Real-Time Prediction of Rate of Penetration in S-Shape Well Profile Using Artificial Intelligence Models.

Rate of penetration (ROP) is defined as the amount of removed rock per unit area per unit time. It is affected by several factors which are inseparable. Current established models for determining the ROP include the basic mathematical and physics equations, as well as the use of empirical correlations. Given the complexity of the drilling process, the use of artificial intelligence (AI) has been a game changer because most of the unknown parameters can now be accounted for entirely at the modeling process. The objective of this paper is to evaluate the ability of the optimized adaptive neuro-fuzzy inference system (ANFIS), functional neural networks (FN), random forests (RF), and support vector machine (SVM) models to predict the ROP in real time from the drilling parameters in the S-shape well profile, for the first time, based on the drilling parameters of weight on bit (WOB), drillstring rotation (DSR), torque (T), pumping rate (GPM), and standpipe pressure (SPP). Data from two wells were used for training and testing (Well A and Well B with 4012 and 1717 data points, respectively), and one well for validation (Well C) with 2500 data points. Well A and Well B data were combined in the training-testing phase and were randomly divided into a 70:30 ratio for training/testing. The results showed that the ANFIS, FN, and RF models could effectively predict the ROP from the drilling parameters in the S-shape well profile, while the accuracy of the SVM model was very low. The ANFIS, FN, and RF models predicted the ROP for the training data with average absolute percentage errors (AAPEs) of 9.50%, 13.44%, and 3.25%, respectively. For the testing data, the ANFIS, FN, and RF models predicted the ROP with AAPEs of 9.57%, 11.20%, and 8.37%, respectively. The ANFIS, FN, and RF models overperformed the available empirical correlations for ROP prediction. The ANFIS model estimated the ROP for the validation data with an AAPE of 9.06%, whereas the FN model predicted the ROP with an AAPE of 10.48%, and the RF model predicted the ROP with an AAPE of 10.43%. The SVM model predicted the ROP for the validation data with a very high AAPE of 30.05% and all empirical correlations predicted the ROP with AAPEs greater than 25%.

A New Model for Predicting Rate of Penetration Using an Artificial Neural Network.

The drilling rate of penetration (ROP) is defined as the speed of drilling through rock under the bit. ROP is affected by different interconnected factors, which makes it very difficult to infer the mutual effect of each individual parameter. A robust ROP is required to understand the complexity of the drilling process. Therefore, an artificial neural network (ANN) is used to predict ROP and capture the effect of the changes in the drilling parameters. Field data (4525 points) from three vertical onshore wells drilled in the same formation using the same conventional bottom hole assembly were used to train, test, and validate the ANN model. Data from Well A (1528 points) were utilized to train and test the model with a 70/30 data ratio. Data from Well B and Well C were used to test the model. An empirical equation was derived based on the weights and biases of the optimized ANN model and compared with four ROP models using the data set of Well C. The developed ANN model accurately predicted the ROP with a correlation coefficient (R) of 0.94 and an average absolute percentage error (AAPE) of 8.6%. The developed ANN model outperformed four existing models with the lowest AAPE and highest R value.

Real-Time Prediction of Rheological Properties of Invert Emulsion Mud Using Adaptive Neuro-Fuzzy Inference System.

Tracking the rheological properties of the drilling fluid is a key factor for the success of the drilling operation. The main objective of this paper is to relate the most frequent mud measurements (every 15 to 20 min) as mud weight (MWT) and Marsh funnel viscosity (MFV) to the less frequent mud rheological measurements (twice a day) as plastic viscosity (PV), yield point (YP), behavior index (n), and apparent viscosity (AV) for fully automating the process of retrieving rheological properties. The adaptive neuro-fuzzy inference system (ANFIS) was used to develop new models to determine the mud rheological properties using real field measurements of 741 data points. The data were collected from 99 different wells during drilling operations of 12 » inches section. The ANFIS clustering technique was optimized by using training to a testing ratio of 80% to 20% as 591 data points for training and 150 points, cluster radius value of 0.1, and 200 epochs. The results of the prediction models showed a correlation coefficient (R) that exceeded 0.9 between the actual and predicted values with an average absolute percentage error (AAPE) below 5.7% for the training and testing data sets. ANFIS models will help to track in real-time the rheological properties for invert emulsion mud that allows better control for the drilling operation problems.

Newly Developed Correlations to Predict the Rheological Parameters of High-Bentonite Drilling Fluid Using Neural Networks.

High-bentonite mud (HBM) is a water-based drilling fluid characterized by its remarkable improvement in cutting removal and hole cleaning efficiency. Periodic monitoring of the rheological properties of HBM is mandatory for optimizing the drilling operation. The objective of this study is to develop new sets of correlations using artificial neural network (ANN) to predict the rheological parameters of HBM while drilling using the frequent measurements, every 15 to 20 min, of mud density (MD) and Marsh funnel viscosity (FV). The ANN models were developed using 200 field data points. The dataset was divided into 70:30 ratios for training and testing the ANN models respectively. The optimized ANN models showed a significant match between the predicted and the measured rheological properties with a high correlation coefficient (R) higher than 0.90 and a maximum average absolute percentage error (AAPE) of 6%. New empirical correlations were extracted from the ANN models to estimate plastic viscosity (PV), yield point (YP), and apparent viscosity (AV) directly without running the models for easier and practical application. The results obtained from AV empirical correlation outperformed the previously published correlations in terms of R and AAPE.

Exposure Time Impact on the Geomechanical Characteristics of Sandstone Formation during Horizontal Drilling.

The rock geomechanical properties are the key parameters for designing the drilling and fracturing operations and for programing the geomechanical earth models. During drilling, the horizontal-section drilling fluids interact with the reservoir rocks in different exposure time, and to date, there is no comprehensive work performed to study the effect of the exposure time on the changes in sandstone geomechanical properties. The objective of this paper is to address the exposure time effect on sandstone failure parameters such as unconfined compressive strength, tensile strength, acoustic properties, and dynamic elastic moduli while drilling horizontal sections using barite-weighted water-based drilling fluid. To simulate the reservoir conditions, Buff Berea sandstone core samples were exposed to the drilling fluid (using filter press) under 300 psi differential pressure and 200 °F temperature for different exposure times (up to 5 days). The rock characterization and geomechanical parameters were evaluated as a function of the exposure time. Scratch test was implemented to evaluate rock strength, while ultrasonic pulse velocity was used to obtain the sonic data to estimate dynamic elastic moduli. The rock characterization was accomplished by X-ray diffraction, nuclear magnetic resonance, and scanning electron microscope. The study findings showed that the rock compression and tensile strengths reduced as a function of exposure time (18% and 19% reduction for tensile strength and unconfined compression strength, respectively, after 5 days), while the formation damage displayed an increasing trend with time. The sonic results demonstrated an increase in the compressional and shear wave velocities with increasing exposure time. All the dynamic elastic moduli showed an increasing trend when extending the exposure time except Poisson's ratio which presented a constant behavior after 1 day. Nuclear magnetic resonance results showed 41% porosity reduction during the five days of mud interaction. Scanning electron microscope images showed that the rock internal surface topography and internal integrity changed with exposure time, which supported the observed strength reduction and sonic variation. A new set of empirical correlations were developed to estimate the dynamic elastic moduli and failure parameters as a function of the exposure time and the porosity with high accuracy.

Properties and Performance of Oil Well Slurry and Cement Sheath Incorporating Nano Silica: A Review.

The oil well cementing job is the operation in which a cement paste is pumped to fill the annulus behind the casing. Inclusion of nanomaterials in oil well cement results in improving the cement properties. This paper provides a comprehensive overview of incorporating nanosilica into oil well cement, addressing various aspects of the nanosilica manufacturing process, dispersion challenges, the impact on cement hydration and properties, as well as the operational challenges. The addition of nanosilica is found to enhance cement properties such as hydration rate, compressive strength at low temperatures, and resistance to deterioration at high temperatures. However, challenges arise, including increased viscosity and the need for higher water content. Dispersion of nanosilica into cement slurry remains a difficulty, compounded by the high manufacturing cost, limiting its practical application. The paper recommends further research to improve nanosilica dispersion, explore cost-effective raw materials, and overcome operational challenges for broader utilization in oil well cementing.

Evaluating the Effect of Claytone-EM on the Performance of Oil-Based Drilling Fluids.

This study provides a detailed characterization and evaluation of Claytone-EM as a rheological additive to enhance the performance of oil-based drilling fluids (OBDFs) under high-pressure, high-temperature (HPHT) conditions. It also offers a comparative evaluation of the effectiveness of Claytone-EM with an existing organoclay, analyzing their mineral and chemical compositions, morphologies, and particle sizes. A series of experiments are performed to evaluate Claytone-EM's influence on crucial drilling mud properties, such as mud density, electrical stability, sagging tendency, rheology, viscoelastic properties, and filtration properties, to formulate a stable and high-performing OBDF. Results indicated that Claytone-EM had no significant impact on mud density but remarkably enhanced emulsion stability. Claytone-EM effectively mitigated sagging issues under both static and dynamic conditions, leading to improvements in the plastic viscosity (PV), yield point (YP), apparent viscosity (AV), and YP/PV ratio. The PV, YP, AV, and YP/PV ratios were improved by 11, 85, 28, and 66% increments, respectively, compared with those of the drilling fluid formulated with MC-TONE. The addition of Claytone-EM resulted in enhancing gel strength and improving the filtration properties of the drilling fluid. The filtration volume was reduced by 2% from 5.0 to 4.9 cm3, and the filter cake thickness had a 13% reduction from 2.60 to 2.26 mm. These findings highlight Claytone-EM as a valuable additive for enhancing OBDF performance, particularly under challenging HPHT conditions. Its ability to provide emulsion stability, reduce static and dynamic sag, and control filtration holds the potential to enhance drilling operations, minimize downtime, and bolster wellbore stability. This study acknowledges certain limitations, including its temperature range, which could benefit from exploration at extreme temperatures. Additionally, the absence of flow experiments limits a comprehensive understanding of sag effects, and further research and field-scale evaluations are recommended to validate and optimize the application of Claytone-EM in OBDFs.

Optimizing hematite filter cake treatment using reducing agents.

In drilling operations, the formation of a filter cake is crucial for well stability, but its removal post-drilling is essential to restore rock formation productivity. This study focuses on hematite-based filter cakes and investigates factors influencing their solubility and removal, addressing a significant knowledge gap in the field. The research methodology involves examining the effects of various factors, including types and concentrations of reducing agents, temperature, particle size, and treatment duration, on the dissolution process. Notably, Nuclear Magnetic Resonance (NMR) tests are employed to assess the treatment's impact on core porosity. Among the diverse reducing agents examined, ferrous chloride emerges as the optimal choice for effectively enhancing hematite solubility. Particularly, a composite solution of ferrous chloride (10 wt.%) and hydrochloric acid (6 wt.%), was highly efficient demonstrated by exhibiting rapid solubilization of hematite filter cakes. A removal efficiency of approximately 99%, with a parallel enhancement in core permeability was achieved. NMR tests reveal the treatment's success in reinstating the porosity system, which had undergone reduction due to drilling fluid particles. Crucially, the solution exhibits a considerably lower corrosion rate than concentrated hydrochloric acid, highlighting its potential to mitigate environmental concerns while ensuring efficient filter cake removal. The findings of this research provide valuable insights into optimizing post-drilling operations, balancing environmental sustainability and operational efficiency. The identified composite solution offers a promising approach to efficient filter cake removal while mitigating environmental concerns associated with corrosion. Overall, this study contributes to advancing the understanding and practice of well productivity enhancement in the oil and gas industry.

Investigating the efficacy of novel organoclay as a rheological additive for enhancing the performance of oil-based drilling fluids.

Oil-based drilling fluids (OBDFs) are extensively used in the drilling industry due to their superior performance in challenging drilling conditions. These fluids control wellbore stability, lubricate the drill bit, and transport drill cuttings to the surface. One important component of oil-based drilling fluids is the viscosifier, which provides rheological properties to enhance drilling operations. This study evaluates the effectiveness of Claytone-IMG 400, a novel rheological agent, in enhancing the performance of OBDFs under high-pressure and high-temperature (HPHT) conditions. A comparative analysis was conducted with a pre-existing organoclay (OC) to assess the improvements achieved by Claytone-IMG 400. The OCs were analyzed using X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), and particle size distribution (PSD) to identify their mineral and chemical compositions, morphologies, and particle sizes. The drilling fluid density, electrical stability, sagging tendency, rheological properties, viscoelastic properties, and filtration properties were studied to formulate a stable and high-performance drilling fluid. The results confirmed that the novel OC does not affect the drilling fluid density but enhances the emulsion stability with a 9% increment compared with the drilling fluid formulated with MC-TONE. The sagging experiments showed that Claytone-IMG 400 prevented the sagging issues in both static and dynamic conditions. Also, Claytone-IMG 400 improved the plastic viscosity (PV), yield point (YP), and apparent viscosity (AV). The PV, YP, and AV were improved by 30%, 38%, and 33% increments respectively compared with the drilling fluid formulated with MC-TONE. The YP/PV ratio increased with a 6% increment from 1.12 to 1.19. Moreover, the gel strength (GS) was significantly increased, and the filtration properties were enhanced. The filtration volume was reduced by 10% from 5.0 to 4.5 cm3, and the filter cake thickness had a 37.5% reduction from 2.60 to 1.89 mm. The novelty of this study is highlighted by the introduction and evaluation of Claytone-IMG 400 as a new rheological additive for safe, efficient, and cost-effective drilling operations. The results indicate that Claytone-IMG 400 significantly improves the stability and performance of OBDFs, thereby reducing wellbore instability and drilling-related problems.

Evaluation of using micronized saudi calcite in ilmenite-weighted water-based drilling fluid.

A high-density water-based drilling fluid (WBDF) is crucial for maintaining wellbore stability, controlling formation pressures, and optimizing drilling performance in challenging subsurface conditions. In the present research, the effect of micronized calcium carbonate (calcite), extracted from the Aruma formation outcrop, is evaluated as one of the additives that could be added to the ilmenite-weighted WBDF to enhance and optimize its properties. Various concentrations of Calcite microparticles were introduced into identical fluid formulations to assess their impact. The concentrations ranged from 0, 10, 20, to 30 lb/bbl, providing a comprehensive examination of the effects of calcite microparticles across a spectrum of concentrations within the fluid. The results highlighted that adding Barite microparticles to the WBDF revealed a notable enhancement in rheological properties. Specifically, the yield point demonstrated an increase of 37%, 37%, and 11% for concentrations of 10, 20, and 30 lb/bbl of calcite, respectively. Equally significant, high-pressure-high-temperature (HPHT) filtration analysis indicated a considerable enhancement for the fluids containing calcite microparticles. A reduction of 14.5%, 24.6%, and 13% were observed in HPHT filtrate for concentrations of 10 lb/bbl, 20 lb/bbl, and 30 lb/bbl respectively. Simultaneously, there is a reduction in filter cake thickness by 20%, 40%, and 20%, respectively. No ilmenite settling was observed in the sample containing 20 lb/bbl of calcite, unlike the other concentrations. These diverse results strongly suggest that the optimal concentration for calcite microparticles is 20 lb/bbl. The combined utilization of the optimal concentration of calcite microparticles alongside the established additives proves to be an effective strategy for optimizing the ilmenite-weighted WBDF performance in terms of both thermal stability and rheological behavior.

Foamed Cement Applications in Oil Industry Based on Field Experience: A Comprehensive Review.

Foam cement is a versatile cementing material that has found numerous applications in the oil and gas industry. As research continues to advance and improve the properties of foam cement, it is likely that we will see an increased use of this material in the years to come. This review aims to summarize the current state of the art and the latest developments in the utilization of foam cement in oil fields. The study focuses on the key benefits of foam cement, including its light weight, excellent flow properties, ability to maintain its structural integrity over time, and high compressive strength. It also examines its various applications in oil field operations, such as cementing against fragile formations, well abandonment, zonal isolation, cementing offshore wells, and well remedial cementing. Furthermore, the paper evaluates the various factors that influence the performance of foam cement, such as the mixing design, foam structure, and stability. In addition, the methods for evaluating the foamed cementing job and the integrity of the formed cement sheath are also presented. The review also highlights the current challenges and limitations of foam cement technology that should be considered when using foamed cement in oil field applications and discusses the future directions for its development and optimization. This review provides a comprehensive overview of the applications of foam cement in oil fields and will be of great interest to engineers, researchers, and practitioners in the oil and gas industry.

Real-Time Prediction of Petrophysical Properties Using Machine Learning Based on Drilling Parameters.

The prediction of rock porosity and permeability is crucial for assessing reservoir productivity and economic feasibility. However, traditional methods for obtaining these properties are time-consuming and expensive, making them impractical for comprehensive reservoir evaluation. This study introduces a novel approach to efficiently predict rock porosity and permeability for reservoir assessment by leveraging real-time machine learning models. Utilizing readily available drilling parameters, this approach offers a cost-effective alternative to traditional time-consuming methods to predict formation petrophysical parameters in real-time. The data set used in this study was collected from two vertical wells located in the Middle East. It encompasses drilling parameters such as the rate of penetration (ROP), gallons per minute (GPM), revolutions per minute (RPM), strokes per minute (SPP), torque, and weight on bit (WOB), along with the corresponding measurements of porosity (ϕ) and permeability (k) obtained through core analysis. Three machine learning models, namely, decision trees (DTs), random forest (RFs), and support vector machines (SVMs), were employed and evaluated for their effectiveness in predicting porosity and permeability. The results demonstrate promising performance across the different data sets. All three models achieved correlation coefficients (R) higher than 0.91 in predicting porosity. The RF model exhibited accurate predictions of permeability, achieving R values surpassing 0.92 in the various data sets. While the DT model displayed slightly lower performance, with the R-value decreasing to 0.88 in the testing data set, the SVM model suffered from overfitting, with R values dropping to 0.83 in the testing data set. The novelty of this work lies in the successful application of machine learning models to the real-time prediction of reservoir properties, providing a practical and efficient solution for the oil and gas industry. By achieving correlation coefficients exceeding 0.91 and showcasing the models' efficacy in a dynamic testing data set, this study paves the way for improved decision-making processes and enhanced exploration and production activities. The innovative aspect lies in the utilization of drilling parameters for timely and cost-effective estimation, transforming conventional reservoir evaluation methods.

Impact of Eco-Friendly Drilling Additives on Foaming Properties for Sustainable Underbalanced Foam Drilling Applications.

Underbalanced foam drilling stands out as a drilling technique acclaimed for its capacity to enhance safety and efficiency in operations. Utilizing foams as drilling fluids offers several benefits over traditional methods, including lower density, diminished formation damage, and augmented borehole stability. However, the persistent challenge of sustaining foam stability in demanding conditions, particularly amid elevated water salinity and alkaline environments, remains a critical issue. Current literature lacks comprehensive insights into foam stability under such specific circumstances, raising concerns about the practicality of numerous reported foaming agents in field applications. This study aims to fill this knowledge void to align with industry standards. With a heightened focus on sustainability due to mounting environmental considerations, the research explores the use of an eco-friendly surfactant, ammonium alcohol ether sulfate (AAES). Additionally, the investigation delves into the impact of environmentally friendly drilling additives-polyanionic cellulose (PAC), carboxymethyl cellulose (CMC), and starch-on the stability of bulk foam under mildly alkaline conditions. Employing a dynamic foam analyzer, diverse foam properties of AAES foams were assessed, encompassing stability, foamability, and bubble structure. The results demonstrated that the optimal concentrations of the tested additives, in the order of PAC > CMC > starch, significantly prolonged the half-life of the AAES foam bubbles. The introduction of PAC and CMC additives elevated the viscosity of AAES foaming solutions, enhancing the liquid retention within the foam structure. In contrast, starch addition exerted no influence on the solution viscosity and did not impede liquid drainage, although it did reduce bubble coalescence. Furthermore, the PAC- and CMC-based AAES foams manifested as considerably wetter foams with a rounded bubble structure, while the starch-based AAES foam exhibited a dry foam characterized by a distinct polyhedral bubble structure. These findings offer valuable insights into the potential application of the AAES surfactant in foam drilling, showcasing its efficacy in improving foam stability and contributing to the evolution of eco-friendly drilling practices.

Synthetic Clay Application to Reduce the Segregation of Barite-Based Oil-Well Cement.

In the oil and gas industry, cement segregation is a significant concern that can have disastrous consequences, such as the failure of cement. The change of hardened cement's properties is observed, resulting in a decrease in its strength and an increase in its permeability. Therefore, providing some solutions to prevent this is crucial. The objective of this study is to assess the efficacy of synthetic clay in mitigating the problem of segregation in cement having barite. Six concentrations of synthetic clay were used to prepare six heavy-weighted cement samples with a high density of 18 lb/gal using the barite weighting material. The approaches of density distribution and nuclear magnetic resonance (NMR) were employed to characterize the heterogeneity in the hardened cement samples with the aim of identifying the potential of cement segregation. Then, the optimum concentration of the synthetic clay was selected and its effects on the rheological, strength, petrophysical, and elastic properties were evaluated and compared with the properties of the base cement (without synthetic clay). The results showed that 0.4% by weight of cement (BWOC) synthetic clay was the optimum concentration, which yielded the minimum cement segregation as represented by a 61% reduction in the density variation compared to the control specimen. The results obtained from the NMR technique validated the findings of the density distribution method, indicating that the porosity distribution of the synthetic clay cement with a concentration of 0.4% BWOC exhibited uniformity across its top, middle, and bottom sections, with a slight deviation window, while the porosity distribution of the control cement specimen displayed noticeable variation. Moreover, the synthetic clay had better properties than the control cement specimen. For example, the rheological properties were improved as represented by a 22% reduction in plastic viscosity and 42 and 11% increase in the yield point and gel strength, respectively. Compared to the base cement, the compressive and tensile strength were increased by 39 and 43%. The synthetic clay decreased the permeability and porosity by 73 and 24%, respectively. The synthetic clay enhanced the elastic properties as represented by a 1.5% reduction in Young's modulus and a 1.3% increase in Poisson's ratio compared to the base cement sample.

Perlite incorporation for sedimentation reduction and improved properties of high-density geopolymer cement for oil well cementing.

Portland cement (PC) is known for its environmental and technical concerns and massive energy consumption during manufacturing. Geopolymer cement is a promising technology to totally replace the use of PC in the oil and gas industry. Although geopolymers are widely used in the construction industry, it is yet to see a full-scale application in the petroleum industry. High-density geopolymer cement development is essential to substitute heavy-weight Portland cement slurries for high pressure well cementing applications. Sedimentation issue is associated with high-density cement slurries which use high specific gravity solids such as weighting materials. This problem causes heterogeneity and density variation along the cemented sections. The main target of this work is to evaluate the use of perlite powder to address the sedimentation issue in the heavy weight geopolymer systems. Hematite-based Class F fly ash (FFA) geopolymer cement slurries with perlite concentrations of 0, 1.5, and 3% by weight of binder (BWOB) were prepared. The sedimentation problem was investigated using three techniques: API method, nuclear magnetic resonance (NMR), and computed tomography (CT) scan. The perlite effects on different geopolymer properties such as unconfined compressive strength (UCS), porosity, elastic and rheological properties were assessed. The results proved that perlite incorporation in high-density hematite-based FFA geopolymer significantly reduced sedimentation issue by increasing yield point and gel strength. NMR and CT scan showed that perlite decreases porosity and density variation across the geopolymer samples. The UCS increased with increasing perlite percentage from 0 to 3%. The measured Young's moduli (YM) and Poisson's ratios (PR) showed that the developed perlite based geopolymer systems are considered more flexible than Class G cement systems. It was found that the optimum perlite concentration is 3% BWOB for tackling sedimentation and developing a slurry with acceptable mixability and rheological properties.

Impact of Pressure and Temperature on Foam Behavior for Enhanced Underbalanced Drilling Operations.

Foam, a versatile underbalanced drilling fluid, shows potential for improving the drilling efficiency and reducing formation damage. However, the existing literature lacks insight into foam behavior under high-pH drilling conditions. This study introduces a novel approach using synthesized seawater, replacing the conventional use of freshwater on-site for the foaming system's liquid base. This approach is in line with sustainability objectives and offers novel perspectives on foam stability under high-pH conditions. Experiments, conducted with a high-pressure, high-temperature (HPHT) foam analyzer, investigate how pressure and temperature affect foam properties. The biodegradable foaming agent ammonium alcohol ether sulfate (AAES) is employed. Results demonstrate that the pressure significantly impacts foam stability. Increasing pressure enhances stability, reducing decay rates and promoting uniform bubble sizes, especially at lower temperatures. This highlights foam's capacity to withstand high-pressure conditions. Conversely, the temperature plays a substantial role in foam decay, particularly at elevated temperatures (75 and 90 °C). Decreased liquid viscosity accelerates the liquid drainage and foam decay. While pressure mainly influences the AAES foam stability at temperatures up to 50 °C, temperature becomes the dominant factor at higher temperatures. Temperature's impact on foamability is minimal under constant pressure, maintaining consistent gas volume for maximum foam height. However, foam stability is sensitive to temperature variations, with increasing temperature leading to a more significant bubble size increase gradient. These findings stress the importance of considering temperature effects in foam drilling, particularly in deep and high-temperature environments. AAES foam exhibits stability at lower temperatures, making it suitable for surface and intermediate drilling. Understanding temperature-induced changes in foam structure and bubble size is essential for optimizing performance in high-temperature and deep drilling scenarios.

Micronized calcium carbonate to enhance water-based drilling fluid properties.

Advanced drilling technique requires competent drilling fluids. This study tests micronized calcium carbonate (CaCO3) as a water-based drilling fluid (WBDF) additive. CaCO3 microparticles were extracted from Aruma formation outcrop and studied for structural, colloidal stability, morphology, and particle size distribution. WBDF systems were prepared with varying quantities of CaCO3 microparticles, including 0, 15, 30, and 45 lb/bbl, respectively. The addition of CaCO3 microparticles was investigated in terms of the rheological, high pressure-high temperature (HPHT) filtration, barite sagging, density, and pH. The results showed that CaCO3 microparticles are stable at a pH greater than 8. Moreover, fluid containing CaCO3 microparticles exhibited an enhancement in rheological properties. The yield point increased by 29%, 34%, and 37% for 15, 30, and 45 lb/bbl of CaCO3 respectively. In addition, the HPHT filtration also showed that CaCO3 has a significant improvement in both filtration loss and filter cake thickness. The filter cake thickness decreased by 17%, 40%, and 65% at 15, 30, and 45 lb/bbl of CaCO3 respectively. Static and dynamic sag maintained in a safe range at 30 lb/bbl of CaCO3 microparticles. This study showed that using CaCO3 microparticles along with conventional fluid additives improved the thermal stability and rheological properties of drilling fluid.

Mixed Micromax and hematite-based fly ash geopolymer for heavy-weight well cementing.

Ordinary Portland cement (OPC) has introduced different environmental and technical issues. Researchers tried either adding new materials to cement or developing alternatives for both technical and environmental challenges. Hematite as a weighting agent is used to increase cement slurry density. Heavy particles sedimentation in cement and geopolymer slurries is a serious issue which creates heterogenous properties along the cemented section. This work presents a new class of geopolymers using both hematite and Micromax as weighting materials for high density well cementing applications. The first system used only hematite while the other system used both hematite and Micromax. The main goal behind using Micromax with hematite is to check the possibility of eliminating the sedimentation issue associated with hematite in geopolymers. Moreover, the effects of adding Micromax on different FFA geopolymer properties were also evaluated. Different mixtures of retarder, retarder intensifier and superplasticizer were introduced to increase the thickening times of the developed geopolymer systems. The results showed that adding Micromax to hematite decreased the average density variation from 12.5% to almost 3.9%. Micromax addition reduced plastic viscosity by 44.5% and fluid loss by 10.5%. Both systems had a close performance in terms of strength, elastic properties, and permeability. The thickening time was 390 min for the hematite system and 300 min for the mixed system using the proposed additives mixtures.

Real-time rate of penetration prediction for motorized bottom hole assembly using machine learning methods.

Drilling rate of penetration (ROP) is one of the most important factors that have their significant effect on the drilling operation economically and efficiently. Motorized bottom hole assembly (BHA) has different applications that are not limited to achieve the required directional work but also it could be used for drilling optimization to enhance the ROP and mitigate the downhole vibration. Previous work has been done to predict ROP for rotary BHA and for rotary steerable system BHA; however, limited studies considered to predict the ROP for motorized BHA. In the present study, two artificial intelligence techniques were applied including artificial neural network and adaptive neurofuzzy inference system for ROP prediction for motorized assembly in the rotary mode based on surface drilling parameters, motor downhole output parameters besides mud parameters. This new robust model was trained and tested to accurately predict the ROP with more than 5800 data set with a 70/30 data ratio for training and testing respectively. The accuracy of developed models was evaluated in terms of average absolute percentage error, root mean square error, and correlation coefficient (R). The obtained results confirmed that both models were capable of predicting the motorized BHA ROP on Real-time. Based on the proposed model, the drilling parameters could be optimized to achieve maximum motorized BHA ROP. Achieving maximum ROP will help to reduce the overall drilling cost and as well minimize the open hole exposure time. The proposed model could be considered as a robust tool for evaluating the motorized BHA performance against the different BHA driving mechanisms which have their well-established models.

Application of Organoclays in Oil-Based Drilling Fluids: A Review.

Organoclays (OCs), formed by surface modification of clay minerals using organic compounds, are typical additives for providing rheology for oil-based drilling fluids (OBDFs). There are different studies on the effect of OCs on the rheological properties of oil-based systems under high-pressure, high-temperature (HPHT) conditions, but finding new OCs as rheology control agents is attractive for drilling fluid engineers. This work reviews different OCs used in OBDFs, namely, organo-montmorillonite (OMMT), organo-sepiolite (OSEP), and organo-palygorskite (OPAL). Furthermore, the structure of OCs in OBDFs, their rheological properties, and the thermal stability of OCs were investigated. Besides, the role of fibrous and layered OCs in enhancing the rheological properties of OBDFs is illustrated. Finally, the synergistic use of different OCs to enhance the thermal stability and rheological properties of the OBDFs is presented. The study highlights research gaps and recommendations for research approaches and potential areas that need further investigation. The application of OCs in OBDFs is a wide field and has huge potential to be developed. The use of OCs in OBDFs will promote development in the oil and gas industry.