bluuebunny/crossref_metadata_2025 huggingface dataset:
I-Geo Sensing Fracture Diagnostic i-GSFD for Fast Processing of the Smart Microchip Proppants Data
Authors: Pham Vuong Van , Dahaghi Amirmasoud Kalantari , Negahban Shahin , Fincham William , Babakhani Aydin
Published: September 2021

Unconventional oil and gas reservoir development requires an understanding of the geometry and complexity of the hydraulic fractures. The current categories of fracture diagnostic approaches include methods for near-wellbore (production & temperature logs, tracers, and borehole imaging) and far-field techniques (micro-seismic fracture mapping). These techniques provide an indirect and interpreted fracture geometry. Therefore, none of these methods consistently provides a fully detailed and accurate description of the characteristic of the subsurface hydraulic fractures. This study proposes a novel approach that uses direct data from the injected fine size (proppant Mesh size equivalence) and battery-less, Smart MicroChip Proppants (SMPs), to map the fracture geometry. This novel approach enables direct, fast, smart, and real-time processing of the received high-resolution geo-sensor data from the SMPs collected in high pressure and high-temperature environment and maps the fracture network using the proposed i-Geosensing Fracture Diagnostic (i-GSFD), which is a closed-loop architecture. i-GSFD is based on multi-dimensional projection unsupervised clustering, and an integrated Bayesian optimizer to control the stochastic nature of any components in the loop.
An Advanced Proppant Depositional Study with Post-Production Flow Evaluation in a 10' X 20', Transverse Fracture, Slot Flow Configuration
Authors: Donald A. Anschutz , Patrick J. Wildt , K. Michelle Stribling , Jim Craig , Luiz R. Curimbaba , Pedro Silva , Ibrahim S. Abou-sayed
Published: September 2021

While the shale revolution flourished prior to the pandemic, the increased supply bubble had already taken a toll on the profitability of horizontal wells with multiple transverse fractures. A significant shift previously occurred to reduce proppant costs by utilizing cheaper, smaller grained, lower strength, and broadly diverse grain sized sands. Due to the extremely low matrix permeability in active unconventional plays, the use of regional 40/70 and 100 mesh sands (50/140, 70/140, etc.) has become commonplace with adequate results. What remains is the need for enhanced conductivity near the wellbore to handle the radial flow convergence loss when the well is brought on-line. Research is being conducted to better understand how to efficiently increase near-wellbore conductivity using lead and tail-in stages with higher permeability (ceramic) proppant when frac sand is the majority of the material pumped into the well. A 10’x20’ Large Slot Flow (LSF) apparatus, equipped with multiple injection points, side-panel ports for leak-off and/or post-test injection, with the ability to be disassembled for sample analysis after testing, was utilized for this project. For this data, the inlet was moved to the centerline of the wall to allow for proppant and fluid to transport into an environment similar to a horizontal wellbore connecting with a transverse fracture. Various tests were conducted to study the depositional characteristics of lead and tail-in stages with ceramic proppant (15% BW-Lead, 5% BW-Tail) and a main stage of 100 mesh sand (80%). Three inlet positions were established in the lower, middle, and upper portion of the apparatus. Tests were recorded to visually capture the efficiency of placing the premium proppants near the wellbore for increased conductivity. A key addition to the study was the innovative, post-production analysis through the side-panel ports. Fluid was injected into the proppant pack to observe the effect of increased near-wellbore conductivity. To improve visibility, the fluid was colored with a fluorescent dye and observed under black lights. The injection front geometry was radial initially, but typically elongated toward the exit point after contacting the ceramic proppant. The amount of time and distance for the fluid to travel through the sand pack, as well as that for the fluid to reach the offtake point once the ceramic bed was reached, were monitored and recorded. The ratio of the velocities should represent a valid qualitative indication of the conductivity contrast of the two proppants.

This paper will describe the unique experimental configuration, outline the testing program for both deposition and post-production assessments performed on the deposits, along with results that could provide better design practices leading to improved transverse fracture performance.
CO2 Leakage Rate Forecasting Using Optimized Deep Learning
Authors: He Xupeng , Zhu Weiwei , Santoso Ryan , Alsinan Marwa , Kwak Hyung , Hoteit Hussein
Published: September 2021

Geologic CO2 Sequestration (GCS) is a promising engineering technology to reduce global greenhouse emissions. Real-time forecasting of CO2 leakage rates is an essential aspect of large-scale GCS deployment. This work introduces a data-driven, physics-featuring surrogate model based on deep-learning technique for CO2 leakage rate forecasting. The workflow for the development of data-driven, physics-featuring surrogate model includes three steps: 1) Datasets Generation: We first identify uncertainty parameters that affect the objective of interests (i.e., CO2 leakage rates). For the identified uncertainty parameters, various realizations are then generated based on Latin Hypercube Sampling (LHS). High-fidelity simulations based on a two-phase black-oil solver within MRST are performed to generate the objective functions. Datasets including inputs (i.e., the uncertainty parameters) and outputs (CO2 leakage rates) are collected. 2) Surrogate Development: In this step, a time-series surrogate model using long short-term memory (LSTM) is constructed to map the nonlinear relationship between these uncertainty parameters as inputs and CO2 leakage rates as outputs. We perform Bayesian optimization to automate the tuning of hyperparameters and network architecture instead of the traditional trial-error tuning process. 3) Uncertainty Analysis: This step aims to perform Monte Carlo (MC) simulations using the successfully trained surrogate model to explore uncertainty propagation. The sampled realizations are collected in the form of distributions from which the probabilistic forecast of percentiles, P10, P50, and P50, are evaluated. We propose a data-driven, physics-featuring surrogate model based on LSTM for CO2 leakage rate forecasting. We demonstrate its performance in terms of accuracy and efficiency by comparing it with ground-truth solutions. The proposed deep-learning workflow shows promising potential and could be readily implemented in commercial-scale GCS for real-time monitoring applications.
Jointed Tubing Injector Snubbing on Extended Reach Wells
Authors: Miller H. J. , Richard A. D.
Published: September 2021

OBJECTIVE / SCOPE

An injector has been developed that is able to continuously move conventional jointed tubing in and out of wells that may be underbalanced. It is an advantage to use the jointed tubing injector rather than coiled tubing or conventional hydraulic snubbing due to cost, speed of operation, transportation, effectiveness, and safety. The paper will describe the function and application of the jointed pipe injector.

METHODS, PROCEDURES, PROCESS

An injector has been designed with retractable gripping segments integral to the gripper blocks that are able to function on conventional jointed tubing, over interconnecting couplings and with the advantages of continuously operating injector movement. The description is to include how the geometry of the retractable gripper block system works and how the technical and safety risks of a conventional snubbing system or coiled tubing are overcome. Configurations whereby the jointed tubing injector can be used to provide methods of completing wells that are safer and more efficient than coiled tubing or a conventional hydraulic snubbing jack will be presented.

RESULTS, OBSERVATIONS, CONCLUSIONS

The biggest limitation of coiled tubing is due to its size and residual bend, it is not capable of reaching the end of the well before the wellbore friction causes helical buckling. The OD of the coiled tubing is limited by the available reel sizes and the difficulty transporting the large reels due to road dimensional and weight limitations. Coiled tubing is not able to be rotated at any time in the well. The use of jointed tubing eliminates those limitations.

When a well is being completed with a conventional hydraulic snubbing jack, the length of the stroke that the jack can take is limited by the allowable unsupported length of the tubing to ensure that it will not buckle. It is also forced to stop workstring movement each time the jack is reset therefore the static friction of the workstring must be overcome during each movement of the jacks. The design of the jointed tubing injector minimizes the unsupported length of the tubing and allows the continuous movement of the tubing. The operation is less labor intensive, and the controls can be moved to a position that is less exposed to danger.

NOVEL / ADDITIVE INFORMATION

The Jointed Tubing Injector can continuously move jointed tubulars in and out of a well. There is no other piece of equipment that will address as many of the problems that have been experienced in the completion of extended reach wells. The paper will describe the injector and control system and how it can be applied to solve the challenges.
Robust CO2 Plume Imaging Using Joint Tomographic Inversion of Distributed Pressure and Temperature Measurements
Authors: Yao Changqing , Chen Hongquan , Onishi Tsubasa , Datta-Gupta Akhil , Mawalkar Sanjay , Mishra Srikanta , Pasumarti Ashwin
Published: September 2021

Geologic CO2 sequestration and CO2 enhanced oil recovery (EOR) have received significant attention from the scientific community as a response to climate change from greenhouse gases. Safe and efficient management of a CO2 injection site requires spatio-temporal tracking of the CO2 plume in the reservoir during geologic sequestration. The goal of this paper is to develop robust modeling and monitoring technologies for imaging and visualization of the CO2 plume using routine pressure/temperature measurements.

The streamline-based technology has proven to be effective and efficient for reconciling geologic models to various types of reservoir dynamic response. In this paper, we first extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process.

The power and utility of our approach are demonstrated using both synthetic and field applications. We first validate the streamline-based DTS data inversion using a synthetic example. Next, the hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warmback analysis of the temperature data.

The novelty of this work is the streamline-based history matching method for the DTS data and its field application to the Department of Engergy regional carbon sequestration project in Michigan.
Dull Bit Grading Using Video Intelligence
Authors: Ekeregbe Merit P. , Khalaf Mina S. , Samuel Robello
Published: September 2021

Although visual data analytics using image processing is one of the most growing research areas today and is largely applied in many fields, it is not fully utilized in the petroleum industry. This study is inspired by medical image segmentation in detecting tumor cells. This paper uses a supervised Machine Learning technique through video analytics to identify bit dullness that can be used in the drilling industry in place of the subjective screening approach. The evaluation of bit performance can be affected by subjective evaluation of the degree of dullness. The present approach of using video analytics is able to grade bit dullness to avoid user subjectivity.

The approach involves the use of datasets in good quantity and quality by separating them into training datasets, testing datasets, and validation datasets. Due to the large datasets, Google Collaboratory was used as it provides access to its Graphic Processing Unit (GPU) online for the processing of the bit datasets. The processing time and resource consumption are minimized using Google GPU. Using the Google GPU resources, the procedure is automated without any installation. After the bit is pulled out and cleaned, a video is taken around and up and down in 360°. Further, it is compared against the green bit. By this approach, multiple video datasets are not required.

The algorithm was validated with new sets of bit videos and the results were satisfactory. The identification of the dullness or otherwise of each screened bit is done with the aid of a bounding box with a stamp of a level of confidence (range 0.5–1) and the algorithm assigns for its decision on the identified or screened object. This method is also able to screen multiple bits stored in a single place. In an event where several drill bits are to be screened, manual grading will be a huge task and will require a lot of resources. This model and algorithm will take a few minutes to screen and provide grading for several bits while videos are passed through the algorithm. It has also been found that the grading with the video was much better than the single image as the contextual information extracted are much higher at the level of the entire video, per segment, per shot, and per frame. Also, methodology is made robust so that the video model test starts successfully without error. The time penalty for the processing is fast and it took less time for a single video screening.

The work developed here is probably the first to handle the dull bit grading using video analytics. With more of these datasets available, the future automation of the IADC bit characterization will soon evolve into an automated process.
Identification of Shale Bedding Layers from Micromechanical Evaluation
Authors: Cheng Shizhong , Sheng Mao , Chen Zhaowei , Tian Shouceng , Li Gensheng
Published: September 2021

Bedding layers are well-developed in shale and recognized to enhance the complexity of the hydraulic fracture network. A micromechanical evaluation approach of shale bedding layers based on indentation testing techniques was proposed. Rock thin section identification and scanning electron microscope were utilized to describe the shale laminations. To capture high-resolution image with large area and ensure abundant morphology and mineral information, Atlas 5 system, which could create large mosaic images, was applied. Combined with FIB, a method for positioning the laminations in SEM and accurately navigate to it in the micromechanics experiment was established. Fractures were emphasized to be initiated and extend in the clay mineral layers. It can be explained that the flaky structure of clay mineral is beneficial for the extension of fracture. It will become more potential to connect with the fluid-driven fractures. Nanoindentation was conducted to obtain micromechanical properties in different lamination layers. Results verify the feasibility of this scheme and demonstrate fine-grained, transition and coarse-grained layers. Indentation results show variation in micromechanical properties of coarse-grained layer, the transition layer and the fine-grained layers. The present work is helpful to identify shale bedding layers from micromechanical evalutions.
Development of a Virtual Flowmeter as an Enhanced Alternative for Field Production Monitoring
Authors: Chaves Gabriela , Karami Hamidreza , Monteiro Danielle , Martins Ferreira Virgilio José
Published: September 2021

Flowrate is a valuable information for the oil and gas industry. High accuracy on flowrate estimation enhances production operations to control and manage the production. Recognized as a cost-efficient solution, the VFM (virtual flowmeter) is a mathematical-based technology designed to estimate the flowrates using available field instrumentation. The VFM approach developed in this work combines black-box simulations with mixed-integer linear programming (MILP) problem to obtain the flowrates dismissing the tuning process. The methodology included a set of multiphase flow correlations, and the MILP was developed to estimate the flowrate and designate the best fit model. We evaluated the proposed VFM against 649 well test data. The methodology presented 4.1% average percentage error (APE) for percentile 25% and 13.5% APE for percentile 50%. We developed a VFM technology to be used in scenarios with a lack of data, and we believe that our tuning-free method can contribute to the future of VFM technologies.
Benchmarking and Field-Testing of the Distributed Quasi-Newton Derivative-Free Optimization Method for Field Development Optimization
Authors: Alpak Faruk , Wang Yixuan , Gao Guohua , Jain Vivek
Published: September 2021

Recently, a novel distributed quasi-Newton (DQN) derivative-free optimization (DFO) method was developed for generic reservoir performance optimization problems including well-location optimization (WLO) and well-control optimization (WCO). DQN is designed to effectively locate multiple local optima of highly nonlinear optimization problems. However, its performance has neither been validated by realistic applications nor compared to other DFO methods.

We have integrated DQN into a versatile field-development optimization platform designed specifically for iterative workflows enabled through distributed-parallel flow simulations. DQN is benchmarked against alternative DFO techniques, namely, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method hybridized with Direct Pattern Search (BFGS-DPS), Mesh Adaptive Direct Search (MADS), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). DQN is a multi-thread optimization method that distributes an ensemble of optimization tasks among multiple high-performance-computing nodes. Thus, it can locate multiple optima of the objective function in parallel within a single run. Simulation results computed from one DQN optimization thread are shared with others by updating a unified set of training data points composed of responses (implicit variables) of all successful simulation jobs. The sensitivity matrix at the current best solution of each optimization thread is approximated by a linear-interpolation technique using all or a subset of training-data points. The gradient of the objective function is analytically computed using the estimated sensitivities of implicit variables with respect to explicit variables. The Hessian matrix is then updated using the quasi-Newton method. A new search point for each thread is solved from a trust-region subproblem for the next iteration. In contrast, other DFO methods rely on a single-thread optimization paradigm that can only locate a single optimum. To locate multiple optima, one must repeat the same optimization process multiple times starting from different initial guesses for such methods. Moreover, simulation results generated from a single-thread optimization task cannot be shared with other tasks.

Benchmarking results are presented for synthetic yet challenging WLO and WCO problems. Finally, DQN method is field-tested on two realistic applications. DQN identifies the global optimum with the least number of simulations and the shortest run time on a synthetic problem with known solution. On other benchmarking problems without a known solution, DQN identified compatible local optima with reasonably smaller numbers of simulations compared to alternative techniques. Field-testing results reinforce the auspicious computational attributes of DQN. Overall, the results indicate that DQN is a novel and effective parallel algorithm for field-scale development optimization problems.
A Dual-Directional Flow Control Device for Cyclic Steam Stimulation CSS Applications
Authors: Zhu Da
Published: September 2021

Cyclic steam stimulation (CSS) is one the most effective thermal recovery methods. It is widely used as the primary thermal recovery method to recovery heavy oil fields in Middle East, Asia Pacific, North and South America. In this paper, a novel dual-directional flow control device (FCD) will be introduced. This FCD technology can allocate accurate steam outflow into the reservoir formation and improve steam quality during steam injection period and can mitigate steam breakthrough from the neighboring wells during production period.

In the first section, we will give a brief introduction on CSS and the main issues encountered in the field operation. A multi-directional flow control nozzle specifically designed for CSS application will be presented. Design philosophy in thermodynamics and hydrodynamics of the nozzle will be discussed in detail. Field performance results, Computational Fluid Dynamics (CFD) and flow loop testing data will be shown to evaluate the performance of the technology. The application of the technology in steam assisted thermal applications will be introduced. Well-known issues such as erosion and scaling on the FCD tools will be studied in the end.
Numerical Mechanistic Study of In-Situ CO2 EOR – Kinetics and Recovery Performance Analysis
Authors: Hussain Sadam , Wu Xingru , Shiau Ben
Published: September 2021

The success of supercritical CO2 Enhanced Oil Recovery (EOR) cannot be duplicated if the cost of CO2 transposition and processing becomes prohibitive. Research results of the in-situ CO2 EOR (ICE) approach offered a potential technology for many waterflooded stripper wells that lack access to affordable CO2 sources. Previously the ICE synergetic mechanisms were only qualitatively attributed to oil swelling and viscosity reduction due to the preferential partition of CO2 into the oleic phase. This study aims to quantify the contributions to recovery factors from several plausible mechanisms with numerical modeling and simulation.

First, the urea reaction was modeled as the CO2 generating chemical decomposing to CO2 and ammonia in the reservoir conditions. The CO2 partitions into oil, which leads to the reaction continuation to generate more CO2. The resulting ammonia largely left in water may further react with certain crudes to generate surfactants, thus, decrease the oil/water interfacial tension (IFT). It is expected that the oil containing CO2 also has a lower IFT with water. The reaction kinetics under different temperatures were incorporated into the numerical model. A numerical model featuring the synergetic mechanisms was built including stoichiometry and kinetics of urea reaction, oil swelling effect, oil viscosity reduction, and IFT reduction effect on the relative permeabilities. The laboratory experiments, pore volume injection versus oil saturation were history matched for three different oils including Dodecane, Earlsboro oil, and DeepStar oil. The phase behavior was modeled with the equation of state (EOS) under different mole fractions of CO2. The reaction kinetics were also modified to history match the laboratory experiment.

The estimated reduction of oil viscosity was calculated, 76% for Earlsboro oil, 91% in DeepStar oil, and 75% in dodecane oil. The oil swelling factors ranged from 1.60% to 19% in the three lab models, which translates to the recovery factor of oil. The endpoints of relative permeability were modified to account for the recovery contribution to the IFT and viscosity reduction. The impact of reaction kinetics on oil swelling and recovery factor was also determined, and they are not numerically close to reaction kinetics used in the lab cases. The matched reaction kinetics, activation energy and reaction frequency factor for the dodecane laboratory experiment were 91.80 kJ/gmol and 6.5E+09 min−1. The study concluded that the incremental recovery due to oil swelling ranges between 3.16% and 18.30%, and then from 12.91% to 41.59% is due to IFT reduction for all the cases. The relative permeability and urea reaction kinetics remained the most uncertain parameters during history matching and modeling the ICE synergetic mechanisms.
Selection of Representative Scenarios Using Multiple Simulation Outputs for Robust Well Placement Optimization in Greenfields
Authors: Mahjour Seyed Kourosh , Santos Antonio Alberto Souza , Santos Susana Margarida da Graca , Schiozer Denis Jose
Published: September 2021

In greenfield projects, robust well placement optimization under different scenarios of uncertainty technically requires hundreds to thousands of evaluations to be processed by a flow simulator. However, the simulation process for so many evaluations can be computationally expensive. Hence, simulation runs are generally applied over a small subset of scenarios called representative scenarios (RS) approximately showing the statistical features of the full ensemble. In this work, we evaluated two workflows for robust well placement optimization using the selection of (1) representative geostatistical realizations (RGR) under geological uncertainties (Workflow A), and (2) representative (simulation) models (RM) under the combination of geological and reservoir (dynamic) uncertainties (Workflow B). In both workflows, an existing RS selection technique was used by measuring the mismatches between the cumulative distribution of multiple simulation outputs from the subset and the full ensemble. We applied the Iterative Discretized Latin Hypercube (IDLHC) to optimize the well placements using the RS sets selected from each workflow and maximizing the expected monetary value (EMV) as the objective function. We evaluated the workflows in terms of (1) representativeness of the RS in different production strategies, (2) quality of the defined robust strategies, and (3) computational costs. To obtain and validate the results, we employed the synthetic UNISIM-II-D-BO benchmark case with uncertain variables and the reference fine- grid model, UNISIM-II-R, which works as a real case. This work investigated the overall impacts of the robust well placement optimization workflows considering uncertain scenarios and application on the reference model. Additionally, we highlighted and evaluated the importance of geological and dynamic uncertainties in the RS selection for efficient robust well placement optimization.
A Competency-Based Approach to Addressing the Leadership Gap in the Oil and Gas Industry
Authors: Howes C. Susan , Taylor Robert W.
Published: September 2021

As oil and gas industry technical professionals land their first supervisory roles, gaps in their leadership skills often become apparent. Years of technical education and training have prepared them well for roles as individual technical contributors, but stronger business, management, and leadership skills are needed as they move into emerging leadership roles in which they direct others.

Competency assessments of first-level supervisors and mid-career experienced hires are conducted to determine mission-critical leadership gaps. This process is done in alignment with competency-focused job descriptions that enumerate key soft skills needed in each leadership role and build on a sound foundation of technical competency. Bringing emerging leaders together as a group enhances their networking opportunities as they advance through the program; including experienced hires helps them become attuned to the company's management style. Learning opportunities can include face-to-face instruction, webinars, e-learning, online resources, exercises, business simulations, and coaching and mentoring.

Building future leaders is key to succession planning. Introducing experienced hires to the leadership styles of the company ensures the successful integration of new talent into the team. A competency-based approach to assessing emerging leaders provides the roadmap for creating a deep bench of candidates for future roles in executive management. Experienced instructors and mentors are crucial to ensuring the leadership program delivery is aligned with the corporate mission, vision and values. The delivery of the leadership development program can be self-sustaining if program graduates and external expert facilitators are incorporated into the delivery of the program to future cohorts.

Technical professionals progress through supervisory/management positions on their respective career ladders primarily by ‘learning on the job' rather than through formal training. This paper looks at differences between the current state of supervisory development and what professionals actually need in leadership skills. These are new skills needed for transitioning from supervisor/manager to an effective leader. New methods of digital delivery allow greater interaction between participants and instructors. Building an innovative leadership development program enhances the company's brand and attracts and retains top talent.
Cost-Effective Development of Shallow and Poorer Quality Gas Reservoir in Mature Field
Authors: Abdulhadi Muhammad , Mohd Said Hani , Zubbir Ahmad Uzair , Ling Evelyn , Mohd Nasir Mohamed Azlin , Anoar Imran , Abdul Rahim Abdul Rahman , Elias Rohani , Sanchez Paul , Sharif Rizam , Abdul Ghapor Zamri , Ismail Nurhanim , Kew Yoong Hau
Published: September 2021

The Cement Packer approach has been successfully implemented to pursue and monetize minor gas reservoirs of poorer quality. Due to its critical role in power supply to meet the nation's needs, license to operate gas fields oftentimes come with contractual obligations to deliver a certain threshold of gas capacity. The cement packer method is a cheaper alternative to workovers that enables operators to build gas capacity by monetizing minor gas reservoirs at lower cost.

Group 1 reservoirs are the shallowest hydrocarbon bearing sand with poorer reservoir quality and relatively thin reservoirs. The behind-casing-opportunities in Minor Group-1 reservoirs previously required a relatively costly pull-tubing rig workover to monetize the reservoir. Opportunities in two wells were optimized from pull –tubing rig workovers to a non-rig program by implementing Cement Packer applications. The tubing was punched to create tubing-casing communication and cement was subsequently pumped through the tubing and into the casing. The hardened cement then acted as a barrier to satisfy operating guidelines. The reservoir was then additionally perforated, flow tested and successfully monetized at a lower cost.

Tubing and casing integrity tests prior to well entry demonstrated good tubing and casing integrity. This is critical to ensure that cement will only flow into the casing where the tubing was punched. Once the cement hardened, pressure test from the tubing and from the casing indicated that the cement has effectively isolated both tubulars. Subsequent Cement Bond Log and Ultrasonic Imaging Tool showed fair to good cement above the target perforation depth. These data supported the fact that the cement packer was solid and the reservoir was ready for additional perforation. Taking into account the reservoir quality, it was decided to perforate the reservoir twice with the biggest gun available to ensure the lowest skin possible. Post perforation, there was a sharp increase in the tubing pressure indicating pressure influx from the reservoir. Despite that, casing pressure remained low, confirming no communication and thus the success of the cement packer.The well was later able to unload naturally due to its high reservoir pressure, confirming the producibility of the reservoirs and unlocking similar opportunities in other wells. Additionally, the cement packer approach delivered tremendous cost savings between $6 – 8 mil per well.

Besides confirming the reservoirs' producibility,the success also unlocked additional shallow gas behind casing opportunities in the area.This method will now be the first-choice option to monetize any hydrocarbon resources in reservoirs located above the top packer.
Mitigating Water Production from High Viscosity Oil Wells in Unconsolidated Sandstone Formations
Authors: AL-Rashidi Hamad , Hussein Hussein Mahmoud Reda Aly , Erhamah Abdulaziz , Malik Satinder , AL-Hajri Abdulrahman , Almeida Dwane , Salehi Nazanine , Omonte German , Zaitoun Alain
Published: September 2021

Large reserves of High-Viscous Oil in Kuwait calls for Improved Oil Recovery scenarios. In Kuwait unconsolidated sandstone formations, the sandstone intervals represent extensive reservoir intervals of sand separated by laterally extensive non-reservoir intervals that comprise finer-grained, argillaceous sands, silts and muds. The reservoir is shallow with high permeability (above 1000 mD) and under bottom aquifer pressure support. Due to strong viscosity contrast between oil and water, after breakthrough, the water cut rises quickly resulting in strong loss of production efficiency. Mitigating water production is thus mandatory to improve production conditions.

The candidate wells have 2 to 3 open intervals in different rock facies with comingle production. The total perforated length is between 38 and 48 ft. Production is through PCP at a rate of around 300 bpd and BS&W is between 71 and 87%.

The technology applied utilizes pre-gelled size-controlled product (SMG Microgels) having RPM properties, i.e. inducing a strong drop of relative permeability to water without affecting oil relative permeability. The size is chosen to selectively treat the high-permeability water producing zones while preserving the lower-permeability oil zones. The chemical can also withstand downhole harsh conditions such as salinity of around 170,000ppm and presence of 2% H2S.

The treatment consisted of bullhead injection of 300 bbls of pre-gelled chemical through tubing. The first results seem very favourable, sincefor two wells, the water cut has dropped from 80 to 40% with almost same gross production rate. The incremental oil is more than 100 bopd. The third well did not show marked change after WSO treatment. The wells are under continuous monitoring to assess long-term performance.

Such result, if confirmed, may lead to high possibilities for the improvement of heavy-oil reservoir production under aquifer support by mitigating water production with simple chemical bullhead injection.
Pore-Scale Imaging of Tertiary Low Salinity Waterflooding in a Heterogeneous Carbonate Rock at Reservoir Conditions
Authors: Selem Ahmed M. , Agenet Nicolas , Blunt Martin J. , Bijeljic Branko
Published: September 2021

We investigated pore-scale oil displacement and rock wettability in tertiary low salinity waterflooding (LSW) in a heterogeneous carbonate sample using high-resolution three-dimensional imaging. This enabled the underlying mechanisms of the low salinity effect (LSE) to be observed and quantified in terms of changes in wettability and pore-scale fluid configuration, while also measuring the overall effect on recovery. The results were compared to the behavior under high salinity waterflooding (HSW).

To achieve the wetting state found in oil reservoirs, an Estaillades limestone core sample was aged at 11 MPa and 80°C for three weeks. The moderately oil-wet sample was then injected with high salinity brine (HSB) at a range of increasing flow rates, namely at 1, 2, 4, 11, 22 and 42 µL/min with 10 pore volumes injected at each rate. Subsequently, low salinity brine (LSB) was injected following the same procedure. X-ray micro-computed tomography (micro-CT) was used to visualize the fluid configuration in the pore space. A total of eight micro-CT images, with a resolution of 2.3 µm/voxel, were acquired after both low salinity and high salinity floods. These high-resolution images were used to monitor fluid configuration in the pore space and obtain fluid saturations and occupancy maps. Wettability was characterized by measurements of in situ contact angles and curvatures.

The results show that the pore-scale mechanisms of improved recovery in LSW are consistent with the development of water micro-droplets within the oil and the expansion of thin water films between the oil and rock surface. Before waterflooding and during HSW, the measured contact angles were constant and above 110o, while the mean curvature and the capillary pressure values remained negative, suggesting that the HSB did not change the wettability state of the rock. However, with LSW the capillary pressure increased towards positive values as the wettability shifted towards a mixed-wet state. The fluid occupancy analysis reveals a salinity-induced change in fluid configuration in the pore space. HSB invaded mainly the larger pores and throats, but with LSW brine invaded small-size pores and throats. Overall, our analysis shows that a change from a weakly oil-wet towards a mixed-wet state was observed mainly after LSW, leading to an incremental increase in oil recovery.

This work established a combined coreflooding and imaging methodology to investigate pore-scale mechanisms and wettability alteration for tertiary LSW in carbonates. It improves our understanding of LSW as an enhanced oil recovery (EOR) method for potential field-scale applications. The data provides a valuable benchmark for pore-scale modelling as well as an insight into how even modest wettability changes can lead to additional oil recovery.
Simulation of a Cyclone Separator to Improve the Efficiency of Gas Purification from Mechanical Impurities
Authors: Abrorov Khasan
Published: September 2021

This paper provides an overview of methods for dealing with mechanical impurities, justifies the choice of a suitable method and prototype for the conditions of the field. A methodology for designing cyclone separators of JSC "NIIOGAS" is presented, in accordance with which a theoretical calculation of the design of a cyclone separator was carried out. A solid model of a computational cyclone separator in the SolidWorks software was created, a computer simulation of a gas flow with the presence of mechanical impurities of various granulometric composition was carried out, based on the results of which conclusions were made.
Plunger Style Optimization by Machine Learning
Authors: Zhong Zhikai
Published: September 2021

Oil and gas wells often need artificial lift technologies to help extract reservoir fluids as the wells age and the reservoir pressure decreases–among those technologies is plunger lift. Plungers are metal cylinders that fit snug inside the tubing in which they are still able to slide freely. Plungers are often used with gas lift: they get pushed up and down the tubing like a piston to unload all the fluids by periodically shut in and open up the well. Many plungers contain a one-way valve that enables them to fall through flow easily and rise to the surface with a seal to prevent fluid slippage. There are many styles of plungers based on their weight, fall speed, and embedded one-way valves’ mechanism, and they should be used in different kinds of wells. Plungers can be grouped into five major different categories. This project utilizes machine learning and data analytics to predict what the most optimal type of plungers is for a given well in order to reduce gas injection and maximize liquid production.

To accomplish this project, more than two million rows of raw plunger lift production data were queried using SQL, a database query language, then pivoted, cleaned, and turned into a data table with approximately two hundred twenty thousand rows. The data came from about 900 wells with a time span of more than 400 days of production. Utilizing the python package Scikit Learn's random forest regressor, five separate machine learning models were trained, tuned, and cross-validated to predict the daily revenue and/or efficiency of a well if it were to run with the corresponding style of the plunger. The models were able to achieve about .85-.90 accuracy scores. On the other hand, a data visualization guide was built to visualize all the past plunger operation history to analyze the efficiency of a type of plunger; it also acts as an educational tool for operators to study the behaviors of different plungers in various wells.

The results of this project were achieved by field testing. Given that there was a time constraint, approximately ten wells were tested with eight of them showing revenue and/or efficiency improvements of 5-10%. More testing, tuning, and data gathering need to be done in the future to improve the project to apply at a larger scale.
Leukocyte and Monocyte Counts as Predictors for Metabolic Syndrome, Hypertension and Type 2 Diabetes in Taiwan Citizens: a 9-year Longitudinal Study
Authors: Li Yen-Wei , Kao Tung-Wei , Kuo Chao-Yin , Chang Pi-Kai , Chen Wei-Liang , Wu Li-Wei
Published: September 2021

Cardiovascular disease whose correlation with metabolic syndrome and diabetes has been well established. As an aspect of preventive medicine, we conducted a 9-year longitudinal study to identify the relationship between easily measured hematologic parameters, future metabolic syndrome (MetS), hypertension and type 2 diabetes mellitus (T2DM) according to age distribution. Divided into three groups according to age (young age: <40, middle age: ≧40 and <65 and old age: ≧65), 10,328 participants, receiving general medical inspection at the health management centre of Tri-Service General Hospital (TSGH) in Taiwan from 2007 to 2015, had been enrolled in the present study. Through multivariate regression analyses, the hazard ratio (HR) of total and subtype leukocyte count for MetS along with its components, hypertension and T2DM were demonstrated. All MetS components revealed significant association with total leukocyte count in multivariate regression models. Total leukocyte count was associated with future MetS, hypertension and T2DM despite of age at first, but failed in adjusted HR for the old group. Additionally, monocyte count showed significant association with all the aforementioned diseases only in middle-aged subjects but failed in the other two groups. Our results explore the promising value of total leukocyte count and monocyte count to identify the high-risk subjects, especially meddle-aged ones, having MetS, hypertension, and T2DM whether in the present or future.
MicroRNA composition of plasma extracellular vesicles: a harbinger of late cardiotoxicity in long-term survivors of acute lymphoblastic leukemia treated with doxorubicin
Authors: Totoń-Żurańska Justyna , Sulicka-Grodzicka Joanna , Seweryn Michal , Pitera Ewelina , Kapusta Przemyslaw , Konieczny Paweł , Drabik Leszek , Kołton-Wróż Maria , Chyrchel Bernadeta , Nowak Ewelina , Surdacki Andrzej , Grodzicki Tomasz , Wołkow Pawel
Published: September 2021

The use of doxorubicin is associated with an increased risk of acute and long-term cardiomyopathy. Despite the constantly growing number of cancer survivors, little is known about the transcriptional mechanisms which progress in the time leading to a severe cardiac outcome. It is also unclear whether long-term transcriptomic alterations related to doxorubicin use are similar to transcriptomic patterns present in patients suffering from other cardiomyopathies. Here we have sequenced miRNA from total plasma and extracellular vesicles (EVs) from 66 childhood acute lymphoblastic leukemia survivors treated with doxorubicin and 61 healthy controls (254 samples in total). We analyzed processes regulated by differentially expressed miRNA and cross-validated our results with the data of patients with clinically manifested cardiomyopathies. Our analyses indicate that the circulating compartment used for inspection should be selected with particular attention. miRNAs contained within EVs may be particularly informative in terms of cardiomyopathy development and may regulate pathways related to neurotrophin, transforming growth factor beta or epidermal growth factor receptors (ErbB). Among miRNAs differentially expressed in vesicles, which additionally are also most variable between groups, we identified those correlated with echocardiographic parameters, including miR-144-3p and miR-423-3p and respectively for plasma miRNAs: let-7g-5p, miR-16-2-3p. Among these, vesicular miR-144-3p correlates with the highest number of echocardiographic parameters and is also differentially expressed in the circulation of patients with dilated cardiomyopathy. We also show that in ALL survivors' distribution of particular miRNAs, e.g., miR-184 between plasma and EVs is different than in healthy controls. This suggests persistent alterations within the cellular sorting and exporting system.
Higher Uric Acid Serum Levels Are Associated With Sarcopenia In West China: Results From The WCHAT Study
Authors: Liu Xiaolei , Chen Xiaoyan , Hu Fengjuan , Hou Lisha , Xia Xin , Luo Shuyue , Zhang Gongchang , Peng Xuchao , Sun Xulian , Yue Jirong , Dong Birong
Published: September 2021

Background: Sarcopenia is the decline in muscle strength and mass attributed to aging. The pathogenesis of sarcopenia may be triggered by oxidative stress and uric acid (UA) has strong antioxidant properties. The aim of this study was to investigate the relationship between UA and sarcopenia in community-dwelling adults of West China using the baseline data of West China Health and Aging Trend (WCHAT) study. Methods: 4236 adults aged 50 years or older in communities of west China were enrolled in this study. We applied AWGS 2019 criteria to define sarcopenia. Muscle mass was measured using skeletal muscle index (SMI) based on bioimpedance analysis (BIA). Handgrip strength (HGS) and gait speed (GS) were recorded, respectively. Different variables like anthropometry measures, life styles, chronic disease and blood test were collected.Results: Participants were grouped according to UA quartiles by gender. After adjusting for potential confounders, a significant association between serum UA levels and sarcopenia was shown both in men and women. And a significant association between serum UA levels and HGS in women was shown as a inverted J shape. Besides, the association between the UA quartiles and SMI was significant, irrespective of gender.Conclusions: Our results showed that a specific range of serum UA levels might be associated with sarcopenia and better HGS or SMI among Chinese adults aged over 50. Higher UA serum levels might slow down the progression of sarcopenia.