Sand Production Research Articles

Gas–Water–Sand Inflow Patterns and Completion Optimization in Hydrate Wells with Different Sand Control Completions

Sand production poses a significant problem for marine natural gas hydrate efficient production. However, the bottom hole gas–water–sand inflow pattern remains unclear, hindering the design of standalone screen and gravel packing sand control completions. Therefore, gas–water–sand inflow patterns were studied in horizontal and vertical wells with the two completions. The experimental results showed that gas–water stratification occurred in horizontal and vertical standalone screen wells. The gas–water interface changed dynamically, leading to an uneven screen plugging, with severe plugging at the bottom and high permeability at the top. The high sand production rate and low well deviation angle exacerbated screen plugging, resulting in a faster rising rate of the gas–water interface. The screen plugging degree initially decreased and then increased as the gas–water ratio increased, resulting in the corresponding variation in the gas–water interface rising rate. Conversely, gas–water stratification did not occur in the gravel packing well because of the pore throat formed between the packing gravels. However, the impact of gas and water led to gravel rearrangement and the formation of erosion holes, causing sand control failure. A higher gas–water ratio and lower packing degree could result in more severe destabilization. Therefore, for the standalone screen completion, sand control accuracy should be designed at different levels according to the uneven plugging degree of the screen. For the gravel packing completion, increase the gravel density without destabilizing the hydrate reservoir, and use the coated gravel with a cementing effect to improve the gravel layer stability. In addition, the screen sand control accuracy inside the gravel packing layer should be designed according to the sand size to keep long-term stable hydrate production.

Gas–Water–Sand Production Dynamics of Offshore Interlayer-Buried Shallow Gas Reservoirs in the South China Sea

Gas–Water–Sand Production Dynamics of Offshore Interlayer-Buried Shallow Gas Reservoirs in the South China Sea

3D CFD-DEM modeling of sand production and reservoir compaction in gas hydrate-bearing sediments with gravel packing well completion

Sand production is one of the bottlenecks restricting the safe, efficient, and controllable production of hydrates. Enhancing the understanding of mesoscopic sand production responses is essential for sand production risk management. Yet, existing mesoscopic sand production models inadequately capture the effects of hydrate cementation, resulting in an incomplete assessment of the mechanical impacts of hydrates on sand production. Herein, we developed a new three-dimensional model for sand production in gas hydrate-bearing sediments (GHBSs) with gravel packing well completion, utilizing the coupled computational fluid dynamics and discrete element method (CFD-DEM). The model considers the coupled interactions of mechanical weakening and permeability variation in GHBSs caused by hydrate cementation reduction. Simulations are analyzed to clarify the responses of sand production and reservoir compaction under the coupled mechanical, hydraulic, and sand control completion in GHBSs during depressurization. The high fluid flow rate induced by a high production pressure differential can promote sand production and reservoir compaction. Additionally, the high effective stress and high hydrate dissociation rate induced by a high production pressure differential are beneficial for initial sand production, but they can also prematurely lead to gravel packing layer obstruction, inhibiting the final sand production. This also results in a dual impact on compaction deformation, enhancing it through compaction while decelerating it by inhibiting sand production. This work provides a viable simulation idea and preliminary insights into the mechanism of sand production from GHBSs.

Spatially resolved CFD-DEM model with innovative experimental validation methods to improve understanding of sand retention in oil and gas wells with the consideration of filter-beds on standalone screens

Coupling CFD and DEM is commonly used to study particle-fluid flow in sand retention systems for oil and gas wells, addressing the limitations of laboratory experiments and reliance on empirical data. These numerical studies aid in optimising standalone sand screens, which are favoured over gravel-pack completions for cost-effectiveness. However, such studies overlook the critical role of the bulk filter-bed in retaining permeability for both particulate and fluid phases. This paper presents a robust numerical methodology using resolved CFD-DEM to model a sand retention system that accurately captures filter-bed permeability, which has a greater impact on sand production and retained fluid productivity than the screen itself from a long-term perspective. The numerical model's accuracy is validated through a novel experimental methodology, which involves benchmarking the numerically derived porosity and single-phase permeability against micro-CT imaging of the filter-bed. Results show strong consistency between the numerical model and micro-CT imaging of the laboratory-derived filter-bed. This validated model provides a solid foundation for running more accurate sand retention tests and improving standalone sand screen selection criteria. Future work will explore the effects of varying parameters on the filter-bed formation to determine optimal conditions for maximising sand retention while maintaining hydrocarbon productivity from a long-term perspective.

Review of Recent Advances in Chemical Sand Production Control: Materials, Methods, Mechanisms, and Future Perspectives

Review of Recent Advances in Chemical Sand Production Control: Materials, Methods, Mechanisms, and Future Perspectives

A Comprehensive Review of Multifunctional Proppants.

Hydraulic fracturing technology is a crucial method for enhancing the production and recovery rates of unconventional oil and gas wells. In this process, proppants, as key materials, directly influence the effectiveness of the fracturing operation, thus attracting widespread attention. With the continuous development of hydraulic fracturing technology, researchers have designed and prepared a series of multifunctional proppants, such as surface-modified proppants, self-suspending proppants, and slow-release proppants, to effectively address issues like water production, sand production, and scaling in reservoirs. This paper aims to systematically review the research progress on multifunctional proppants, analyze their application potential in fracturing operations, and forecast the development direction of proppants. It is hoped that this review will provide valuable references for researchers and promote the further development of proppant-related technologies in hydraulic fracturing.

Study on the Sand Reduction Effect of Slope Vegetation Combination in Loess Areas

Slope erosion in the Loess Plateau region has long been a concern, and vegetation plays an important role in slowing down erosion and controlling sedimentation. However, a single vegetation model shows some limitations when facing complex natural conditions and variable rainfall events. Therefore, this study investigated the influence mechanism of vegetation configuration on slope sand production at different slopes through theoretical analyses and indoor experiments. The results of the study showed that certain factors, such as vegetation configuration mode, flow rate, runoff power, runoff velocity, and runoff shear, are closely related to slope runoff sand production. The specific findings are as follows: (1) Under the condition of slope gradient of 2°, the sand reduction effect of the rigid–flexible single-row staggered configuration is the most significant, and the sediment production is reduced by 29.89%. (2) With the increase in the slope gradient and flow rate, the sand production on the slope surface rises significantly, and when the slope gradient is increased from 2° to 6°, the average sand production is increased from 1.43 kg to 2.51 kg.(3) The erosion reduction effects of different vegetation configurations were in the order of rigid–flexible single-row staggered combination > flexible vegetation single combination > rigid–flexible double-row staggered combination > rigid vegetation single combination > upstream rigid downstream flexible combination > bare slope. This study provides a theoretical basis for optimizing the vegetation configuration for effective sand reduction and provides an important reference for the sustainable development of the Yellow River Basin.

Modeling the impact of pH and reservoir temperature on the dissolution of quartz mineral due to oilfield chemical treatment

The petroleum industry frequently uses oilfield chemicals, such as corrosion inhibitors, scavengers, drilling fluid, and chemical enhanced oil recovery methods, to improve oil recovery. However, these chemicals can negatively impact the geochemical characteristics of the formation, potentially leading to facility failure and reservoir formation damage. A study using PHREEQC was conducted to predict the impact of reservoir temperature and pH on quartz rock dissolution under different temperatures and pH levels. The results showed consistent dissolving rates for quartz at different pH levels. The solubility of quartz minerals was slightly affected by the solution pH, suggesting that the process variable pH has little effect on the equilibrium rate. However, precipitation caused quartz to dissolve at a rate of 0.04 mmol.L−1.s−1 at 45 °C but increased to 0.07 mmol.L−1.s−1 at 65 °C in 0.8 s. As temperature increased, quartz and NaNO3 solution interaction reached equilibrium concentrations in 0.8 and 2.7 s. The study concluded that temperature significantly impacts quartz dissolution during interaction with sodium nitrate oilfield chemicals compared to pH. The PHREEQ software is a useful research tool for simulating rock-fluid interactions resulting in reservoir formation dissolution and precipitation, which can cause formation damage and sand production.

Coupled Modeling of Computational Fluid Dynamics and Granular Mechanics of Sand Production in Multiple Fluid Flow

Summary Sand production is a significant issue in oil and gas fields with poorly consolidated formations, often involving the multiphase flow of reservoir fluids and solid particles. The multiscale mechanisms of sand production, particularly fluid flow and particle movement, remain poorly understood. This study investigates these mechanisms using a coupled computational fluid dynamics and discrete element method (CFD-DEM) modeling approach. Single and multiple fluid flows of water and heavy oil were simulated with increasing fluid injection velocities, leading to different sand production patterns. The simulation results were compared with experimental results from a large cylindrical specimen of weak artificial sandstone under similar loading conditions. The multiphase conditions created various localized flow and deformation patterns that influenced both fluid and solid production, resulting in shorter transient sand production periods. Microstructures and phenomena such as fingering and water coning were observed, associated with a critical flow rate below which oil displacement was uniform and no water breakthrough occurred. Higher fluid injection velocities and fluid viscosities resulted in greater drag forces, leading to progressive damage zones and explaining the occurrence of single or multiple staged sand production events. The evolution of the microscopic granular structure was visualized under the effect of transient sand production.

Experimental study on acidizing of natural gas hydrate reservoirs

Abstract Natural gas hydrates (NGH) are a promising resource. Due to the weak cementation of hydrate reservoirs, the reservoirs are prone to sand production or destabilization during hydrate dissociation. Samples of hydrate sediments were manually prepared, consolidated using a cementing agent, and then subjected to flow experiments using an acid solution. Comparative experiments were also conducted with unconsolidated samples. The consolidation samples could maintain the skeleton morphology after acidizing, and no sand production was observed; the unconsolidated samples had severe skeleton deformation after acidizing and serious sand production. The permeability of the consolidation samples after acidizing was 2.95mD, and porosity increased by 8.56%; the permeability of the unconsolidated samples after acidizing was 1.26mD, and the porosity decreased by 7.45%. CT scan images and mercury intrusion curves show good pore development after acidizing the consolidation samples, while the unconsolidated samples have poor pore development and sand plugging after acidizing. This result is because the cementing agent can consolidate the sand and gravel so that it will not be dislodged and transported during the acidizing process, thus maintaining reservoir stability. This study demonstrates the feasibility of acid modification technology in hydrate reservoirs, which is informative for the safe development of gas hydrates.

Study on Agglomeration and Plugging Behavior of Fine Particles in Reservoir Based on DEM-CFD Coupling

Abstract Given the particularity, significance, and complexity of particle migration behavior in fine silt sand hydrate reservoirs, the agglomeration and plugging behavior of free fine particles are mainly studied. Based on the discrete element method (DEM) and computational fluid dynamics (CFD), the DEM-CFD coupled 3D wellbore sand production numerical model is established and verified. The DEM module divides the reservoir particles into coarse and fine components according to the actual particle size distribution, and assigns adhesive and non-adhesive rolling resistance linear models, respectively. The CFD module uses the finite volume method to solve the incompressible Darcy flow in coarse grids. The results show that the DEM-CFD coupled numerical model established can effectively simulate the phenomenon of fine particle agglomeration during particle migration; Compared with the condition without particle agglomeration, fine particle agglomeration can lead to lower wellbore sand production and more severe pore blockage and permeability loss in the surrounding reservoir; The influences of different production and reservoir parameters such as flow rate, porosity and mud content on the variation of wellbore sand production and reservoir permeability under the condition of fine particle agglomeration is further determined, and relevant production measures and suggestions are put forward. The research results help to clarify the sand production mechanism and characteristics of fine silt sand reservoirs and are expected to provide theoretical and technical support for the efficient and safe development of natural gas hydrate resources in fine silt sand reservoirs.

Research and Practice of Sand Control Completion Technology Optimization in Western H Oilfield

Abstract In view of the problems of poor reservoir physical properties, high clay content, loose cementation, shallow burial, low compaction degree, low temperature in the middle and deep oil layers during the development process of unconsolidated sandstone reservoirs in the western H oilfield, the original sand control technology has poor adaptability and short sand control validity period., this paper carried out research on the optimization of sand control completion technology. In the study, a series of optimization studies were conducted, including analysis of acoustic time difference in sand producing layers, simulation of sand control formation compaction, optimization of gravel filling particle size, and sand control tools. A high-strength artificial wellbore and cyclic gravel filling sand control completion process suitable for different sand producing well conditions were developed and applied in practice. The research results and on-site practice indicate that the high-strength artificial wellbore sand control completion technology has good adaptability in low-temperature and long wellbore sand production wells; The cyclic gravel filling sand control completion technology has the advantages of simple construction, low cost, and low probability of major repairs in conventional shallow sand producing wells; The complementary advantages of the two processes effectively solve the problem of sand damage in H oilfield. Since 2021, the optimized sand control completion technology has been applied 46 times in H oilfield, with an average recovery oil production of 3.4t per well and an average effective period of over 500 days for sand control. The overall input-output ratio is 1:2.8, achieving good benefits and having high promotion and application value.

Quantitative Assessment of Sand Particulates in Gas-Water Slug Flow Using Deep Learning

Summary The weak collision response excited by micrometer-scale sand particulates is prone to overmixing with strong slug noise, significantly reducing the characterization and monitoring accuracy of sand particulate information in slug flows. Therefore, we developed a quantitative assessment method for sand particulates in slug flow that combines triaxial vibration monitoring and deep learning. First, a migration behavior characterization method of sand particulates is proposed combining nonlinear statistics, multifrequency coherence, and multiscale time frequency. The multifrequency response characteristics corresponding to the multiscale flow behavior of the sand-carrying slug flow were successfully characterized on the 2D time-frequency plane, namely, the mixed sand migration behavior [Intrinsic Mode Function 1 (IMF1)], liquid slug sand carrying (IMF2), forward liquid film and Taylor bubble sand carrying (IMF3), and reflux liquid film sand carrying (IMF4). Furthermore, the influence mechanism of gas superficial velocity (1.5–3.5 m/s), liquid superficial velocity (0.95–2.14 m/s), and sand content (0–20 g) on the triaxial vibration response of slug particulate flow with different migration behaviors is elucidated. Finally, a convolutional neural network (CNN)-gated recurrent unit (GRU)-self-attention mechanism (SATT) model for sand content assessment is developed based on the characterized multiscale migration behavior information and achieves an average recognition accuracy of 95.55% for data sets representing different sand migration behaviors in slug flow. This provides a new method for precisely identifying and monitoring sand production information of multiphase pipe flow.

Remedial Conformable Sand-Control Technology Deployed Offshore Colombia

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 23690, “First Horizontal Deployment of Remedial Conformable Sand-Control Technology in Colombia: Qualification and Case Study,” by Suzanne Stewart, SPE, TAQA, and Jose M. Bermudez, SPE, and Camilo Mazo, Hocol, et al. The paper has not been peer reviewed. Copyright 2024 International Petroleum Technology Conference. _ The challenge of remedial sand control lies in the fact that the system must pass through restrictions in the upper completion before ideally conforming to the inner diameter (ID) of the zone requiring sand control. The complete paper describes the qualification of a multilayer, open-cell matrix polymer (OCMP) system for the first horizontal deployment in an offshore gas well. The system is capable of being deployed remedially through tight tubing restrictions while providing conformant sand control in a horizontal wellbore without the need for gravel packing, making the approach particularly valuable for scenarios where surface space is limited. Background During 2006, gas Wells CH-20, CH-19, and CH-18 were originally drilled and completed in the B2 zone in the Chuchupa field offshore Colombia. Wells CH-20, CH-19, and CH-18 experienced water breakthrough from the aquifer in late 2016, 2018, and 2020, respectively. The first workover operation in these wells was performed in 2021. The aim was to isolate the B2 zone with a packer and to perforate the slightly shallower B1 zone to access attic gas. In Well CH-18, an inflatable packer between Zones B2 and B1 was installed successfully, resulting in the ability to produce at full potential, while Wells CH-19 and CH-20 recovered their potential partially but below the calculated target rate. A new operation for the three wells was planned in 2022 to set a mechanical packer to isolate Zone B2 and reperforate Zone B1 to increase flow area, reduce drawdown at the sandface, and diminish the risk of sand production. However, because produced sand had accumulated in front of the perforations in all wells, removing the sand and setting the mechanical packer was impossible. At present, Wells CH-19 and CH-20 are not producing and Well CH-18 is on lower-than-calculated target production. Given the production difficulties, the plan is to isolate Zone B2 successfully in all wells, clean the wells, and install effective remedial sand control with significant surface-space constraints. OCMP: Conformant Remedial Through-Tubing Sand Control The OCMP system evaluated and subsequently selected for this application consists of multiple layers of highly porous (up to 85%) and permeable (40 darcies or greater) OCMP bonded to a specially designed base pipe. The compressibility of the system enables it to be run in hole compressed within a sleeve to allow passage through tight restrictions in the upper completion; then, once in place, the sleeve can be removed, allowing a return to the original shape and conformance to the ID of the sand-producing section. The system can be run on slickline, braided line, coiled tubing, or pipe. If deployed with a hydraulic conduit, it has the capability to perform sand cleanout during deployment and can incorporate an integral hydraulic-set, high-expansion anchor. If run with slickline or braided line, it is necessary to run an anchoring device on a separate trip; then, the first OCMP system can be anchored in place.

Production-Enhancement-Candidate Screening Powered by ML Unlocks Brownfield Potential

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215244, “Automated Production-Enhancement-Candidates Screening Powered by Machine Learning Unlocks Untapped Potential in Matured Oil Fields: A Case Study,” by Nusheena M. Khair, SPE, M. Farid Zaizakrani, SPE, and Nur A.I.Z. Azhar, Petronas, et al. The paper has not been peer reviewed. _ Field A offshore East Malaysia has been a productive conventional oil field for more than 3 decades. It has encountered several surface and subsurface issues, including sand production, increasing water cut, and reservoir-pressure depletion. The complete paper presents the process of identifying production-enhancement opportunities, develops a methodology to identify underperforming candidates and analyze well-integrity issues, and describes how data science and engineering analyses are integrated. Introduction Field A is undergoing redevelopment, including activities such as enhanced oil recovery, production-enhancement (PE) initiatives, idle-well reactivation (IWR), and infill drilling. However, Field A’s operations and PE initiatives face multiple challenges. These include a shortage of comprehensive data affecting reservoir management and forecasting, difficulties in managing wells on unmanned platforms during adverse weather, and high logistical costs in offshore interventions that affect the economic feasibility of certain PE and IWR jobs. Recognizing these issues, the operator team is taking a proactive approach by embarking on enhancing PE and IWR candidate generation by machine learning (ML), a strategy that aims to expedite well-by-well review (WBWR) to streamline candidate-generation processes and enhance decision-making. Production Enhancement Candidate Generation and Screening (PECGS) Methodology PECGS is a petroleum engineering advisory system that helps operators improve the efficiency of PE and IWR candidate screening and intervention planning. PECGS automatically generates a list of underperforming wells along with recommendations for remedial actions. PECGS works by first evaluating each well’s production potential and risk assessment through use of a data-driven advisory system that combines analytical and ML models with industry-standard petroleum and reservoir management logic. Once the wells have been evaluated, PECGS generates a live automated opportunity register with a ranking of candidate wells. Technical Solution The technical solution in PECGS includes four main stages: knowledge base, technical analysis, chance of success, and economic analysis. The knowledge base of PECGS is formed through data integration from various sources. Static data have been standardized and validated by subject-matter experts before being uploaded into the advisory-system database. Dynamic data, such as production and well test, are integrated daily into the advisory system database according to a predefined schedule. The technical analysis is leveraged with proven analysis methods to identify well constraints and recommend PE opportunities and present estimated production gain, success probability, and profitability. The workflow uses multicriteria ranking, or the analytical hierarchy process (AHP), to rank screened wells based on production and petrophysical key performance indicators. Once a potential PE candidate has been identified through an automated screening, the next step is to review the chance of success. Next, the engineers perform an economic analysis to evaluate the potential profitability of the PE job. The economic analysis uses a variety of factors, including the cost of the intervention, the expected increase in production, and the value of the produced oil or gas in order to calculate the net present value (NPV) of the job. If the NPV is positive, then the intervention is profitable.

Sand Production Prediction and Management Using a One-Dimensional Geomechanical Model: A Case Study in NahrUmr Formation, Subba Oil Field

Sand production in sandstone reservoirs is a complex problem for oil and gas companies. This problem can damage downhole equipment and surface production facilities. This paper presents a sand production case and quantifies sand risks for the NahrUmr formation located in Subbaoilfied.The risk of sanding or rock failure is commonly observed during production phases as well as drilling operations. A (1D) mechanical earth model was created using wireline log data and core data for estimating the formations mechanical properties.The extrapolation method is utilized for vertical stress prediction, whereas pore pressure and static Young’s modulus were calculated using Slowness Eaton method and John Fuller correlation respectively. The poro-elastic model was used to determine horizontal principal stresses and hydrocarbon intervals susceptible to sand production issues.The purpose of this study was achieved using Tech-Log software. Sand onset intervals are firstly predicted as an open hole using ten methods: Loading factor (LF), Critical drawdown pressure (CDDP), B-index, schlumberger (Sc), Elastic combination index (Ec-index), Interval Transit-Time (DTc), Total porosity method (PHIT), unconfined compressive strength (UCS), Shear modulus to bulk compressibility ratio (G/Cb), and shear failure method. Approximately ten methods refer to the same intervals that can produce sand. Secondly, sand depths were predicted by representing the well according to what actually existed as a cased hole by calculating the critical drawdown pressure (CDDP), which is calculated at various depletion rates (0%, 15%, 25%, and 35%) in order to measure the effect of reservoir pressure depletion on sand production. The results show that as the rock strength is increased, the amount of sand-free drawdown and depletion becomes larger. Also, a single-depth analysis was conducted for problem intervals, indicatg a sandwillproducefromdepth of 2527.7 m under certain conditions. Therefore, it is necessary to install sand control equipment in this well.

Prediction of Sand Production from Poorly Consolidated Formations Using Artificial Neural Network: A Case Study, Nahr Umr Formation in Subba Oil Field

Sand production in poorly consolidated formations is a significant challenge to the oil and gas industry, resulting in reduced production and compromised equipment integrity. The oil and gas industry has recently become interested in data analytics because it has significantly simplified, accelerated, and reduced the cost of data visualization. The intriguing new approaches in artificial intelligence development promise to offer long-term solutions to the increasing problems affecting the petroleum industry's operations. Any completion operation in sandstone formations is based on determining whether or not a well will produce sand. It is economically unfavorable to the Nahr Umr Formation to install sand control equipment for wells that don't produce sand. This study aims to create an efficient and precise artificial neural network that can predict sanding in sandstone formations. To achieve this, we developed a two-layered ANN with a back-propagation algorithm using JMP software. The model formulation included various geological and mechanical factors that could impact sand detachment, such as Young’s modulus (YME), Poisson’s ratio, minimum and maximum horizontal stresses (SHMIN and SHMAX), pore pressure, shale volume, and formation strength. The study acquired data from both local fields, specifically the Amarah oilfield, and non-local fields from the literature. Two sets were created from the data: a training set comprising 75% of the data, and a test set comprising 25% of the data, both of which were classified. The speed and accuracy of a learning process in an Artificial Neural Network depends on the size of the data set, the number of hidden layers, and the input parameters. The statistical measures such as accuracy, confusion matrix, root mean square error, and generalized RSquare demonstrate the strong efficacy of the created Artificial Neural Network model. The results indicate a significant likelihood of sand production occurring over the perforation intervals across Su-4 and Su-5 wells. The method's unique feature is its ability to isolate shale areas and identify weak areas capable of producing sand in sandstone formations. In conclusion, it is determined that an Artificial Neural Network employing the back-propagation algorithm is a simple, reliable, and easy-to-use method for accurately predicting sand production.

Prediction of shear wave velocity in three sedimentary rocks in East Baghdad oilfield using multiple regression analysis

Shear wave is a crucial parameter for assessing the wellbore stability, the stress response, and rock deformation. It is essential for constructing the mechanical earth model (MEM) for many applications related to reservoir geomechanics including wellbore stability, sand production, hydraulic fracturing, and fault reactivation. However, shear sonic data is often omitted during the well-logging measurements for cost and saving purposes. To overcome this challenge, recent research has been focused on determining shear wave velocity through the use of core plugs, empirical correlations, artificial intelligence techniques, and multiple regression to quantify and evaluate the mechanical properties of subsurface formations without performing direct measurements at the wellbore. The greatest difference between this study and the literature is to predict the shear wave velocities for three sedimentary rocks based on conventional well logs. This study has been conducted on datasets of two wells drilled in the East Baghdad oilfield, for which there is a lack of shear wave data. Two formations (Tanuma and Zubair formations) within the production section of this field were conducted to develop new models for determining the shear wave velocity using multiple regression analysis. These two formations primarily consist of three lithologies: limestone, sandstone, and shale. Before the model development, data analysis on the selected data was applied to figure the most influential parameter(s) in determining the shear wave velocity. The results of the developed models are then compared with the previous models in the literature. The results showed that the multiple regression analysis technique is a powerful technique in determining shear wave velocity with high-performance capacity. The correlation coefficient ( ) and the root mean square error (RMSE) were 0.84 and 0.092 for limestone, 0.84 and 0.0972 for sandstone, and 0.86 and 0.0796 for shale respectively. Furthermore, the performance of the developed models is well matched to the actual shear wave data rather than the Castagna correlations. The findings of this study are effective in determining shear wave velocity for future applications related to reservoir geomechanics without needing costly well-log or core measurements.

Using well log data to predict rock compressibility and elasticity in Zubair formation/ southern of Iraq

The mechanical characteristics of rocks such as elasticity (Young's modulus, Poisson's ratio, and unconfined compressive strength) play an essential in sand production analysis, well design, and borehole stability assessment. In this study, the mechanical characteristics of rocks were indirectly estimated using gamma ray, density, and acoustic (compressional and shear) log data from well RU-X in the Rumaila oil field, specifically for the Zubair Formation. These estimated properties were compared to direct measurements obtained from triaxial and uniaxial mechanical tests conducted on well RU-X. The results showed a significant similarity between the indirect estimates and the direct measurements, indicating their reliability for sand production analysis and their valuable contribution to constructing the geomechanical model. Moreover, the static profile of Poisson's ratio was validated using laboratory core test results, demonstrating reasonable agreement. The validation process involved comparing laboratory-derived measurements with actual field measurements in the Zubair Formation. The higher Poisson's ratio observed in the shale was attributed to the slower propagation of acoustic waves, resulting in a good matching with an R2 value of 0.77. On the other hand, the lower Young's modulus in the shaly formations indicated lower resistance to deformation, with a comparative ratio of R²=0.96. Static measurements, which consider various influencing factors, provide a more realistic representation of rock behavior under different conditions. Regarding unconfined compressive strength, the comparative ratio was R²=0.83.

A new evaluation method for sand control performance of slotted screen

Evaluation method of slotted screen performance is a critical concern for sand control. Despite its significance, comprehensive investigations into quantitative study of sand retaining during the complex flow process need further in-depth study, particularly in numerical simulation research model of the slotted screen. This paper adopts the two-way coupling calculation method of computational fluid dynamics (CFD) and discrete element method (DEM) for the particle movement and fluid flow at the slotted screen and establishes a numerical model of the sand particle migration process through the slotted screen. The sand particle deposition and plugging dynamics on the surface of the sand retaining medium and the micro sand plugging mechanism and blockage pattern are studied. The fractal dimension of formation sand is introduced to characterize different distribution of formation sand. The effects of fluid viscosity, width of the slotted screen, sand production concentration, fluid velocity and particle size distribution on sand production, sand passing rate and particle size distribution of formation sand passing through the slot and plugging behavior are studied. The sand plugging process of slotted screen can be divided into three stages: the beginning of blockage, the intensification of blockage, and the balance of blockage. Under simulated conditions, the initial sand plugging rate is 87%, and as the blockage intensifies, the sand plugging rate gradually increases to 96.5%. Based on the analysis of numerical simulation results, the index of total seepage resistance damage amplitude and velocity, general sand retention ratio and passed-sand size were defined to construct the integrated evaluation method of slotted screen media, which involves the performance of sand retention, anti-plugging and flow ability. A brand new set of ideas on quantifying the integrated evaluation method were introduced to calculate the individual and integrated performance indicators of the slotted screen based on simulated data. The quantitative evaluation of the sand control performance of the slotted screen provides guidance and reference for the parameter design of the slotted screen in the target oil region and the accuracy optimization of the sand control medium.