidenced by the potential application of the results in optimizing industrial processes and improving computational simulations.

Scleral lens wear and fluid reservoir turbidity in eyes with ocular surface disorders.

To investigate changes in fluid reservoir turbidity parameters over time and its influence on visual performance in eyes with ocular surface disorders (OSD) wearing scleral contact lenses (SL). Thirteen eyes with OSD were assessed for corrected distance visual acuity, contrast sensitivity (CS) and fluid reservoir turbidity using anterior segment optical coherence tomography at baseline, after 5 min and 0.5, 1, 2, 3 and 4 h of SL wear on day 1 and after 1 month. A significant reduction in CS was noted at 0.5, 1, 2, 3 and 4 h of SL wear compared to 5 min (p < 0.001) and a similar trend was noted after 1 month (p < 0.001). The average number of particles on day 1 showed a significant increase over 4 h of SL wear (p < 0.001), with a same trend noted at 1 month (p = 0.001). However, the percentage of particles decreased from 88% ± 4% to 75% ± 12% (p = 0.004) after 1 month of SL wear. Average particle size showed a significant increase at all time points over 4 h compared with 5 min of SL wear (p < 0.003) and after 1 month (p < 0.001). The percentage of average particle size decreased from 73% ± 9% to 67% ± 8% after 1 month of lens wear (p = 0.003). The mean percentage turbid area increased from 0.6% ± 0.5% to 24% ± 16% over 4 h of lens wear on day 1 (p < 0.006) and from 0.7% ± 0.5% to 11% ± 8% at 1 month (p = 0.001). The mean difference in percentage turbid area at the first and follow-up visits decreased from 96% ± 3% to 89% ± 9% (p = 0.01). A gradual increase in fluid reservoir turbidity parameters was noted with the reduction in CS; however, all these parameters improved after 1 month of SL wear.

The Crack Propagation Behaviour of CO2 Fracturing Fluid in Unconventional Low Permeability Reservoirs: Factor Analysis and Mechanism Revelation

The Crack Propagation Behaviour of CO2 Fracturing Fluid in Unconventional Low Permeability Reservoirs: Factor Analysis and Mechanism Revelation

A systematic global recharacterization method for reservoir fluids in compositional simulations

A systematic global recharacterization method for reservoir fluids in compositional simulations

The Architecture of BaTiO3 Nanoparticles Synthesis via Temperature-Responsive for Improved Oil Recovery: A Molecular Dynamics Simulation and Core-Flooding Experimental Study

This research investigates the influence of various concentrations of BaTiO3 nanofluid on adsorption energy and improved oil recovery. BaTiO3 nanoparticles were successfully synthesized using a Sol-gel approach at temperatures of 400 °C, 500 °C, 800 °C, and 1000 °C and characterized for their structural and morphological properties and interfacial tension (IFT)/Wettability measurement. The study focuses on using ferroelectric nanofluid in combination with an electromagnetic field to enhance oil recovery mechanisms. Three concentrations of BaTiO3 nanofluid were prepared, and their effects on pressure and recovery factors were examined. The results demonstrate that BaTiO3 nanofluids increase the reservoir fluid’s ionic conductivity, leading to environmental polarization. Applying BaTiO3 nanofluid on glass bead samples resulted in a significant 42.15% increase in the recovery factor at a 0.3% concentration in various measurements, including interfacial tension, core-flooding, and wettability. The nanofluid caused a reduction in interfacial tension and a shift in wettability from oil-wet to water-wet. The higher adsorption energy of the nanofluid corresponded to more significant oil recovery. The optimal concentration for maximum adsorption energy (−2.566331 × 104) and oil recovery (22.5%) was 0.3wt%. At 0.1% concentration, the IFT value was 0.023 mN/m, at 0.3% concentration the IFT was 0.017 mN/m and at 0.5% concentration IFT value was 0.032 mN/m. The contact angle of the brine with the oil was 89.39% compared to the contact angle of 0.1%, 0.3%, and 0.5% which were 64.25%, 10.57%, and 44.63%, respectively. It was revealed from the result that 0.3% of nanofluid decreased the contact angle from 89.39% to 10.57 at a 0.3% concentration of BaTiO3 nanofluid. This shows that the wettability of the rock surface changed from oil-wet to water-wet with the novel application of BaTiO3 nanoparticles. This improvement in recovery can be attributed to the modification of wettability and reduction of interfacial tension.

Subsidence and Effective Stresses Distribution Using Finite Element Techniques for an Iraqi Oilfield

Geomechanical problems are the most important problems that happen in the Zubair oil field; treating these problems requires a lot of time (Non-Productive Time) and thus increases the cost of drilling the well. Wellbore instability, subsidence, reservoir compaction, casing smash, pipe damage, and well kick is the main geomechanical problems facing the drilling process in the Mishrif formation, Zubair oilfield. The main goals of this study are to estimate the changes in stresses and subsequent subsidence values for this field during the production and injection periods. These estimation values, many problems can be avoided, thus increasing the drilling efficiency. This study is to introduce the one way coupling between the reservoir model and geomechanical model using the finite element method. The finite element technique in CMG 2018 program was used to estimate the stress states during the production or injection operations in this field of interest. The results of the 3D finite element model showed that the effective vertical stress rises by 32 psi during production while the effective horizontal stress increases by 16 psi. This may be explained by the fact that variations in pore pressure have little or no impact on the total vertical stress generated by weight. The results of this study demonstrated that the finite element method is a conservative method for coupling reservoir geomechanics and fluid flow. Subsidence values were 6.096 mm in the north part of the Al-Hammar dome, while at the center the subsidence was -5.1816 mm. Shuaiba dome has negative subsidence which is about -9.75 mm. It is important to note that the positive results subsidence signify the pore volume compacting, which may have an impact on the permeability and porosity of the reservoir petrophysics. As a result of a negative subsidence deformation, different failures including well casing damage, wellbore failure, and pipe smashing, are expected. Based on these results, production can cause an increase in the differential stress, which leads to rock shear failure and in injection cases, increasing pore pressure can cause a tensile rock failure.

Effects of Modified Cross-Linkers on the Rheology of Water-Based Fracturing Fluids and Reservoir Water Environment

Improving the chemical structure of the cross-linker is a potential method for reducing reservoir pollution and enhancing the fracturing efficiency of shale reservoirs. In this investigation, a three-dimensional (3-D) spherical cross-linker comprising branched chains was synthesized, and the 3-D structure of the cross-linker was analyzed through scanning electron microscopy (SEM). Furthermore, we constructed a multifunctional coupled collaborative evaluation device that can be used to evaluate numerous properties associated with water-based fracturing fluids, including fluid viscosity, adsorption capacity, and water pollution. Meanwhile, the influence of varying reservoir conditions and cross-linker content on the fluid viscosity of water-based fracturing fluids and the potential for reservoir contamination has been evaluated and elucidated. The results indicated that the synthesized cross-linker exhibited a superior environmental protection of the shale reservoir and an enhanced capacity for thickening fracturing fluids in comparison to commercial cross-linkers. Moreover, cross-linker content, reservoir temperature, reservoir pressure, and fracture width can affect fluid viscosity and reservoir residual in different trends. The addition of 0.3% nano-cross-linker (Synthetic products) to a water-based fracturing fluid resulted in an apparent viscosity of 160 mPa·s at 200 °C, and the adsorption capacity and water content of the shale reservoir were only 0.22 µg/m3 and 0.05 µg/L, respectively. Additionally, an elevation in reservoir temperature resulted in a reduction in the adsorption capacity. However, the cross-linker content in groundwater underwent a notable increase, and the cross-linker residue in water increased by 0.009 µg/L. The impact of reservoir pressure on fluid viscosity and groundwater pollution potential exhibited an inverse correlation compared to that of reservoir temperature, and the above two parameters changed by +18 mPa·s and −0.012 µg/L, respectively. This investigation provides basic data support for the efficient fracturing and reservoir protection of shale reservoirs.

Electrode-Level Modeling of Silicon Anodes for Improved Cell Design

Abstract Silicon has a remarkably high specific capacity as a Li-ion battery anode material; however, its large volume expansion and contraction make it extremely challenging to use. This work introduces a pseudo-2D (P2D or Newman-type) model that incorporates the distinctive mechanical and electrochemical behaviors of porous electrodes with large volume changes characteristic of silicon and similar active materials. Localized volume change is propagated rigorously to other electrode variables, considering elastic, plastic, and chemical strains; associated advection and hysteresis; the presence of a fluid reservoir and packaging adjacent to the cell stack; nonlinear electrode swelling behavior; deactivation of active material; and the effect of stress on open circuit potential. A silicon half-cell model is carefully parameterized by previously published experiments, and indeed provides insights in how to interpret the experiments and shows where some are problematic. The model is used as a digital twin to predict the degree of electrode utilization for different packaging designs and active material loadings, thereby allowing improved cell design.

Integrated experimental studies of pore structure and fluid uptake in the Bossier Shale in eastern Texas, USA

Within the Haynesville-Bossier Shale complex, the Bossier Shale has not been extensively studied by either industry and academia, despite it being an unconventional gas reservoir and a potential caprock for carbon storage in the underlaying Haynesville Shale. The lack of knowledge of the complex pore structures and fluid-rock interactions hinders the effective extraction of gas and the characterization of fluid reservoirs and sealing capacity. Integrated experimental studies of pore structure and fluid-rock interactions were conducted in seven Bossier Shale core samples collected in eastern Texas. Petrographic, geochemical, and petrophysical properties such as mineral composition, organic richness, thermal maturity, porosity, pore/pore throat diameter distribution, water-accessible pores, liquid water imbibition, and water vapor adsorption were characterized using complementary approaches of thin-section petrography, scanning electron microscopy, X-ray diffraction, total organic matter, pyrolysis, mercury intrusion porosimetry, nuclear magnetic resonance, (Ultra-) small angle X-rays scattering as well as small angle neutron scattering with deuterated liquids and contrast variation. The results show that the thermally mature Bossier Shales are composed of mixed argillaceous mudstone, mixed mudstone, and mixed carbonate mudstone. The shale contains both organic and inorganic pores, with porosities of 3.24–9.37 %, pore-to-throat ratios of 1.65 to 19.4, and water-accessible pores accounting for 28.7–72.6 % of total pores. Approaches of liquid water imbibition and water vapor adsorption, with and without direct contact of water with shale samples, indicate that liquid water first enters the nano-sized pores under high capillary pressures, and water vapor adsorption is mainly controlled by both clay minerals and pores with diameters less than 10 nm. These findings contribute to a better understanding of pore structures and water-shale interactions and their controlling factors in the Bossier Shale.

A time-lapse multicomponent (9C 4D) seismic study at Vacuum Field, New Mexico, USA

In November and December 1995, the Reservoir Characterization Project (RCP) at the Colorado School of Mines acquired time-lapse multicomponent 3D surveys over the Central Vacuum Unit of Vacuum Field in Lea County, New Mexico. Two surveys were acquired — one before and one after the injection of 50 MMscf CO2 through a single wellbore into the San Andres Reservoir. The project determined that repeated multicomponent seismic surveys at the earth's surface can detect changes in bulk rock properties due to variations in reservoir pressures and fluid properties. Interpretation of the dynamic seismic response due to reservoir production processes over time provides an image of the relative permeability structure of the reservoir. Time-lapse multicomponent data were acquired using three-component geophones and vertically and horizontally actuated vibrator sources at the surface. A data processing flow was developed for time-lapse multicomponent 3D surveys. It uses surface-consistent processing algorithms and the source and receiver redundancy between initial and repeat surveys to derive surface-consistent corrections. Differences in S-wave polarization are measured between the initial and repeat surveys. S-wave data show sensitivity (through birefringence) to anisotropy caused by the orientation of fractures and low-aspect-ratio pore structure in a nonuniform stress field. The direction of fast S-wave polarization can be related to the direction of maximum horizontal stress and preferential permeability. Pore-pressure variations alter the effective stress. This varies the direction and intensity of open fractures and low-aspect-ratio pore structure within the current permeability structure of the reservoir, causing detectable changes in S-wave anisotropy. Anomalies in S-wave anisotropy, interpreted from time-lapse multicomponent 3D data, in conjunction with reservoir production data, are consistent with the fluid composition and pore-pressure changes associated with the CO2 injection program and reservoir processes in the survey area. Applications include monitoring hydrocarbon enhanced oil recovery; carbon capture, utilization, and storage; hydraulic stimulation; induced seismicity; and geothermal investigations.

Reservoir Fluid Properties From Cuttings: An Innovative Synergy of Gel Permeation Chromatography and Data Analytics

Reservoir Fluid Properties From Cuttings: An Innovative Synergy of Gel Permeation Chromatography and Data Analytics

A Case Study: Determination of Physical Properties of The Reservoir Fluid “Pse” Field Using The EOS and Black Oil Model on Commercial PVT Software

Lapangan PSE, yang terletak di Cekungan Sumatra Tengah, menghadapi tantangan signifikan akibat data sifat fluida yang tidak lengkap dan usang dari sumur X, di mana pengukuran terakhir dilakukan pada tahun 1992. Kurangnya data fluida yang komprehensif menghambat karakterisasi reservoir yang akurat, yang sangat penting untuk mengoptimalkan strategi produksi. Penelitian ini bertujuan untuk mengatasi kekurangan tersebut dengan menggunakan perangkat lunak karakterisasi fluida termodinamika (PVTp) untuk menghasilkan data fluida yang andal, melalui perbandingan antara model Persamaan Keadaan (Equation of State, EOS) dan model Black Oil. Metodologi penelitian mencakup penerapan dua model prediksi sifat fluida: model EOS dan model Black Oil. Model EOS, yang berbasis pada prinsip-prinsip termodinamika, dievaluasi terhadap model Black Oil yang bersifat empiris. Kedua model tersebut dievaluasi berdasarkan parameter kunci seperti tekanan jenuh (Psat), rasio gas-minyak (GOR), faktor volume formasi (FVF), densitas, dan viskositas. Persentase rata-rata kesalahan absolut (AAE%) digunakan sebagai tolok ukur kinerja model. Hasil penelitian menunjukkan bahwa model EOS secara konsisten lebih unggul dibandingkan model Black Oil, dengan AAE% rata-rata 1,2%, dibandingkan dengan 10,94% pada model Black Oil. Untuk parameter spesifik, metode EOS mencapai AAE% sebesar 0% untuk Psat, 0,81% untuk volume relatif, 3,7% untuk GOR, 1,4% untuk FVF, dan 0,1% untuk densitas. Sebaliknya, metode Black Oil menunjukkan kesalahan yang jauh lebih tinggi, terutama pada GOR (40,6%) dan FVF (7,7%). Hasil ini menegaskan bahwa model EOS lebih akurat dalam memprediksi sifat fluida dengan kesalahan minimal. Kebaruan dari penelitian ini terletak pada studi kasus yang terfokus di Cekungan Sumatra Tengah, di mana data sifat fluida sebelumnya sangat terbatas. Penelitian ini menunjukkan keterbatasan model Black Oil dalam reservoir yang kompleks, di mana penyesuaian terhadap data laboratorium diperlukan, serta menempatkan model EOS sebagai alternatif yang lebih andal untuk karakterisasi fluida yang akurat. Manfaat utama dari penelitian ini adalah kontribusi praktisnya terhadap teknik reservoir, dengan menyediakan pendekatan yang tervalidasi untuk pemodelan fluida yang dapat meningkatkan pengambilan keputusan pada lapangan dengan data terbatas serupa. Studi ini tidak hanya mengatasi tantangan langsung dari sumur X, tetapi juga menetapkan preseden untuk upaya pemodelan fluida di masa depan, serta menyarankan bahwa industri perlu mempertimbangkan untuk beralih dari metode Black Oil tradisional ke simulasi berbasis EOS yang lebih akurat

Modeling the Constant Composition Expansion Test of Black Oil using Pressure, Volume, and Temperature (PVT) Calculations

The black oil pressure, volume, and temperature (PVT) properties of well X were measured in the laboratory in a PT cell with subsurface and surface recombination samples. Four sets of black oil samples were collected for the analysis. The black oil standard test is a constant composition expansion test (CCE) separator flash test for volatile oils and rich oil gas condensate and a constant volume depletion test (CVD). The PVT analysis was carried out at Reservoir Fluid Laboratory, Port Harcourt. Oil samples were collected from the Q oil field. The PVT analysis results were correlated to validate the bubble point pressure (Pb), oil isothermal combustibility, (Co), oil formation volume factor (Bo), and the oil viscosity (μo). The PVT report gives Po= 2000 psi while the standing correlation gives Pb= 1934.271 psi a difference of 65.7 psi, i.e. 3.3% and solution gas/oil ratio 647.3 SCF/STB while the standing correlation gives 671.03 SCF/STB a difference of 3.5%,oil formation volume factor (Bo) of 1.456 res. Bbl/STB while standing correlations give (Bo) of 1.0675 res bbl/STB a difference of 3.6%. The isothermal compressibility of the oil ranges from 10.12 x 10-6psi-1at P&lt; Pb(a t 4500 psi) to 4.1309 x 1018cp at 15 psi. The conclusion is that Gas began evolving at 2000 psig and increased as the pressure decreased. Also, it was noticed that at high pressure of 4500 psig the black oil viscosity was as low as 0.54 cp while at a lower pressure of 15 psiag the viscosity recorded was 1.38 cp. The crude is of high viscosity, with an average absolute error = 3.5% (0.035). The reservoir contains heavy crude oil with an API rating of 30.

Validating Subsurface Samples of Volatile Black Oil through PVT Calculations of Surface Separator Samples for Enhanced Reservoir Characterization

This study investigates black oil's pressure, volume, and temperature (PVT) properties from well X, analyzed using subsurface and surface recombination samples. Black oil samples were collected from the Q oil field and subjected to PVT analysis at the Reservoir Fluid Laboratory in Port Harcourt. Key findings include bubble point pressure (Pb) of 2000 psi, with a standing correlation value of 1934.3 psi, resulting in a 3.3% difference. The solution gas/oil ratio was measured at 647.3 SCF/STB, compared to 671.0 SCF/STB from correlations, a difference of 3.5%. The oil formation volume factor (Bo) was 1.456 res Bbl/STB, while standing correlations indicated 1.0675 res Bbl/STB, showing a 3.6% difference. The isothermal compressibility ranged from 10.12 x 10&lt;sup&gt;-6&lt;/sup&gt; psi&lt;sup&gt;-1&lt;/sup&gt; at 4500 psi to 4.1309 x 10&lt;sup&gt;18&lt;/sup&gt; cp at 15 psi. Gas evolution began at 2000 psig and increased with decreasing pressure. Viscosity varied significantly, recorded at 0.54 cp at 4500 psig and 1.38 cp at 15 psig. The reservoir contains heavy crude oil with an API rating of 30 and an average absolute error of 3.5% (0.035). These results enhance reservoir characterization and validate the use of PVT calculations in analyzing volatile black oil samples.

Role of optic zone diameter in scleral lens fitting in traumatic aniridia with scarred cornea – A case report

Scleral lenses (SLs) are large-diameter rigid gas-permeable lenses that vault over the entire cornea and rest on the bulbar conjunctiva overlying the sclera and maintain a fluid reservoir, which along with the rigidity of the lens masks irregular astigmatism and reduces the aberrations. A 20-year-old male had decreased vision, photophobia, and double vision due to an open globe injury with a shuttle bat 1 year back, followed by which he underwent corneal tear repair and multiple retinal surgeries. He was advised for penetrating keratoplasty elsewhere and came for a second opinion. Based on a diagnostic fitting approach, an 18.5 mm diameter SL was applied on the right eye, with which vision improved from 6/60, N36@ 10 cm to 6/7.5 and reduced the higher-order aberrations but a slightly higher vault was observed. Therefore, a 16.5 mm diameter SL was applied but with this lens, vision decreased to 6/12 with effort, and in both lenses, the patient reported binocular diplopia. Therefore, a combination of management, larger optic zone SLs, and a Fresnel prism was prescribed, which improved the patient’s vision, and reduced diplopia. The purpose of the case report is to emphasize the role of optic zone diameter in SL fitting, particularly in cases of traumatic scarred cornea with eccentric pupils and the importance of co-management.

Physics-based, data-driven production forecasting in the Utica and Point Pleasant Formation

We introduce a robust, data-driven and physics-based method to forecast the estimated ultimate recovery (EUR) of gas and condensates from the Utica-Point Pleasant Formation. By categorizing 3,410 horizontal wells into eight static cohorts based on the initial gas-oil ratios (GOR) and completion dates, we construct generalized extreme value (GEV) distributions of annual reservoir fluid mass production for each cohort. We use the expected values (means) to build historical, statistical well prototypes for each cohort. These prototypes account for hydraulic fracture deterioration, pressure interference between neighboring fractures, well interference, and advancements in completion technology. We extrapolate mass production of the reservoir fluids for several decades by fitting the scaling parameters of our physics-based model to the statistical well prototypes. A key innovation in this approach is using GEV statistics to generate a time series for each cohort’s GOR and condensate-gas ratio (CGR). We replace the individual production rates from all existing wells with their corresponding extended well prototypes and convert mass to volumetric rates. We sum up the latter rates and provide a base forecast of total reservoir fluid rates and cumulative production, closely matching the historical field production. Our base forecasts predict approximately 23 trillion scf of gas and 200 million barrels of condensate by 2035.The Utica-Point Pleasant Formation is divided into core and noncore areas, each further subdivided into regions based on fluid types. We analyze the future infill potential per square mile in each of these regions, proposing two drilling schedules and four potential future drilling scenarios. We identify approximately 35,847 potential future wells: 12,476 in the core area and 23,371 in the noncore area. The core wells can contribute about 157 trillion scf of natural gas and 0.9 billion barrels of condensate.This study marks the first integrated evaluation of the future production from the Utica-Point Pleasant Formation by combining GEV statistics, physics-based modeling, big-data analysis, geology, proposed drilling programs, and economics. It provides a comprehensive understanding of the Utica-Point Pleasant Formation’s significance in future U.S. shale production.

A new method for identifying reservoir fluid properties based on well logging data: A case study from PL block of Bohai Bay Basin, North China

Abstract The characterization of reservoir fluid properties is a crucial component of oilfield operations, as it provides a vital data foundation for the development and optimization of oilfield work programs. However, the complexity of water-flooded, along with the mixed data from drilling and cable logging, and the inherently weak foundational research, make the evaluation of water-flooded formations difficult. Therefore, this article aims to address this challenge by proposing a new reservoir fluid identification method. In this article, an improved Markov variation field model is applied to map geophysical logging data and is integrated with a quantum hybrid neural network (HQNN) to address the nonlinear correlations between logging data. By integrating the non-standard Markov variation field with HQNN, this article constructs a novel reservoir fluid identification model. Experimental results demonstrate that the model achieves a recognition accuracy of 90.85% when trained on feature images mapped from logging data. Furthermore, the superiority of the HQNN was validated through eight sets of comparative experiments. Additionally, the model was further validated using logging data from blind wells within the block, demonstrating high predictive accuracy and proving its effectiveness for reservoir fluid identification in the PL block. The method proposed in this article not only addresses the challenge of evaluating water-flooded layers in the absence of key logging curves but also offers a novel approach to reservoir fluid identification using geophysical logging data. The non-standard Markov transition field model is employed to map logging data into feature images, offering a new perspective on the application of geophysical logging data in practical reservoir analysis.

Suprachoroidal Space in Rhegmatogenous Retinal Detachment Assessed with Optical Coherence Tomography: Implications for Potential Future Therapeutic Interventions.

To comprehensively investigate the suprachoroidal space (SCS) in the context of rhegmatogenous retinal detachment (RRD) using swept-source optical coherence tomography (SS-OCT). We conducted a post hoc analysis of 90 consecutive patients with a primary RRD. Baseline SS-OCT scans were graded for the presence and thickness of the suprachoroidal space. Available scans of the fellow eye were graded for comparison. The suprachoroidal space was visible in 31.6% (24/76) of gradable RRD scans, with a mean thickest location measuring 67.0µm (SD 25.9), mean thinnest location of 33.8µm (SD 11.1), and mean average thickness of 50.0µm (SD 16.8). Additionally, the SCS was detectable in 28.3% (13/46) of available fellow eye scans, with a mean thickest location measuring 47.0µm (SD 41.7), thinnest location of 25.2µm (SD 27.6) and mean average thickness of 35.8µm (SD 31.4). A statistically significant difference was found between RRD and fellow eyes in all measurements of SCS thickness. In RRD, the suprachoroidal space serves as a crucial fluid reservoir influenced by dynamic shifts in intraocular hydrostatic and oncotic pressures. We found significant SCS engorgement in RRD eyes compared to fellow eyes, which may facilitate intra-SCS therapies such as suprachoroidal viscopexy (SCVEXY) or other pharmacologic interventions.

Controlling factors of fluid mobility in the tuff reservoirs of the Huoshiling formation, Dehui fault depression, southeastern Songliao Basin: insights from micro-nano pore structures

This study addresses the unclear understanding of the primary factors controlling fluid mobility in the tuff reservoirs of the Huoshiling Formation from the Dehui Fault Depression, southeastern Songliao Basin. Through physical property analysis, X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), thin section (TS), pressure-controlled porosimetry (PCP), rate-controlled porosimetry (RCP), and nuclear magnetic resonance experiments (NMR) on ten tuff samples, we conducted a comprehensive and in-depth exploration of the influencing factors that control the mobility of reservoir fluids. The results indicate: 1) The primary mineral types in the tuff reservoirs are quartz, feldspar, and clay minerals, with porosity predominantly characterized by dissolution pores and intergranular pores; 2) Based on the morphology of PCP intrusion curves, the tuff samples from the study area can be categorized into three types, with reservoir quality progressively deteriorating from Type I to Type III; 3) Compared to the movable fluids saturation (MFS), movable fluids porosity (MFP) is more suitable for characterizing fluid mobility. The mobility of fluids is influenced by various factors such as mineral composition, physical property, pore-throat connectivity, pore type and heterogeneity. MFS and MFP show a positive correlation with permeability, the content of quartz and feldspar, median pore-throat radius (R50), average throat radius (ATR), average pore-throat radius ratio (APT), T2 cutoff value (T2-C), average throat radius (RT), sorting coefficient (SC), and intergranular pore dominate space (Inter-DS), while a negative correlation with the content of calcite and clay minerals, average pore-throat radius ratio, and the fractal dimension from NMR (DNMR). This study elucidates the influencing factors of fluid mobility in tuff reservoirs, which has important reference significance for the scientific development of this type of gas reservoir.

Fast mass transfer processes of interfering trapped CO2-clusters at reservoir conditions: Experiment and theory

The gas-to-oil ratio (GOR) of a reservoir fluid plays a critical role in optimizing oil recovery and oil production strategies, improving oil recovery efficiency, and predicting reservoir behavior. Understanding the complicated kinetics of multicomponent mass transfer at the pore scale after gas injection into petroleum reservoirs is of great importance for estimating GOR and enhanced oil recovery (EOR). However, to date, there is a significant gap in the fundamental process understanding of the complex mass transfer process at reservoir conditions. Using micro-CT technology, we investigate the time dependence of CO2 mass transfer and cluster growth after high pressure CO2 injection into sedimented porous media (sintered 0.2 mm glass beads).Surprisingly, the CO2 partitioning equilibrium is already reached after 2 h. To the best of our knowledge, such a fast CO2 transport through water-saturated porous media, which cannot be explained by linear diffusion models (time scale 100 days for a diffusion length of 10 cm), has not been reported in the literature before. We proposed a conceptual model that assumes CO2 inflation of interfering gas clusters drives cascading CO2 transport. We verified this conceptual model through a time series of experiments at different initial gas saturation, analyzing in each case the spatial cluster distribution, cluster size distribution, and pore occupancy frequency.Whether CO2 inflation of the gas clusters occurs depends on the critical initial gas saturation, which is about 10%. Our main conclusion is that CO2 migration should be considered as gas phase diffusion cascading along a quasi-percolating cluster, since CO2 inflation leads to a high gas saturation of about 26%, which is close to the percolation threshold. Our experimental results support this physical hypothesis. We show for the first time that CO2 clusters can expand over large pore spaces and thus are close to the critical percolation threshold (mobility threshold). The cluster size distribution can be described by a power distribution with the critical exponent 2.19, i.e., it shows universal scaling.We model the interfering mass transfer processes of neighboring gas clusters with a multi-sphere model. Exploring different scenarios for the dissolution kinetics of an ensemble of interfering gas clusters allow a deeper understanding of the complicated mass transfer kinetics and agree well with experimental cluster analyses at specific times.