bluuebunny/crossref_metadata_2025 huggingface dataset:
First Worldwide Application of Metal Expandable Fracture Packers to Enhance Integrity and Reduce Deployment Issues While Utilizing Openhole MSAF Completions
Authors: Arias Rommel E. , Guizada Pablo , Gaby Mohamed , Riou Yoann
Published: October 2020

This paper presents the first application of metal expandable frac packers for multistage acid fracturing (MSF) completions. This technology significantly reduces deployment risk commonly associated with openhole (OH) MSF completions with the ability to rotate while running in hole without any risk of premature expansion or compromising integrity of the sealing mechanism. Additionally, it improves efficiency of fracturing operations in tight gas reservoirs with the ability to expand to larger borehole diameters than is possible with current isolation packer technologies.

The overall deployment method for this technology is similar to traditional openhole multistage fracturing completions that are industry standard. The main difference is that the isolation packer used is expanded by pressure to mechanically deform the metal sleeve to provide sealing against the open hole. The technology comprises an innovative material and design that can hold high differential pressure at high reservoir temperatures while maintaining permanent isolation in a relatively compact element length. The metal expandable frac packer completed an extended qualification process, including American Petroleum Institute (API) testing, to fulfil deployment and acid fracturing completion requirements.

The outcome was an overall successful deployment and stimulation operation of multistage completion with the metal expandable frac packer. The metal expandable frac packer provided the ability to deploy the lower completion in difficult wellbore conditions with ability to rotate. The metal expandable frac packer is set with pressure; therefore, there is no waiting time to have full differential pressure capabilities for the fracturing operations. This technology provided a flexibility factor for packer placement as the metal expandable packer technology can hold its rated pressure at larger borehole diameters. Since the mechanism of the metal packer is expansion by inelastic deformation, the metal expandable sleeve conforms perfectly to the geometry of the borehole, providing a highly reliable seal for high pressure fracturing operations. Through a complete diagnostic process, it was confirmed that the metal expandable packers successfully isolated each stage of the stimulation treatment.

Metal expandable frac packers unique testing was conducted in the laboratory and in field to qualify the technology with special focus on the chemical composition for the fluids encountered for the deployment, stimulation, and production environments including high concentration acid fracturing applications. The metal expandable sleeve technology utilizes a unique double-sleeve system for pressure compensation to enhance the sealing integrity of MSF stimulation operations and truly provide 10,000 psi under API 19OH V1.
Characterizing Gas-Water Transport Behavior in Tight Shale and its Application on the Well Productivity
Authors: Liu Ang , Liu Shimin , Sang Guijie
Published: October 2020

This study provides a systematic method to study the gas/water transport behavior and water retention behavior in gas shale reservoir using analytical and numerical modelling approaches. The critical water saturation determined from the relative permeability curve is regarded as the turning point between two gas production stages: Stage I and Stage II. At Stage I, the gas /water two phase flow dominates shale gas production period, while at Stage II the single gas flow and the flow of water in adsorbed phase are dominative. The improved permeability evolution model incorporates both the gas and water sorption-induced swelling strains. The permeability ratio is a time- and location-dependent parameter and its change can be divided into three stage, namely, the increase at early time, the decrease at mid-term time, and the increase at later production time. With gas depletion, gas pressure drawdown significantly dominates the evolution of permeability ratio. Continuously, the effect of sorption induced matrix shrinkage strain will become dominative with gas pressure decreases to low values. Due to the gas source supplement induced by gas desorption at Stage I, the gas production rate will temporarily increase but then will continuously decrease till to the lowest level at critical water saturation. At Stage II, the gas production rate is significantly influenced by residual water content in shale controlled by the flow of water in adsorbed phase. In addition, the effects of elastic properties (i.e. Young's modulus and Poisson's ratio), initial permeability and diffusion time on permeability ratio and gas/water production profiles were discussed. These results provide a first rational method for analyzing the gas/water transport behavior and water retention behavior with potential application of shale gas recovery.
On the Inference of Gas Diffusion Coefficient in Organic Matter of Shale Gas Reservoirs
Authors: Eltahan Esmail , Mehrabi Mehran , Sepehrnoori Kamy , Javadpour Farzam
Published: October 2020

Gas production from shale-gas reservoirs constitutes the largest portion of total gas production. The US shale reservoirs are tight and inherently heterogeneous with abundant presence of kerogenic material. Modeling fluid flow in shale reservoirs is complex and still an active field of research. The complexity arises from different flow physics such as pressure flow and diffusion. Many of the field performance forecasts constantly underestimate production from these reservoirs because most of the current models ignore important governing physics. This study provides new insights on diffusion in organic matter, in an effort to correct a main source of underestimation of gas production in shale gas models.

In an earlier study, we developed for the first time a detailed diffusion model and showed how pore size distribution and specific surface area of the pores in organic matter can significantly influence gas production. An important parameter controlling the rate of gas release is the diffusion coefficient of gas diffusing into organic matter which appears in the flow equations. One of the methods of estimating the diffusion coefficient is based on analysis of gas uptake into shale samples in a closed chamber. The coefficient is extracted by comparing experimental observations to the solution of diffusion equation in the domain of pore/kerogen interface. If the mathematical representation of the organic matter is inaccurate, the diffusion coefficient will be inaccurate as well, regardless of lab-measurements accuracy. The values reported in the literature are based on the slab-shaped mathematical representation of organic matter, assuming a single scale for diffusion characteristic length.

In this study, we implement a multi-scale diffusion model to estimate gas diffusion coefficient in organic matter. The previously reported evaluations are on the order of 10−20 m2/s. Reanalysis of the same set of experimental data using our detailed model suggests the interpretation of the coefficient is largely dependent on the diffusion-length scales being considered. We show that diffusion occurs over multiple time scales and the coefficient could be as much as four orders of magnitude higher than reported. The developed diffusion model is a robust and practical mathematical model and can be implemented in reservoir simulators. The findings of this study shed some light on why production forecasts constantly underestimate gas production from shale gas reservoirs.
Mapping Buried Steel Flowlines Using Geophysical Sensors on Small Drone Aircraft
Authors: Hammack Richard , Veloski Garret , Schlagenhauf Mark , Zorn Andrew , Wylie Luke , Campbell Nathan
Published: October 2020

This study evaluated magnetic surveys using small unmanned aerial systems (sUAS) for the mapping of small diameter, buried pipelines, particularly flowlines. The study found that 2-inch diameter, steel pipelines buried 3-ft. deep can be confidently mapped by a total field, atomic magnetometer flown at 8 m above ground level, the maximum sensor altitude tested. The study also suggested that spiral flightplans might be preferred over bidirectional, parallel line surveys (serpentine surveys) because of the increased likelihood that the magnetic sensor will cross pipelines at or near 90° angles, the preferred orientation to obtain narrow, but intense pipeline magnetic signatures.
Effect of Oil Chemistry on the Performance of Low Salinity Waterflooding: An Integrated Experimental Approach
Authors: Tawfik Miral S. , Karpyn Zuleima T. , Johns Russell T.
Published: October 2020

Chemical enhanced oil recovery (cEOR) relies on the interactions of the injected chemicals with the surface-active components (SACs) of the oil-in-place and the rock surface to induce favorable physico-chemical changes. In this study, we investigate the effect of oil composition on the performance of low salinity waterflooding (LSWF) in carbonate rocks using an integrated experimental approach. In addition, we assess the extent of usefulness of total acid number (TAN) as an oil screening criterion for LSWF application in carbonate reservoirs by using model oils that have different SACs, but the same TAN.

A variety of characterization techniques including thermal gravimetric analysis (TGA), attenuated total reflectance (ATR-FTIR) and zeta potential (ζ) are performed to investigate the molecular-scale effect of oil chemistry on rock-oil-brine interactions during LSWF. Sessile drop contact angle measurements are also performed to quantify the influence of different SACs on the wettability of carbonate rock samples. Concurrently, coreflood experiments are performed to evaluate the effect of oil composition on the performance of LSWF in carbonate rocks in terms of Darcy-scale oil recovery.

Results of this study show that oil chemistry significantly influences the performance of LSWF at all scales. Different molecular-scale interactions are observed in the presence of different SACs owing to differences in their affinity to the rock surface, strength of adsorption, solubility in brine, as well as their distinct pore-scale wetting abilities. These differences translate into significant variation in Darcy-scale oil recovery. In addition, carboxylic acid chain length is found to affect the amount of SACs adsorbed onto carbonate rocks during aging. Carboxylic acid chain length also affects the strength of adsorption, which in turn impacts the magnitude of wettability alteration during LSWF. Further, partitioning of SACs in brine is observed to influence the type of interactions taking place in the rock-oil-brine system, where carboxylate salts (soaps) generated in-situ are detected only in the presence of certain oil-brine pairs but not in the presence of others. Solubility of SACs in brine is also found to promote water-wetness. As a result, significant differences in the rate of oil recovery and ultimate recovery are observed when displacing four oils by the same low salinity brine at similar experimental conditions. Finally, the value of TAN is found to be insensitive to the type of acidic SACs present in the oil phase as long as they are monoprotic and their molar concentration in the oil is the same. Even within the same class of SACs, namely carboxylic acids, the usefulness of TAN is limited in differentiating between the type and molecular structure of the acid (i.e.: straight chain versus aromatic).
Mechanics of Fracture Propagation in Closely Spaced Clusters
Authors: Daneshy Ali
Published: October 2020

For more than a decade there has been a gradual reduction in perforation cluster spacing together with increased number of clusters and larger frac sizes. The main driver for this change has been increased production. In recent years the more common cluster spacing has been in the range of just a few tens of feet, even as low as only five feet.

This paper discusses the effect of reduced cluster spacing on propagation pattern of hydraulic fractures. It notes that fractures are more likely to initiate axially/longitudinally from perforations and reorient once they extend away from the wellbore to become perpendicular to the least principal stress. This process causes formation of a pseudo-open hole along the axial fracture near each perforation cluster and its existence has been verified by proppant tracer and fiber optic surveys. In cases of close cluster spacing these pseudo-open hole segments can merge and cover a much longer segment of the cemented liner. Merging of axial fractures will be further assisted by poor quality cement. This causes the fracture re-orientation to occur along a material weakness intersected by the merged axial fractures, somewhat like what would happen in an openhole completion. The net result is random location and number of fractures extending away from the wellbore. Presence and extent of the pseudo-open hole is demonstrated by proppant tracer surveys from actual field examples presented in the paper.

Paper concludes that there is a limit to usefulness of shorter spacing for increasing the number of created fractures. If too close, the randomness of fracture location and number can create results contrary to expectations. It recommends an alternate hybrid cluster arrangement consisting of bunching the closely spaced perforation clusters into multiple separate groups and using larger separation between the groups to avoid spread of the initiated axial fractures outside each group.
Robust Data Driven Well Performance Optimization Assisted by Machine Learning Techniques for Natural Flowing and Gas-Lift Wells in Abu Dhabi
Authors: Al Selaiti Iman , Mata Carlos , Saputelli Luigi , Badmaev Dorzhi , Alatrach Yara , Rubio Erismar , Mohan Richard , Quijada Daniel
Published: October 2020

Asset management success is accomplished when the integrated production system is operating close to its intended potential. Continuous awareness of wells and facility conditions are key factor in the realization of designed capacity. In contrast, unknown status and conditions can severely limit production capacity.

The rise of instrumentation technologies over the last four decades have created new opportunities to understand well and reservoir behavior. However, despite of being proved as a cost-effective surveillance initiative, remote monitoring is still not adopted in over 60% of oil and gas fields around the world. Understanding the value of data through machine learning techniques is the basis for establishing a robust surveillance strategy.

The objective of this paper is to develop a data-driven approach, enabled by Artificial Intelligence (AI) methodologies including machine learning (ML), to find optimal operating envelope for gas-lift wells. The process involves building ML models for generating instantaneous predictions of multiphase flow rates and other quantities of interest, such as GOR, WCT, using real-time sensor data at the surface, historical performance, and sporadic test data.

Additionally, forecasting models were developed for generating short-term (30 days) forecast of cumulative oil, water, gas, and liquid production, multiphase flow rates, WCT, GOR, and reservoir pressure. Using time-series forecasting models, a sensitivity analysis was performed to generate short-term well response for a selected number of combinations of choke settings, and gas injection rates. Sensitivity analysis provides 2D maps of well response highlight an operating envelope, which are proposed to be combined with physical and operational constraints to arrive at optimal operating conditions, which may effortlessly add 2.5% net profit from optimum gas-lift alocation.

The results of this work show encouraging results, and demonstrate value that AI-enabled methodologies can provide in instrumented wells by enabling automated workflows for virtual metering, production allocation, short-term production forecasting, and deriving optimal operating conditions. The developed AI methodology has tremendous potential of integration in an end-to-end workflow of autonomous well control by utilizing available data to produce easy to update ML models, with little to no human intervention.
How Much Can You Afford to Ignore Casing Failure During Hydraulic Fracturingš the Search for a Non Damaging Frac Plug
Authors: Stolyarov Sergey , Casanova Gabriel , Xu YingQing , Deng Guijun , Holmes Kevin , Gomez Ricardo , Young Aaron
Published: October 2020

Frac plugs remain the most common zonal isolation tool in multistage stimulation. However, while manufacturers in recent past have focused on improving frac plug drillability and dissolvability, the industry critically overlooked significant plug design flaws. Among these flaws is mechanical damage to horizontal well casing caused by inadequate plug construction, poor isolation integrity, and cycled pressure stress on the pipe throughout the entire fracture treatment. Until recently, casing integrity issues had never even been associated with frac plugs.

Today, significant improvements in ultrasonic wellbore diagnostics, downhole cameras, and fiber optic well monitoring visualizing post-frac casing integrity have revealed widespread casing breaches at plug setting depths. These recently discovered flaws called for a frac plug with non-damaging slips and optimized packing element systems for improved zonal isolation. Three-dimensional finite element analysis was performed to understand casing damage caused by various slip designs currently being utilized in the market. Extensive laboratory tests were conducted on slip and packing element designs to further support and validate the numerical study. Finally, fiber-optic diagnostic data was used to confirm interstage isolation efficiency by a non-damaging frac plug.

This paper will review findings that some slips, under certain scenarios, cause severe casing wall damage. It will also review findings that some packing element designs provide inadequate isolation during the fracture–posing considerable challenges to casing integrity. Based on extensive numerical analyses, laboratory tests, and field trials, a frac plug with non-damaging slips, as well as anti-extrusion packing element systems, limit the frac plug's impact on the casing during high fracture pressure treatments.
Digital Transformation of Well Completion Selection and Design Through Data Insights
Authors: Gottumukkala Varma , Worthington Matthew , Basak Debasmita , Radhakrishnan Renuka , Srinivasan Jay , Ramesh Smitha
Published: October 2020

Well completion selection and design involve the selection of optimum well completion architecture and associated downhole equipment to deliver hydrocarbon to surface in a safe and efficient manner. A number of well architectures can be conceived for a given application, and a plethora of equipment is available across the industry, with hardware to meet a wide range of operating conditions including hole size, pressure, temperature, flow rate and fluid type. This wealth of choice results in a highly complex and challenging selection process that today is done manually, relying on subject matter experts and local best practices through trial and error approach. As a result, the process can be quite inefficient, designs can be suboptimal and fail to consider unique reservoir and well conditions leading to premature equipment failure causing loss of production and well integrity. These failures can have impact ranging from unplanned well intervention, equipment pull outs, fishing operations, extended rig time, workovers, or even complete well loss—costing the oil and gas industry billions of dollars. The shortcomings in design are therefore ripe for innovative digital solutions.

This paper describes how manual completion selection process can be seamlessly transformed into an intuitive digital solution providing insights for the well completion selection process. The proposed digital solution describes software tools and architecture used to consolidate thousands of historic, unstructured, completion schematic data into a structured database. It automatically maps the completion architecture and equipment details to relevant operating environments, captures nonproductive time and highlights installation challenges. The solution also identifies correlations and data trends across various types of well designs and equipment categories, using advanced artificial intelligence and machine learning algorithms to provide insights into equipment reliability, operational efficiency, total cost of ownership and production performance. A minimum viable product consisting of 24,000 wells from across the world has been successfully developed to demonstrate key value propositions.

New data coming in from recently completed wells can be seamlessly integrated with the existing data bases and the algorithms constantly improvise its learning process to provide better accuracy. The digital solution proposed for well completion selection and design process ultimately enables oil and gas companies to optimize well completion configurations and equipment that can deliver maximum value. It allows them to identify offset well issues, derisk operational concerns, check compatibility of equipment with respect to dimensional constraints, pressure and load rating requirements, thread configurations, metallurgy constraints, seal elements, complete well on digital file with tracing and accountability.
Data Analysis of the Permian Basin Wolfcamp and Bone Spring Leads to Better Understanding of Production Sweetspots
Authors: Sorkhabi Rasoul , Panja Palash
Published: October 2020

The Wolfcamp and Bone Spring formations of Lower Permian age in the Permian superbasin of west Texas and southeast New Mexico have contributed greatly to the US shale oil revolution in the recent decade. These formations were deposited in a rapidly subsiding basin at the southern margin of the North America craton during collisional tectonics in Late Paleozoic times. Here we analyze production data from nearly 4,800 horizontal wells drilled into Welfcamp and Bone Spring to constrain petroleum accumulations. The data indicate a bimodal distribution of oil and gas occurrence in Wolfcamp suggesting the migration of oil and gas from deeper (∼11,000 ft.) to shallower levels (4,000-6,000 ft.) in the same formation. Oil accumulation in Bone Spring is concentrated at the depths of 11,000-7,000 ft. with some intervals being more productive mimicking the alternating position of shaley and sandy layers in this formation. High gas-to-oil ratios are found at shallower levels for both formations. This study offers an application of reverse engineering to petroleum system analysis and supports the concept of intra-formational migration in the tight (shale) oil formations.
Optimization of Multi-Stage Hydraulic Fracturing in Unconventional Reservoirs in the Context of Stress Variations with Depth
Authors: Singh Ankush , Zoback Mark , McClure Mark
Published: October 2020

Stage length and perforation cluster spacing are important design parameters for multi-stage hydraulic fracturing. This study aims to demonstrate that the interplay between subtle variations of the least principal stress (Shmin) with depth and the stress shadows induced by simultaneously propagating hydraulic fractures from multiple perforation clusters, primarily determines the propped and fractured area in the target formations. This principle is illustrated with the help of a case study in a prolific unconventional formation in the north eastern US, where the vertical stress variations are well characterized through discrete multi-depth stress measurements and actual stage design parameters used by the operator are known. At first, we show how the hydraulic fracture footprint and proppant distribution varies with a change in the vertical stress profile. The stress profile is shown to be a very important in determining the optimal vertical and lateral well spacing. The evolution of the stress shadow in the different layers is shown during the pumping as the fracture propagates across multiple layer boundaries. Subsequently, we demonstrate that by changing the magnitude of stress perturbations caused by the stress shadow effect, the distribution of propped area can be altered significantly. We use this method to determine the optimal cluster spacing keeping other design parameters constant such as flow rate, perforation diameter, etc. Simulations from selected cluster spacing realizations are run with high and low permeability scenarios to show the importance of correct matrix permeability inputs in determining the three-dimensional depletion profile and ultimate production. By varying the cluster spacing we show the hydraulic fracture propagation change from being solely stress layering driven to stress shadow influenced. The effect of stress shadow on the final fracture footprint is highly specific depending on the given stress layering and is thus case-dependent. This study demonstrates that knowledge of stress variations with depth and modeling are critical for optimizing stimulation efficiency.
Application of Flexible Variable Frequency Drive Systems in Low-Volume Pumping Wells
Authors: Fu Zhijun , Wang Qian , Wang Lei , Xu Jingjing , Qiu Yiwang , Li Chaofeng
Published: October 2020

Improving pumping system efficiency in low production wells has been a big challenge for most of mature fields in China. These wells often cause high energy consumption and additional mechanical wear because of relatively high pumping speed and nonoptimalpower input for motor drive, even though operators respond it by simply turning down the stroke per minute (SPM) or adopting variable intermittent production scheme based on the well conditions. Therefore, for low production wells, it is important to produce more oil with lower energy input or operational cost. In recent years, researchers proposed a few high-efficiency intelligent control strategies used for these wells, but rarely could be effective and widely used in the field due to the lack of behavior improvement and adaptability. Based on the results from previous research, this paper provides a new solution on flexible variable frequency drive to address the aforementioned challenges.

To obtain high system efficiency for low production well, firstly new solution, under a preset and fixed SPM, manage to change pumping speed within each cycle. This can be done utilizing the pumping net load data which is calculated by controller algorithm. Then, it will regulate the SPM based on the real time production data (mainly for fluid rate) which is automatically collected by a specialized wellhead flow meter. Since flow rate is the most effective and direct data to demonstrate reservoir capacity, it can guarantee an accurate and reasonable pump SPM. All adjustments above would be done through continuously regulating the motor electrical parameters, such as voltage and current, using converter and control algorithm built in the flexible controller. Real-time matching to the lifting load and well capacity can realize the best motor drive pattern and avoid the waste of energy. Tow set of process control makes up the new control strategy and fulfills a more ideal pumping operation.

For different well capacity, new technology allows the pump frequency to be regulated from 0.5 SPM to 12 SPM under a stable running condition. Each stroke has an adjustable rate process to match inconstant net load. For those low production wells, relatively low and constant-changing pumping speed not only largely decrease producing energy needs, but also reduce rod-on-tubing wear. Thus, the test wells have improved system efficiency and prolonged mean time between failures (MTBF). This paper would describe the control principle of flexible variable frequency drive system in detail and demonstrate its application through two well cases.
Improving ESP Performance with Two Stages of Gas Separation in 7 Casing Case Study
Authors: Delgado Anderson , Espinosa Jorge , Hernandez Maria , Guanacas Luis , Gonzalez Gustavo , Aya William
Published: October 2020

The Electrical Submersible Pump (ESP) has become one of the most popular ALS worldwide due to its capacity of lifting high fluid volumes with high efficiency, however, its application is questioned under some circumstances related to difficulties that this system presents when managing high gas rates. Even though the ESPs can handle high volumes, they are also highly affected by gas bubbles flowing through each component, affecting: the motor temperature, lifting efficiency, the integrity of the motor and cable, situations that can lead to premature failure and expensive workover operations. This is the reason why some companies decide to install a different ALS instead of an ESP. The present study shows a successful ESP optimization in combination with a new gas mitigation system that allowed to manage high GOR and GLR and avoid gas locking, low lifting efficiency, multiple shutdowns due to poor cooling in the motor, and surge production (changes on motor load). The new double stage gas mitigation system was designed to manage a GOR>1,200 SCF/STB with a WC of <1%, BHT of 200 °F, and 85% of free gas flowing into the pump intake. This gas separation system for ESP was complemented by installing a shrouded ESP to assure a proper cooling of the motor and to prevent the free gas to flow directly to the pump intake. This paper contains all the descriptions of each component of the 2 stage gas mitigation/separation system.

The well showed a notorious production improvement and the operator was able to decrease the PIP below 630 psi (Max limitation on the Jet pump system due to low efficiency of this ALS) achieving a production increase from 300 to 700 BOPD (↑400 BOPD)
Laboratory Measurement of Cement Stress Before, During, and After Curing Under Undrained Condition with Constant Hydrostatic Pressure
Authors: Meng Meng , Frash Luke , Carey James , Li Wenfeng , Welch Nathan
Published: October 2020

Wellbore integrity analysis should consider the cement setting process in a confined downhole environment, noting that cement is initially a liquid that becomes a solid. In our study, the state of stress of cement specimens is measured during cure from a liquid to a solid at laboratory simulated downhole conditions. We apply accurate control of axial stress, confining pressure, and pore pressure inside cement specimens during the entire setting process combined with strain gauges mounted on the outer surface of the steel pipe to measure the cement's state of stress during the setting process. The setup allows multiple experimental conditions to be investigated, including constant axial stress, constant axial displacement, drained and undrained conditions. Different controlling conditions represent different field scenarios since the process of cement setting in the downhole situations is a highly complex process that depends on the in-situ condition, formation lithology, cement slurry composition, mud cake composition, drill bit type, etc. In this work, the Class-G cement slurry is cured under constant axial stress, confining pressure, and undrained conditions. This represents a field condition where the top of the cement can drop during setting, the vertical component of cement weight is not significantly affected by bonding, and the formation is quite impermeable with a very difficult fluid exchange between formation and cement. Our results show that under such a scenario, no significant pressure drop occurs after seven days of the setting process, and the cement initial total stress is close to its hydrostatic pressure.
Application of Deep Learning Methods in Evaluating Well Production Potential Using Surface Measurements
Authors: Alakeely Abdullah A. , Horne Roland N.
Published: October 2020

This work investigated deep learning (DL) algorithms to forecast wells' economic potential using wellhead surface measurements. The results of DL algorithms were compared to existing solutions in the literature that aim at solving the same problem. The performance of algorithms trained on multiple input representations, resulting from applying unsupervised DL feature extraction methods, was compared to algorithms trained on raw inputs.

In this work, available wellhead measurements that can be collected at surface were used in modeling their relationship to well production rate. A search method was used to select the best combination of measurements for modeling. In addition, features were extracted automatically using autoencoders to generate additional inputs. The algorithms used for forecasting were designed using standard and customized DL layers. The results of both DL and existing solutions from the literature were compared systematically to determine the usefulness of the DL methodology developed.

Previous work has shown the limitations of correlation-based methods in offering a reliable solution when applied to data outside of the historically observed range. In addition, multiple models are sometimes required depending on operational settings, e.g. choke opening, making the modeling process inefficient. Moreover, mass balance-based methods require information, such as phase density, that might not be readily available when modeling is performed, affecting the reliability of the solutions. We found that using DL algorithms offers a flexible solution that can help overcome these limitations and opens a new path to solve similar problems. We found that algorithms trained properly on relevant features are useful tools to use in assessing the economic potential of wells, using already available surface measurements.

The study developed a novel methodology for forecasting economic potential using wellhead surface measurements and demonstrated the application to real field data. The method was found to be an efficient utilization of data that are readily available and do not require well intervention to measure.
Machine Learning Approach to Quantifying ISIP and Friction Losses from Stage by Stage Hydraulic Fracture Treatment Falloff Data
Authors: Alwarda Fahad
Published: October 2020

While diagnostic fracture injection tests (DFIT) data is relatively rare, pressure and flow rate data are widely collected for hydraulic fracture treatment stages in multiple transverse-fracture horizontal wells, both during pumping and during pressure falloff after the end of pumping. Recent papers have shown value in applying analysis developed for DFIT data to hydraulic fracture treatment falloff (HFTF) data. As is often the case with routine processing of large volumes of data, the time required for analyzing HFTF datasets for each of the treatment stages in a long horizontal well may be overly expensive in time and human resources. To address this issue, this paper applies machine learning techniques to standard HFTF pressure data, to produce data-driven mathematical models that estimate wellbore and perforation friction loss, near-wellbore tortuosity friction loss, and the instantaneous shut-in pressure (ISIP). The models are trained based on a small subset of hydraulic fracture treatment stages, data from for which is processed manually, to provide targets for model outputs. Model structure is based on multivariate statistical methods, including principal component regression (PCR) and partial least squares regression (PLSR).

Comparison between state-by-stage friction losses and ISIP values estimated manually and those quantified by machine learning reveals good agreement and underscores the value of the machine learning approach as a practical tool for field application tasks, including well and pad completion design decisions related to perforating strategies, and fracture and well spacing.
Model for Estimating Static Bottom Hole Pressure for Gas Wells Using Varying Pseudo Critical Properties in Modified Cullender and Smith’s Equation
Authors: Bassey Israel
Published: October 2020

As the economic importance of natural gas continues to grow because of its relatively clean output, the exploitation of natural gas wells is of increasing importance in the energy industry. Monitoring of these gas wells is key and the Static Bottom Hole Pressure is an integral parameter when we talk about reservoir/well evaluation. The Static Bottom Hole Pressure is most often acquired through downhole gauge measurements. However, this method is disadvantaged by associated risk and cost of execution.

This paper presents a new method for calculating Static Bottom Hole Pressure. This new model considers the changes in the critical properties in the well in a fine grid segmentation of the well and uses the different values of specific gravity in a numerical simulation that involves a modification to the Cullender and Smith’s Equation that accounts for the variation in gas gravity profile values, fine grid segmentation, and well geometry.

Based on the results obtained, this model was seen to provide a more accurate estimate than the existing methods. The model was tested on 30 wells using the generated software and its results were benchmarked against other exiting models and compared with gauge measurements to validate the error reduction. Error estimation on the model showed that this method gives an average accuracy of 99% with an average absolute error of 0.304%. The results of this work showed that this method was effective in estimating Static Bottom Hole Pressure.
New Model Development for Polymer Chemical Enhanced Oil Recovery EOR
Authors: Jaffray Jacob
Published: October 2020

Chemical enhanced oil recovery (EOR) is a method that helps to increase recovery of oil in the tertiary stage of a reservoir. Methods such as polymer, surfactant, and microbial injection increase overall recovery by producing unswept or residual oil that remains after a water flood. The primary goal of this research was to simplify the calculations needed to predict polymer rheology and to model polymer behavior without the need for lab testing samples. Polymer samples with varying concentrations, salinities, and hardness levels were prepared and polymer viscosity versus shear rate was measured using a rheometer. It was found that polymer preparation methods significantly affect the rheological properties of a sample and standard procedures ensure consistency. Predictive calculations were performed before lab testing samples so that the lab data could be compared to various models in order to determine their accuracy. A program was created to find constants of the polymer and to model polymer viscosity versus shear rate. This program also includes fitting parameters (specific for polymer type) that allow these calculations to be performed without the need for lab fitted data. Polymer rheology is dependent on a sample's composition, and its rheological properties can be easily and accurately modeled by the developed program. Various outdated programs relating to polymer EOR were also updated to meet modern standards and to improve their functionality.
Effects of three methods of breast milk expression on breastfeeding initiation, breast milk extraction and proportion of exclusive breastfeeding—an open label, randomized controlled trial
Authors: Zhou Yun , Ni Jiaying , Zhou Chenchen , Chen Ying , Little Julian , Zhang Lin
Published: October 2020

Background Direct breastfeeding has multiple health benefits. Some mothers need to express their breasts when directly breast feeding is unavailable immediately after delivery. However, there is insufficient evidence regarding an effective method of breast milk expression in the absence of an infant's suction. This trial was designed to investigate the effects of different methods of breast milk expression on breastfeeding initiation, efficacy of breast milk extraction, and on the rate of exclusive breastfeeding at 6 months. Methods The participants of mother-infant dyads separated immediately after birth for at least 6 hrs were recruited and randomly assigned (1:1:1) into three groups: (1) hand expression of breast milk; (2) sequential and (3) simultaneous electrical breast pumping. The two primary outcome measures were the time required for initiation of breastfeeding and the milk volume expressed in a 10-minute session (direct breastfeeding in hand expression group) at 3 days and at 6 weeks; a secondary outcome was the proportion of exclusive breastfeeding at 4 and 6 months. Intention-to-treat data set was used in this analysis. Results Between 2018 and 2019, we recruited 226 participants, of whom 154 were randomized. The median time (in hour) of breastfeeding initiation of sequential (46.5, 95% CI 36.1-50.5) and simultaneous (45.6, 95% CI 34.2-53.0) breast pumping groups did not differ from those of hand expression (46.7, 95% CI 40.8-50.0) (p=1.000). At 3 days the breast volume through simultaneous pumping (13.1±10.9 ml), but not sequential pumping (16.7±11.6 ml) (p=0.560), was significantly less than hand expression (23.8±26.2 ml through direct sucking) (p=0.007). At 6 weeks the breast volume through sequential pumping (64.7±51.0 ml), but not simultaneous pumping (71.6±50.8 ml) (p=0.670), was significantly less than hand expression (89.8±67.3 ml through direct sucking) (p=0.035). The breast milk volume through sequential breast pumping (10 min per breast) was 37.9 ml less than those of simultaneous pumping (p=0.000). The rate of exclusive breastfeeding at 4 months was 21.0%, and at 6 months 10.6%, and did not differ between the three methods of breast milk expression. Conclusions Hand expression, sequential breast pumping, or simultaneous breast pumping in absence of immediate infant suction after birth did not show differences on the time required to initiate breastfeeding, or on the rate of exclusive breastfeeding at 4 and 6 months. Trial registration This trial was registered with www.chictr.org.cn (ChiCTR1800018193) on 4 September 2018.
Syndromic Management of Female Sexually Transmitted Infections at Primary Care Level .A Descriptive Cross-Sectional Study Tunisia (Monastir 2007-2017)
Authors: Dhouib Wafa , Zemni Imen , Kacem Meriem , Bennasrallah Cyrine , Fredj Manel Ben , Abroug Hela , Grira Samia , Mastouri Maha , Sr Asma Belguith
Published: October 2020

Background: In the world as in North Africa, Sexually Transmitted Infections (STIs) are a public health problem especially for reproductive-age women. Since the quantification of the prevalence of STIs is important for the planning of interventions and the promotion of resources, it is necessary to have current data to evaluate the situation in the Maghreb and to give the answer as to the possibility of reaching the desired WHO goal of ending STIs epidemics as a public health concerns by 2030.The aim of this study was to determine the prevalence and trend of STIs during 11 years in Tunisia (2007-17). Methods: We conducted a descriptive cross-sectional study including all women with STIs diagnosed with the syndromic approach in all basic health care centers of the Governorate of Monastir (Tunisia) from 2007 to 2017. Syndromes included, Pelvic Pain (PP), Vaginal Discharge (VD) and Genital Ulceration (GU). Results: We analyzed 40388 cases of genital infection with a crude prevalence rate and age standardized prevalence rate of 13.93/ 1000 inh and 72.38/ 1000 respectively. The prevalence rate was relatively high and showed a positive trend over 11 years for all age groups and syndromes. VD was the most common syndrome with a CPR of 11.7/1000. For all syndromes, women of childbearing age (20 to 39 years) were the most affected age group (p <0.05). Conclusion:Our results were consistent with the global evidence, suggesting a focus on primary prevention reinforcement and STIs surveillance system improving in North Africa countries to achieve the World health organization goal of ending STIs epidemics by 2030.
Medicine Storage, Wastage and Associated Determinants Among Urban Households: A Systematic Review of Household Surveys
Authors: Jafarzadeh Adineh , Mahboub–Ahari Alireza , Najafi Moslem , Yousefi Mahmood , Dalal Koustuv
Published: October 2020

Background: Irrational household storage of medicines is a world-wide problem resulting medicine wastage and associated harms, which imposes an additional burden on the health care system. The study has performed a systematic review of household surveys to provide strong evidences and policy implications through a comprehensive and comparative understanding of available global literatures. The review also maps existing literature on the burden, outcomes and affecting socio-economic factors of medicine storage and wastage.Methods: Five electronic databases were searched (from inception to 2019) for surveys that reviewed in-home medicine storage modality, size, cost and main determinants. The methodological quality of included studies was appraised through an adapted checklist developed by past studies.Results: From the initial 2604 records we identiﬁed, 22 studies met our inclusion criteria. In 16 studies, medicine storage rates were reported for more than 70%. The maximum rate of potential (not in use medicines) and real (expired or without expiration date medicine) wastage were about 70 and 40 percent, respectively. The most common classes of medicines found in households belonged to the nervous system (18%) and anti-infective for systemic use (15%). Income, education, age, presence of chronic illness, female gender and insurance coverage were among the factors influencing medicine storage. The most commonly used method of disposal was throwing them in the garbage.Conclusions: Factors beyond medical needs determined medicine storage in the studied contexts which urges effective strategies in the supply and demand side of the medicine consumption chain. The first necessary step to mitigate home storage is adequate legislation and strict enforcement of regulations on dispensing, prescription and marketing of medicines. Patient pressure on excessive prescription, irrational storage and use of medicines deserve efficient community centered programs for increasing awareness of these issues. Hazardous consequences of inappropriate disposal should be mitigated by different take back programs, particularly in low and middle income countries.
Diversity and Composition of Gut Microbiome of Cervical Cancer Patients by 16S rRNA and Whole-metagenome Sequencing
Authors: Biegert Greyson , Karpinets Tatiana , Wu Xiaogang , Alam Molly B. El , Sims Travis T. , Yoshida-Court Kyoko , Lynn Erica J. , Yue Jingyan , Medrano Andrea Delgado , Petrosino Joseph , Mezzari Melissa P. , Ajami Nadim J. , Solley Travis , Ahmed-Kaddar Mustapha , Colbert Lauren E , Klopp Ann H.
Published: October 2020

Background Next generation sequencing has progressed rapidly, characterizing microbial communities beyond culture-based or biochemical techniques. 16S ribosomal RNA gene sequencing (16S) produces reliable taxonomic classifications and relative abundances, while shotgun metagenome sequencing (WMS) allows higher taxonomic and functional resolution at greater cost. The purpose of this study was to determine if 16S and WMS provide congruent information for our patient population from paired fecal microbiome samples. Results Comparative indices were highly congruent between 16S and WMS. The most abundant genera for 16S and WMS data did not overlap. Overlap was observed at the Phylum level, as expected. However, relative abundances correlated poorly between the two methodologies (all p>0.05). Hierarchical clustering of both sequencing analyses identified overlapping enterotypes. Both approaches were in agreement with regard to demographic variables.Conclusion Diversity, evenness and richness are comparable when using 16S and WMS techniques, however relative abundances of individual genera are not. Clinical associations with diversity and evenness metrics were similarly identified with WMS or 16S.