bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Gas Lift Compressor Adjust Injection With Dynamic Conditions
Authors: Munding Paul , Hudson John , Karami Hamidreza 
Published: October 2020

Abstract
Approximately 40% of unconventional wells in the United States with artificial lift are using gas lift. One of the blessings of gas lift is that it is very forgiving and rarely fails. This has led some operators to the conclusion that gas lift doesn’t require a proper control and optimization scheme. The objective of this study is to use field data and show the importance and benefit of a controlled and optimized gas lift compressor to aid production.
The intelligent gas lift compressor utilizes a heavy computational process of taking a composite Vogel reservoir inflow model coupled with a Hagedorn & Brown outflow model that informs the Guo model to solve for a minimum critical rate to lift liquid droplets out of the wellbore. First, an empirical range of injection rates is used to find the rate with maximum unloading as indicated by a drop in casing injection pressure. Once this rate is found, reservoir inflow performance relationship (IPR) parameters are estimated to meet that condition. These parameters are held constant for a time period and injection rate needed is calculated based on production rate and pressure coming into the programmable logic controller (PLC) via digital connections. This approach is tested on a well and the production is monitored over a 3-month period. The collected data are used to analyze the benefits of an intelligent gas lift compressor control.
The data from a well with this intelligent gas lift system is monitored over a 3-month period. This includes a 20-day period of the compressor searching for an injection rate that shows to be the most efficient. Then the compressor control is set up with a critical rate control mode. This calculation is performed with an edge server that runs the intense calculations every minute to instruct the compressor what volume of injection it needs to achieve manipulation of an automated suction control valve and speed control of the engine driver. The surface casing pressure data shows a very stable unloading behavior profile, which is confirmed with very stable oil and gas production data over the observation period. An estimate of gained production during the periods of high line pressure along with stable unloading is given as the justification for outfitting the well site with the intelligent compressor controls. Despite gas lift’s importance as a lift technique, its control and optimization are still not properly addressed within the industry. This work’s proposed intelligent gas lift scheme can be a potentially valuable solution to unstable unloading of liquids, and benefit the operators significantly in production and revenues.
A New Way of Looking at Safety Culture Maturity Models-The Lens of Employee Engagement
Authors: Knode Thomas 
Published: October 2020

Abstract
Over the years, various authors have put forth cultural maturity models for organizations to describe the pathway towards high levels of safety performance. While these models are readily accepted and viewed as benchmarks for assessments of the state of safety culture, what lies beneath the premise, and what may we be searching for? We now know through both the study of organizations employee attitudes and brain science that individuals respond well to having a say in their work output and environment. If we apply the lens of employee engagement to a typical culture maturity model, it will look different. Ideally, every employee would feel empowered to identify hazards and be a party to the development of risk mitigation solutions. If we ask employees to participate on discreet occasions in observation programs, toolbox talks, and safety committees, does that guarantee full engagement? An employee who is fully engaged in safety is looking for it beyond those moments and may be better prepared to manage risk.
A new model looking at employee engagement and active participation in workplace safety would move along a continuum. Historically there has been a lack of regulatory guidance and legislative framework to support active participation, leaving individuals and organizations to make their judgments and actions. From there, governments implemented laws and regulations that formed the basis of expectations. Industry and companies then realized that management systems would help integrate the regulations with their specific processes to form a complementary set of requirements. We then understood that safety leadership from supervisors was needed to ensure workers understood and followed the process and adhered to the rules. Finally, we began asking the front line to participate, and ultimately own responsibility for looking out for themselves and each other. Each step must be built on the previous as it would be challenging to create a safety culture in the absence of external and internal requirements or safety leadership from supervisors. This continuum helps drive the maturity from the belief that "They own safety" to "We own safety" and encourage behavior beyond discreet point-in-time activities to a more complete and engaging program and workforce.
This different way of looking at cultural maturity through the lens of what should be expected of supervisors and employees may help organizations develop plans and strategies to achieve an incident and injury-free workplace.
Qualification and Deployment of Float Equipment as an Independent Mechanical Barrier in Unconventional Wells
Authors: Champeaux Christopher J. , Arrazola Alvaro J. , Patin Vincent , Stair Todd , Rogers Hank 
Published: October 2020

Abstract
The generally overlooked implications of intentional or unintentional overdisplacement of shoe track cement in production casings, resulting in what is commonly known as a wet shoe, are discussed in addition to how these implications/risks have been addressed and mitigated with recent developments in float equipment technology and operational methods. Additionally detailed are the operational, cost, and production efficiencies afforded by an engineered wet shoe system for primary cementing and completion operations.
To utilize an intentionally overdisplaced production casing shoe track, or wet shoe, a float valve was developed, tested, and manufactured with the intent to be used as an independent mechanical barrier, preventing inflow of hydrocarbon into the casing. This was accomplished by performing a float equipment qualification, meeting the requirements in API SPEC 10F (2018), and exceeding the requirements with additional testing comprised of static high-pressure and low-pressure testing with nitrogen to simulate formation gas pressure during cement phase change and before completion. Each discrete manufactured valve was also tested with low-pressure gas to validate each valve was fit for service before deployment. During a 20-well trial, a typical float check was used to test the barrier in place at the conclusion of cement displacement. Wellhead pressure was then monitored to confirm gas-tight integrity of the float equipment over time before completion operations.
New technology using float equipment, conventionally not regarded or considered for use as a mechanical barrier, was successfully developed and qualified for use as an independent mechanical barrier in uncemented shoe tracks and successfully deployed in low-permeability wells to maintain a two-barrier system without shoe track cement. This success was the culmination of the equipment design and qualification process with operational risk assessment/mitigation.
Identification of Fractures and Preferential Flow Paths Using Streamlines and Dynamic Data in Dual Porosity Dual Permeability Reservoir Models
Authors: Hongquan Chen , Changqing Yao , Akhil Datta-gupta , Ali A. Alturki , Majdi A Baddourah 
Published: October 2020

Abstract
Identification of the location and orientation of fractures and preferential flow paths using the dynamic reservoir response can provide insightful guidance for naturally fractured reservoir development and management. However, data assimilation for high-resolution fractured reservoir models using well responses is time consuming. The streamline-based technology has proven to be effective and efficient for subsurface flow modeling and inverse problems. We propose a novel and robust streamline tracing method in dual porosity dual permeability (DPDK) systems and an efficient workflow to identify fracture location in fractured reservoir models using dynamic data.
In DPDK models, the matrix-fracture interactions are typically described by non-neighbor connections (NNCs) which make streamline tracing non-trivial. We use a boundary layer method to reconstruct the fluxes and avoid flux discontinuities at NNCs. The flux reconstruction allows us to trace streamlines and compute the time of flight (TOF) in DPDK models. The fracture identification workflow relies on the streamline-based analytic sensitivity computation and rapid model calibration using dynamic data. Multiple realizations of fracture distribution are initialized and calibrated using observed well responses, for example water cut and BHP. The ensemble of calibrated fracture models is then used for uncertainty analysis, and a probability map of the spatial distribution of fractures is finally generated.
The power and utility of our approach are demonstrated using several applications. We first validate the streamline tracing algorithm for DPDK model by comparing its TOF with the result generated by the finite volume formulation of TOF generalized for compressible flow. Next, we validate the fracture identification workflow using a synthetic case by comparing the fracture probability map with the "true" fracture distribution. Finally, we apply our method to a DPDK model of a fractured reservoir and generate fracture probability map by calibrating multiple model realizations to well production and pressure data. The fracture probability maps serve as valuable tools to guide reservoir management and field development strategy.
The novelty of this work is the newly developed streamline tracing algorithm for DPDK models and the efficient workflow to generate fracture probability maps based on dynamic data. The proposed approach is easy to implement and can be coupled with commercial simulators for field scale applications.
First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska North Slope – Producer Responses and Operational Lessons Learned
Authors: Ning Samson , Barnes John , Edwards Reid , Schulpen Walbert , Dandekar Abhijit , Zhang Yin , Cercone Dave , Ciferno Jared 
Published: October 2020

Abstract
The US Department of Energy and Hilcorp Alaska, LLC are jointly cosponsoring a field pilot project entitled "First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil Enhanced Oil Recovery (EOR)." The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on Alaska North Slope (ANS). Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot which was designed to acquire field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Hydrolyzed polyacrylamide (HPAM) polymer injection started on August 28, 2018 using a custom made polymer mixing and pumping unit. Polymer solution properties such as concentration, viscosity, and filter ratio, have been closely monitored and adjusted as necessary. Operational procedures have been improved to ensure adequate injectivity and polymer propagation through the formation. Oil and water production is tested frequently to monitor water cut performance, and produced water is sampled and analyzed for polymer content. Tracers were pumped pre and post polymer injection startup to compare polymer flood breakthrough timing and sweep efficiency.
Polymer injectivity of the horizontal wells drilled in the Schrader Bluff NB sand is found to be sufficient to replace the reservoir production voidage although there were some declines as high viscosity polymer swept the near wellbore region. Production data show significant reduction in water cut and increase in oil production rate. No polymer production has been confirmed from the two horizontal producers after 23 months of polymer injection into the two supporting horizontal injectors. Tracer data show very low sweep efficiencies with waterflood alone, whereas significant improvement has been achieved with polymer flood. Many operational lessons have been learned and improvements have been made regarding polymer mixing, pumping, and onsite quality control, particularly in a challenging Arctic environment. Adequate polymer injection rate can be achieved with diligent monitoring and quality assurance of the properties of the injected polymer solution.
New Type Curves for Horizontal Well Rate Transient Analysis and Their Field Application
Authors: Su Chang , Zhao Gang , Cai Hua , Xiao Lei , Shen Xiaohong , Lu Kefeng , Yuan Wanju 
Published: October 2020

Abstract
This paper presents three sets of new integrative production decline type curves for the analysis of horizontal well production data in order to systematically estimate reservoir flowing capacity (kh), effective horizontal wellbore length and original oil/gas in place. In addition, diagnostics of dynamic flow regimes possible for the entire flow duration from early time transient to late time boundary dominated flow gives the proposed type curves unique value in field data analysis through using different idealized flow regimes as the reference systems. Comparing to the traditional classic type curves, these three sets of type curves offer more practical implemental strategy for well performance evaluation and reservoir formation characterization, resulting in less ambiguity in the outcome of data interpretation. The effects of horizontal wellbore length and reservoir geometry on the appearances and the characteristics of these three sets of new type curves are studied and documented. A detailed curve matching process has also been comprehensively developed to achieve systematically proper matching with field data using all of the three sets of type curves synchronously.
To showcase this work in field application, the production dynamics of a gas field containing two vertical non-commingled units, each being produced by a horizontal well independently, is analyzed using the three sets of new type curves. With successful estimation of the kh and the effective horizontal wellbore length, it helps geologists and geophysicists locate the "sweet spot" with more confidence and offer the potential to extend the seismic response pattern to support further exploration activity in this geology unit. The outcome of this work helped identify the existence of an untapped gas reserve in the lower unit, thus to promote the potential of infill drill to enhance ultimate gas recovery.
Multiphase Transient Analysis of Flowback and Early Production Data of Unconventional Gas Wells
Authors: Nguyen Kien , Zhang Miao , Garcez Jonathan , Ayala Luis F. 
Published: October 2020

Abstract
Analysis of fracturing water flowback data from hydraulic fractures in unconventional reservoirs plays an important role in determining key fracture properties and predicting future well performance. Current flowback data analysis tools mostly rely on empirical correlations and/or simplified models. This paper presents a semi-analytical, multiphase solution that is applicable to the analysis of not only water flowback but early gas production data of multi-fractured horizontal gas wells. The proposed solution couples a Green's function-based analytical solution for gas flow in matrix with a finite-difference numerical solution for two-phase (gas and water) flow in fracture domain. The validity of proposed semi-analytical solution is verified against simulation results generated using commercial numerical simulators. Inverse analysis techniques are developed based on the proposed semi-analytical solution and presented in the form of type curves. Synthetic case studies show that the proposed type-curve methods can provide explicit and accurate estimation of fracture and reservoir properties, including fracture conductivity, and fracture pore volume. For all case tested, the proposed model is shown to provide accurate and consistent prediction of reservoir performance and estimations of fracture properties while maintaining the simplicity of explicit, iteration-free calculations.
Evolution of Three Dimensional Fluid Phase Connectivity During Injection
Authors: Ganguly Eliza , Misra Siddharth , Wu Yaokun 
Published: October 2020

Abstract
The three-dimensional connectivity of the fluid phases in porous media plays a crucial role in governing the fluid transport, displacement, and recovery. Accurate three-dimensional quantification of the fluid phase connectivity following each fluid injection stage will lead to better understanding of the efficacy and efficiency of the fluid injection strategies. Two metrics for measuring the connectivity in 3D show robust performance; one uses fast marching method to quantify average time required for a monotonically advancing wave to travel between any two pixels and the other uses two-point probability function to approximate the average distance between any two connected pixels belonging to the same fluid phase. The two connectivity metrics are applied on the three-dimensional (3D) CT scans of one water-wet Ketton whole-core sample subjected to five stages of multiphase fluid injection to quantify the evolution of the three-dimensional connectivity of the three fluid phases (oil, water, and gas). The water-wet Ketton carbonate sample (4.9 mm in diameter and 19.5 mm in length) is subjected to five sequential stages of fluid injection: 100%-brine-saturated sample, oil injection, water-flooding #1, gas injection, and water-flooding #2. CT-scan of the core sample was acquired after each injection stage. The metric response for oil phase connectivity drops after each injection process, denoting a reduction in oil connectivity after each fluid injection. The spatiotemporal variations in the connectivity of a fluid phase help understand the fluid displacement across pores of varying sizes depending on the wettability.
Real Time Reservoir Fluid Log from Advanced Mud Gas Data
Authors: Hafidz Arief Ibnu , Yang Tao 
Published: October 2020

Abstract
In a recent paper (Yang et al., 2019a), we published a machine learning method to quantitatively predict reservoir fluid properties from advanced mud gas (AMG) data. This approach has clear advantages due to early access, low cost, and a continuous reservoir fluid prediction for all reservoir zones. In this paper, we demonstrate how real time reservoir fluid logs are generated and compare the results with PVT samples or production data from the same well.
We develop a workflow of generating reservoir fluid logs from AMG data and PVT database. The workflow consists of two main processes; first a quality assessment of AMG data and second the computation of reservoir fluid properties (in this paper we use gas oil ratio). The entire workflow is written in python and embedded into existing commercial petrophysics softwares. The final product of the workflow are three log tracks which we call the reservoir fluid logs and those are 1) the concentration readings of the AMG data, 2) the QC metric score, and 3) the predicted GOR log. These three logs are plotted together with other standard open hole logs such as gamma ray, neutron-density, sonic and resistivity log to get a more comprehensive formation evaluation.
Reservoir fluid logs derived from AMG data has two main advantages. First, it is the only approach to acquire continuous reservoir fluid properties along the well path. The continuous fluid profile can be used to understand the variation of reservoir fluids in both vertical and lateral direction. The second advantage is that the reservoir fluid log is obtained while drilling and therefore the information can be used to optimize the drilling process or the downhole sampling program during wireline operation.
In this paper, we demonstrate the application of the reservoir fluid logs in four conventional field cases. In the first study case we show the benefit of using the reservoir fluid logs in a horizontal well as a substitute for downhole fluid sampling. In the second case study, we demonstrate how the reservoir fluid log is utilized to optimize the downhole fluid sampling program which results in reducing the subsurface uncertainty. Next, we exhibit the use of the reservoir fluid logs to locate gas oil contact in a case where pressure data does not show clear distinction of gas and oil gradient in the reservoir. In the last example, we illustrate the use of reservoir fluid knowledge from AMG to characterizing the fluid variation across a field. The field applications demonstrate the success of the new method for conventional reservoirs, provided good-quality AMG data are available.
Rapid Production Forecasting with Geologically-Informed Auto-Regressive Models: Application to Volve Benchmark Model
Authors: Mohd Razak Syamil , Jafarpour Behnam 
Published: October 2020

Abstract
Reliable hydrocarbon production forecasting is necessary for optimizing field development and management and for assisting asset teams in making sound business decisions. In conventional reservoir modeling workflows, the data used to build a subsurface flow model comes with inherent uncertainties that are typically represented by, and propagated through, a set of prior model realizations. History matching, which is used to generate a set of calibrated reservoir models, typically involves repeated runs of computationally intensive forward simulations. For many existing automated history matching workflows, production data scarcity and its non-linearity with respect to reservoir input model parameters complicate the formulation and solution of model calibration problems. Additional complexities of the model calibration workflows include ensuring geologic realism (plausibility) and assessing the uncertainty of the solution and the resulting forecasts. Short-term predictions that can be used to inform daily operational decisions may be more conveniently derived from data-driven models without relying on complex integrated reservoir models and the related complex workflows. In this paper, we develop spatial autoregressive models to obtain short-term data-driven prediction models. To this end, the injectors and producers in a reservoir are related through a set of weights that can be interpreted as their lumped connectivity information, which may be initialized with prior geologic knowledge, whenever available. Each element in the matrix dictates the existence and strength of connectivity between any injector-producer pair. The well connectivity depends on the spatial geologic features within the reservoir, such as heterogeneity and compartmentalization induced by stratigraphic trap, faulting and diagenesis. As more dynamic data becomes available, the connectivity matrices are continuously updated to derive new forecast in a manner similar to the history matching process. When data is not sufficient to resolve the uncertainty in connectivity information, alternative scenarios may remain plausible. However, when additional information about inter-well connectivity is available, it can be imposed to reduce the uncertainty in inter-well connectivity. The model presents a practical tool that can be applied to evaluate and rule out certain inter-well connectivity scenarios and address what-if questions. We present the model and discuss its properties with both synthetic and field-scale examples.