Nanotechnology has attracted significant attention in recent decades due to its diverse applications, particularly in chemical enhanced oil recovery (cEOR). By reducing fluid–fluid interfacial tension (IFT) and oil–rock contact angle (CA), nanomaterials offer a promising approach to improving oil recovery. This study explores the application of green-synthesized zinc quantum dots (Zn-QDs)—with an average size of approximately 10 nm and derived from parsley leaves—for EOR applications. The synthesized Zn-QDs were characterized using Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis (TGA), and transmission electron microscopy (TEM). Nanofluids were prepared by dispersing Zn-QDs in formation water and distilled water at concentrations ranging from 100 to 500 ppm. The stability and quality of the nanofluids were assessed by measuring key properties such as pH, density, and conductivity.Experimental evaluations, including IFT, CA, emulsion stability, and oil recovery tests, confirmed the effectiveness of these nanofluids. FW1-1-300 nanofluid, prepared by dispersing 300 ppm of nanodots in formation water, reduced the IFT significantly from 28.51 to 8.06 mN/m. Meanwhile, FW1:5-300 and FW1:15-400 were the most effective nanofluids for altering carbonate and sandstone wettability towards a strongly water-wet state, achieving CA values of 29.5° and 36°, respectively. Stability analysis indicated that lower concentrations of Zn-QDs provided better dispersion stability. In contrast, higher concentrations resulted in a significant reduction in droplet size, leading to the formation of a stable emulsion of crude oil and the injection solution. Ultimately, the green-synthesized nanodots enhanced the ultimate oil recovery by 22.28% of the original oil in place (OOIP) for carbonate rocks and 18.03% OOIP for sandstone rocks. These recovery rates represent a substantial improvement over the baseline water flooding recovery factors of 49.24% and 49.18% for carbonate and sandstone formations, respectively.

Greenhouse gas emissions, particularly carbon dioxide (CO2), drive anthropogenic climate change; although greenhouse gases such as methane (CH4) and nitrous oxide (N2O) have higher global warming potentials, CO2 dominates due to its high emission volume and long atmospheric lifetime, posing indirect risks to human health and the global climate. Among carbon capture and storage (CCS) approaches, geological CO2 storage is a promising solution for mitigating atmospheric concentrations by injecting CO2 into suitable subsurface formations and ensuring long-term stability. This paper presents a comprehensive review of CCS strategies focusing on the Czech Republic, synthesizing current knowledge on CO2 reduction principles, storage mechanisms, and geological suitability. While previous studies examined individual storage sites, this review provides a nationalscale assessment by systematically linking global CCS knowledge with geological conditions of the Czech Republic, enabling identification of the most promising regions and previously investigated storage sites. Based on literature and recent projects, saline aquifers in the Central Bohemian Basin exhibit the largest storage capacity, whereas depleted oil and gas reservoirs in the Vienna Basin offer more reliable containment due to wellcharacterized structures. Coal seams in the Upper Silesian Basin represent a more constrained option due to low permeability and injectivity limitations. Furthermore, the paper presents a structured framework for evaluating CO2 storage resources, integrating geological, technical, and techno-economic factors to assess storage feasibility in the Czech Republic. By consolidating fragmented studies and site-specific investigations, this review provides a national-scale perspective on CO2 storage potential, enabling identification of the most promising regions and key limitations.

Sustainable oil and gas development demands eco-friendly and cost-effective drilling fluids. Water-based drilling fluids (WBDFs) are preferred over oil-based alternatives for their lower environmental impact, but they often suffer from excessive fluid loss in permeable formations, leading to thick filter cakes, reduced mud weight, and operational delays. Conventional chemical additives mitigate this issue but pose environmental and health risks due to their toxicity and non-biodegradability. This study explores the use of biodegradable additives extracted from avocado seed (AS), rambutan shell (RS), tamarind shell (TS) and banana trunk (BT) biomass in four particle sizes of 300, 150, 75 and 32 mu m to improve filtration control in WBDFs. All four materials were crushed by ball milling and characterized by Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray (EDX). In accordance with API Spec 13A recommendations, several water-based drilling fluids (WBDFs), including reference fluid and modified fluids formulated with biodegradable additives at a fixed percentage of 3 wt% and varied particle sizes, were prepared. The rheological and filtration properties of the formulated drilling fluids were investigated by conducting industry-standard rheology and filtration tests under LPLT conditions (100 psi, 25 degrees C) and HPHT conditions (1500 psi, 75 degrees C). The results show that 32 mu m tamarind shell powder delivered the strongest performance, reducing fluid loss by 82.4% under HPHT conditions and producing the thinnest mud cake (0.33 mm); it also reduced fluid loss by 72.8% under LPLT conditions, outperforming the other biodegradable materials.

Accurate determination of the viscosity of carbon dioxide (CO 2 ) mixed with nitrogen (N 2 ) is vital for enhanced oil recovery (EOR) and carbon capture, utilisation and storage (CCUS/CCS). The determination of this important thermophysical property is usually through costly and time‐consuming experiments, which is not ideal for field recovery planning and rapid decision‐making. On the other hand, the conventional modelling relies largely on equations of state (EoS) and empirical correlations, which can be inaccurate for CO 2 –N 2 viscosity, particularly near supercritical conditions due to simplifying assumptions and limited transferability. Consequently, machine‐learning (ML) methods have gained popularity for fast and accurate prediction. Hence, in this study, ~3036 literature data points spanning pressures of 0.00127–160.99 MPa and temperature of 66.55–575.15 K were collected, cleaned and pre‐processed. Then, using pre‐processed data, several ML models, including gradient boosting (GB), extreme gradient boosting (XGBoost), LightGBM, CatBoost, random forest, three multilayer perceptron artificial neural networks (MLP‐ANNs), a stacking ensemble and a group method of data handling (GMDH) were developed. The developed models were benchmarked to predict CO 2 –N 2 viscosity as a function of temperature, pressure and the mole fractions of CO 2 –N 2 in the mixture. The analysis of the results indicate that the GB achieved the best performance with a correlation coefficient ( R 2 ) of 0.9933 ± 0.0011, root mean square error (RMSE) of 4.83 ± 0.39 μPa·s and mean absolute error (MAE) of 2.34 ± 0.10 μPa·s (mean ± 95% CI) for the test dataset, outperforming all other ML models and the utilised literature correlations. In addition, based on GMDH, two practical explicit equations within temperature ranges of T < 300 K and T > 300 K that predict the experimental viscosity with high accuracy were proposed. The sensitivity analysis also shows that the pressure has the highest positive impact, while temperature exhibited a comparably strong negative effect on viscosity.

Yield stress and plastic viscosity (PV) are key rheological parameters controlling the flow behavior, placement efficiency, and zonal isolation of oil well cement slurries. Maintaining these properties within API standards is essential for well integrity. This study investigates the effect of the chemical composition of cement, particularly silicon dioxide (SiO2), on yield stress across three systems: base cement, nano-silica (NS)-modified cement, and silica fume (SF)-modified cement. In modified systems, total SiO2 includes contributions from both cement and additives. A dataset of 224 entries was analyzed alongside 358 entries from the literature to examine the relationship between yield stress and PV. Four quartic regression models were developed using different chemical descriptors: individual oxides (IOs), alumina-ferric ratio (AFR), silicate-metallic ratio (SMR), and lime modulus (LM). Results show that in base cement, the IO model achieved the highest accuracy (R 2 = 0.98, RMSE = 2.49), whereas the LM model performed worst (R 2 = 0.80, RMSE = 8.88). For NS cement, IO, and AFR models showed strong performance (R 2 = 0.96), whereas all models performed similarly well for SF systems (R 2 approximate to 0.97). Overall, models based on IOs outperformed combined indices. These findings highlight the critical role of oxide composition, particularly SiO2, in controlling cement rheology and support incorporating detailed chemical parameters into predictive models of oil well cement performance.

Accurate determination of the viscosity of carbon dioxide (CO2) mixed with nitrogen (N-2) is vital for enhanced oil recovery (EOR) and carbon capture, utilisation and storage (CCUS/CCS). The determination of this important thermophysical property is usually through costly and time-consuming experiments, which is not ideal for field recovery planning and rapid decision-making. On the other hand, the conventional modelling relies largely on equations of state (EoS) and empirical correlations, which can be inaccurate for CO2-N-2 viscosity, particularly near supercritical conditions due to simplifying assumptions and limited transferability. Consequently, machine-learning (ML) methods have gained popularity for fast and accurate prediction. Hence, in this study, similar to 3036 literature data points spanning pressures of 0.00127-160.99 MPa and temperature of 66.55-575.15 K were collected, cleaned and pre-processed. Then, using pre-processed data, several ML models, including gradient boosting (GB), extreme gradient boosting (XGBoost), LightGBM, CatBoost, random forest, three multilayer perceptron artificial neural networks (MLP-ANNs), a stacking ensemble and a group method of data handling (GMDH) were developed. The developed models were benchmarked to predict CO2-N-2 viscosity as a function of temperature, pressure and the mole fractions of CO2-N-2 in the mixture. The analysis of the results indicate that the GB achieved the best performance with a correlation coefficient (R-2) of 0.9933 +/- 0.0011, root mean square error (RMSE) of 4.83 +/- 0.39 mu Pa.s and mean absolute error (MAE) of 2.34 +/- 0.10 mu Pa.s (mean +/- 95% CI) for the test dataset, outperforming all other ML models and the utilised literature correlations. In addition, based on GMDH, two practical explicit equations within temperature ranges of T < 300 K and T > 300 K that predict the experimental viscosity with high accuracy were proposed. The sensitivity analysis also shows that the pressure has the highest positive impact, while temperature exhibited a comparably strong negative effect on viscosity.

In recent years, surfactants as chemical-enhanced oil recovery (cEOR) agents have attracted attention to improve oil recovery from carbonate reservoirs, wherein they are able to reduce the interfacial tension (IFT) and alter the wettability. This study focuses on the application of a greenly purified surfactant from local pistachio leaves in the Kurdistan region of Iraq in EOR. The plant-sourced surfactant (bio-PLs surfactant) was fabricated using low-consumption machines and lab protocols in a sustainable and environmentally friendly way and confirmed through performing several analytical approaches (FTIR, HMNR, TGA, and DSC). EOR solutions were developed at different concentrations (500 to 3500 ppm), with 2000 ppm as the CMC based on the electrical conductivity and surface tension data. The experimental approach consists of measurements and evaluations of IFT reduction, wettability alteration, foamability, foam stability, salt tolerance, and adsorption. The obtaining results show that the bio-PLs surfactant decreased the IFT by 72.55% from 29.28 to 8.04 mN/m and altered the wettability by minimizing the contact angle (CA) from 118.4 to 84.92 degrees. The bio-PLs surfactant exhibited a stable emulsion over 15 days with 66% as the minimum reduction and maintained stability with low-salt precipitation up to the addition of 10 wt % NaCl. Moreover, the adsorption results, measured experimentally and estimated using Langmuir, Freundlich, and Tamkin isotherms, showed a sharp increase in surfactant adsorption by increasing the surfactant concentration from 500 ppm to the CMC point of 2000 ppm that was 7.032 g/mg rock, then the increasing rate was reduced by limiting the presence of rock surface-active sites and micelle formation that remains within the bulk solution. The experimental results illustrated the best fits with the Langmuir isotherm with a R 2 of 0.9631, which suggests monolayer surfactant adsorption on the rock surface. These findings of saponin extracted from pistachio leaves support its applicability in green EOR processes.

Meeting the global energy demand and sustainable development of conventional petroleum reserves necessitates the development of high-performance and environmentally friendly water-based drilling fluids (WBDF). Nevertheless, one of the major concerns of using WBDF is the fluid loss due to its penetration into the formation during the drilling operation. Various additives (fluid-loss agents) in the industry have been introduced to tackle the issue but at the cost of non-biodegradable hazardous chemicals. Due to the recent interest in environmentally friendly WBDF additives, this study looked at the suitability of the composite part of peanut shell powder (CSP). The CSP was selected because of affordability, accessibility and fibrous content. Following the American Petroleum Institute (API) guidelines for preparing the drilling mud additives, six different laboratory experiments were carried out for biodegradable drilling fluids prepared from CSP at different concentrations of 1, 2 and 3 wt

Surfactant flooding, as a chemical enhanced oil recovery (cEOR) technique, boosts oil production from oil reservoirs through lowering oil-water interfacial tension (IFT) and altering reservoir rock wettability from oil wet state to water wet. Recently, environmental concerns have encouraged researchers to turn more to use plant-based surfactant as cEOR agent. In the current study, the performance of the purified saponin from Prosopis farcta extract as a natural surfactant was evaluated for EOR applications. Initially, the validity of the purified saponin was analyzed using Fourier transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA) and proton nuclear magnetic resonance (1H NMR) to confirm saponin purification, thermal stability and structure integrity. Prior to EOR experimental tests, the critical micelle concentration (CMC) of the developed saponin was identified from the behavior of the electrical conductivity and surface tension results with increasing saponin's concentrations. Thus, a surfactant solution prepared with 3000 ppm demonstrated the best performance and thus concentration was identified as saponin's CMC point. At the same concentration, the IFT was reduced from the initial value of 29 mN/m to 6.56 mN/m and further decrease was obtained as 2.91 mN/m when NaCl was added to the solution. Meanwhile, the developed saponin at CMC range altered sandstone and carbonate rock wettability from strongly oil wet to water wet by reducing contact angles (CAs) of oil droplets to 64.57 degrees and 44.8 degrees, respectively. The findings of foamability and emulsification analyses exhibited that the Prosopis farcta saponin was capable in forming a stable foam and emulsion system. Ultimately, coreflooding test at CMC revealed that the recovery factor was enhanced by 9.65 and 11.48 % original oil in place (OOIP) from sandstone and carbonate core plugs, respectively, compared with waterflooding.

Cement composition can influence the cement slurry’s main mechanical properties, such as compressive strength (CS). This study focuses on the evaluation of the effect of cement composition materials (SiO2, Al2O3, CaO, and Fe2O3) on the slurry compressive strength along with the size effect of silica content using nano-silica (NS) and silica-fume (SF). Thus, four different models, including linear regression (LR), pure-quadratic (PQ), interaction (IA), and full quadratic (FQ), were used to predict the CS of the cement slurry using 355 datasets collected from the literature. The precision and validation of modeling were assessed using correlation coefficient (R2), root mean squared error (RMSE), mean absolute error (MAE), and scatter index (SI). Several parameters were considered when evaluating the CS of the NS and SF-modified cement slurries, such as cement chemical composition (SiO2, 18.31–23.06

ABSTRACT This study evaluates the impact of cement chemical composition on the compressive strength (CS) of cement slurries, utilizing silica fume (SF) and fly ash (FA) as additional materials. A comprehensive analysis was conducted on 317 datasets from the literature, focusing on factors including silicon dioxide (SiO₂), aluminum oxide (Al₂O₃), calcium oxide (CaO), iron oxide (Fe₂O₃), water‐to‐binder (w/b) ratio, and SF and FA content, as well as curing time and temperature. The research presents three geochemical moduli, namely, silicate modulus (SM), aluminate modulus (AM), and hydraulic modulus (HM), to assess and forecast CS. The investigation utilizing full quadratic (FQ) and cubic (CUB) models underscores the precision of prediction models corroborated by statistical metrics, such as scatter index (SI), root mean squared error (RMSE), and correlation coefficient ( R 2 ). Univariate, bivariate, and multivariate evaluations indicate that SM, AM, and HM significantly decrease input parameters while preserving or enhancing model accuracy. The ideal replacement percentages for SF and FA to maximize strength were determined to be 14.6% and 11.6%, respectively. The optimal values for SM, AM, and HM were 2.62, 1.38, and 2.21, respectively. The results establish a solid framework for optimizing cement formulations, presenting sustainable alternatives for improved mechanical performance and decreased material consumption in oil well cementing and building applications.

Drilling activity in the Kurdistan Region of Iraq is challenging because of the swelling behavior, dispersion of particles, and mechanical breakdown of shale, which is subjected to exposure to common water-based drilling fluids (WBDFs). This research examines the role of KCl-based inhibitive-WBDFs through the Gercus, Sarmord, Chia gara, Garagus, Naokelekan (CG-G-N), and Baluti Formations. Inhibitive-WBDFs were developed by mixing several additives in deionized water (DW) along with 1 and 2 wt % KCl, which were subjected to rheological testing, linear swelling measurements (LSM), hot-rolling dispersion, filtrations, and bulk hardness. The results demonstrate that the fluid loss of the drilling fluid containing 2 wt % KCl (WBDF-KCl-2%) used with the Baluti Formation is the lowest compared with other drilling fluids, which are 4.8 and 9 mL for the LPLT and HPHT, respectively. Meanwhile, the Sarmord Formation exhibited the highest filtration rates of 8.5 and 15.9 mL at LPLT and HPHT conditions, respectively. The Gercus Formation, which mostly contains smectite and palygorskite along with a cation exchange capacity (CEC) of 6.5 mequiv/100 g, produced severe swelling of 6.23-6.45% LSM and low bulk hardness of 130-140 psi. Meanwhile, the Baluti Formation, containing the vermiculite and glauconitic clay types with a CEC of 1.75 mequiv/100 g, exhibited the lowest shale swelling rate of 0.16%, 91.51% recovery, and 250 psi bulk hardness when exposed to WBDF-KCl-1%. These results demonstrate that the optimum inhibition depends on fluid formulation, shale mineralogy, and CEC. Although KCl at a low concentration of 1-2 wt% was highly effective in minimizing shale swelling, its role was not universal for all study formations. Thus, it can be stated that the formation response to KCl-based WBDFs affects the inhibition efficiency for swelling prevention, which strongly depends on mineralogy and CEC.

Drilling fluids are vital in oil and gas well operations, ensuring borehole stability, cutting removal, and pressure control. However, fluid loss into formations during drilling can compromise formation integrity, alter permeability, and risk groundwater contamination. Water-based drilling fluids (WBDFs) are favored for their environmental and cost-effective benefits but often require additives to address filtration and rheological limitations. This study explored the feasibility of using vegetable waste, including pumpkin peel (PP), courgette peel (CP), and butternut squash peel (BSP) in fine (75 μm) and very fine (10 μm) particle sizes as biodegradable WBDF additives. Waste vegetable peels were processed using ball milling and characterized via FTIR, TGA, and EDX. WBDFs, prepared per API SPEC 13A with 3 wt% of added additives, were tested for rheological and filtration properties. Results highlighted that very fine pumpkin peel powder (PP_10) was the most effective additive, reducing fluid loss and filter cake thickness by 43.5% and 50%, respectively. PP_10 WBDF maintained mud density, achieved a pH of 10.52 (preventing corrosion), and enhanced rheological properties, including a 50% rise in plastic viscosity and a 44.2% increase in gel strength. These findings demonstrate the remarkable potential of biodegradable vegetable peels as sustainable WBDF additives.

This study conducts a comparative analysis between hydrophobic nanosilica (HNS) and potassium chloride (KCl), a widely used shale inhibitor, to better understand how HNS can effectively manage water and shale interactions by restricting mud filtration into the formation. Due to their small size and optimal interfacial properties, nanoparticles emerge as remarkable solutions for addressing this issue. In this work, shale samples were collected from the Kolosh Formation in the Kurdistan Region of Iraq, known for being one of the most challenging formations to drill. Investigations into the properties of drilling fluid were conducted using low pressure and low temperature (LPLT) and high pressure high temperature (HPHT) filter press, alongside analyzing rheological properties at three different temperatures (25, 50 and 75 degrees C). In addition, the impact of the HNS on clay swelling was examined using the liner swelling meter (LSM) test, shale dispersion test (SDT) and capillary suction time (CST) test. The obtaining results revealed that the shale hydration in the drilling fluids was reduced 24.36-15.53% and the shale recovery at high temperatures was improved from 80.2% to 94% by adding 0.4 wt% HNS. Furthermore, HNS demonstrated improved clay suspension in the CST test wherein the suspension time reduced from 303 to 80 sec at the same HNS concentration. Utilizing HNS effectively reduced clay swelling in all experiments and enhanced the rheological properties of the mud, showcasing stability across a range of temperatures and significantly reducing the formation of filter cake and fluid loss. As is obvious, KCl based drilling fluids are prohibited in several parts in the word due to its negative impact on the environment and subsurface activities; thus, it can be substituted by HNS as an active shale inhibitor additive.

Understanding key material properties such as compressive strength (CS) is crucial for improving cement production. Its chemical composition significantly influences the CS of cement. This study investigates the impact of the primary cement constituents such as SiO₂, Al₂O₃, CaO, and Fe₂O₃ along with varying dosages of fly ash (FA) and silica fume (SF) on the compressive strength of cement slurries. Four predictive models with varying complexities were employed: linear regression, pure-quadratic, interaction (IA), and full quadratic (FQ). These models, previously validated for concrete and mortar, were applied to a dataset of 317 records from prior research. Model performance was assessed using correlation coefficient (R2), root mean squared error, mean absolute error, and scatter index. Key input parameters included cement chemical composition (SiO₂: 13.57–22.62

Injecting surfactant by means ofchemical enhanced oilrecovery(cEOR) has acquired predominant attention in improving oil recoveryby changing either fluid/rock and/or fluid/fluid interaction due toion-pair forming and/or surfactant adsorption on the rock surface.As the main surfactant role in EOR, IFT reduction refers to adsorbingof surfactant molecules on the residual oil/water interface, whichcauses an increase in capillary number; as a result, trapped oil dropsin porous media get free and start to move through the pore spacetoward the production well. The toxic nature, excessive cost, andenvironmental issues are the obvious limitations in applying the chemicalsurfactants in EOR, hence, looking for a less-expensive and eco-friendlytype of surfactant has become a significant task to researchers tostudy the natural surfactant as an alternative to chemical surfactants.A deep understanding about the classification of natural surfactants,fabrication methods, and the difference between each class is crucialto propose a new plant-derived natural surfactant. This study triedto review up-to-date published studies related to the natural surfactanttypes and prepare a comprehensive catalog respective to natural surfactantthat helps researchers with regard to future work in natural surfactantapplication in EOR. In addition, comparisons of each class performanceand the impact of nanoparticles and the salinity on them in reducingIFT, altering wettability, and improving the recovery factor havebeen investigated. It had been concluded that natural surfactant canbe produced from different plant parts (leaf, root, steam, fruit,and seed) based on the fabrication method. Natural surfactants synthesizedfrom seed oil are stronger, compared with those extracted from theplant part (i.e., IFT reduction by 98%). Generally, injecting naturalsurfactants expressed low to high performance in improving the ultimateoil recovery from 2% to 40% original oil in place (OOIP).

Aphron drilling fluids (ADFs) are finding increasing application in science engineering fields because of their distinctive characteristic. As the interest in the application of aprons-based fluids continues to grow, there is a decisive need to advance a deeper understanding of the factors affecting their behavior and properties, especially for successful petroleum industries, such as drilling depleted reservoirs and production. This study delves into investigating the density, rheological behavior and properties, filtration properties, bubble size, and their distribution of Aphrons-drilling fluids utilizing two ionic surfactants. Sodium Dodecyl Benzene Sulfate (SDBS) as an anionic surfactant, Cetyl Trimethyl Ammonium Bromide (CTAB) as a cationic surfactant, described as environmentally friendly, in Iraqi depleted reservoirs drilling. With an emphasis on the concentrations balance between Aphron generator (SDBS) and Aphron stabilizer (CTAB), the study analyzes the behavior and characteristics of Aphron drilling fluid. The investigation demonstrates that adding SDBS and CTAB reduces system density by 28%, owing to microbubbles production which is utilized with near-balance drilling. Rheological testing reveals that shear-thinning behavior in all Aphron samples improved, and the presence of SDBS affects the fluid's internal friction, gel strength, and short-term gel structure. Filtering control characteristic study demonstrates that the presence of microbubbles significantly minimizes fluid loss by 33% with 0.20% SDBS during filtering. Bubble size and dispersion studies demonstrate that 0.20% SDBS concentration, along with 0.30% CTAB, gives the best microbubble size and distribution. These findings suggest that Aphron fluids will be a promising innovation in petroleum industries, during actual drilling operations in Iraqi depleted oilfields.

This study explores the effect of cement chemical composition on the compressive strength (CS) of pure cement, cement modified with Nano Silica (NS), and Silica Fume (SF) across various mix proportions, curing times, and temperatures. Three new parameters, Silicate Modulus (SM), Aluminate Modulus (AM), and Hydraulic Modulus (HM), were introduced to evaluate cement composition's impact on CS. SM combines SiO2, Al2O3, and Fe2O3; AM integrates Al2O3 and Fe2O3; and HM includes CaO, SiO2, Al2O3, and Fe2O3. Using 355 datasets, two mathematical models, Cubic (CUB) and linear and inverse (L&I), predicted CS, considering factors like cement composition, water-to-binder ratio, NS and SF content, curing time, and temperature. Statistical tools such as R2, RMSE, MAE, and SI validated model accuracy. The study assessed three scenarios: (1) multi-variate analysis of individual cement oxides; (2) bi-variate analysis using SM and AM, and (3) mono-variate analysis using HM. Introducing SM, AM, and HM improved model accuracy and reduced input parameters. Optimal NS and SF replacement percentages were 4.64% and 14.6%, respectively. SM, AM, and HM optimal values were 2.62, 1.38, and 2.21. Although initial costs increase with these replacements, they offer long-term benefits and align with sustainable construction practices.

Drilling fluid is crucial for oil and gas well drilling operations, serving key functions such as facilitating the removal of drill cuttings, maintaining borehole stability and controlling formation pressures. When the drilling fluid is lost into formations, it can alter the formation's integrity, contaminate groundwater and cause permeability damage. In addition, environmental concerns arise from the waste produced during drilling activities, particularly when discarded drilling fluids contain hazardous substances like heavy metals. This study explores the potential of integrating ultrafine potato powder (PP) into water-based drilling fluids (WBDFs) as environmentally friendly additives. Several analytical techniques including X-ray fluorescence (XRF), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electronic microscope (SEM) and differential scanning calorimetry (DSC) were used to comprehensively characterize the prepared PPs. The study included API and HPHT filtration test, permeability plugging test and rheological evaluations of drilling fluids, assessing parameters such as filter loss, filter cake, apparent viscosity, plastic viscosity, yield point and gel strength under varied conditions of different particle sizes of PP, concentrations of PP, and temperature and pressure measurements. The obtaining results emphasize PP's potential to enhance the wellbore stability and reduce the fluid loss, the filtration of water or oil into the permeable formation, achieving 43% reduction in the filtration rate and 70% reduction in the filter cake thickness. Adding 0.5wt.% ultrafine PP improved the maximum gel strength to 32.2lb/100 ft2, while the same concentration and particle size raised the plastic viscosity from 3 to 6.8cP, which subsequently dropped to 6cP in high temperature conditions. PP performed better compared with the reference fluid in improving the thinning behavior of the drilling fluids. Moreover, permeability plugging tests confirm that adding PP effectively lowered the filtration rate, with higher concentrations achieving greater reductions over time. These findings suggest that PP holds promise as an effective additive for drilling fluids, contributing to enhanced drilling efficiency, improved wellbore stability and a reduced likelihood of instability and lost circulation. The characterization and rheological analysis of PP biodegradable drilling fluids provide valuable insights for optimizing fluid formulations, tailoring them to specific operational conditions, and achieving a balance between fluidity, wellbore stability, and cuttings transport. This research highlights the potential of PP as a sustainable and efficient solution in the realm of drilling fluid additives.