bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shifting Turner's Paradigm: Gas Wells Can Produce in Slug Flow
Authors: Marino M. , Schiferli W. , Veeken C. A. , Smith J. 
Published: October 2017

Abstract
This paper aims at improving the understanding of gas wells stability and to shift Turner's paradigm, i.e. to demonstrate that, under specific circumstances, stable production below the liquid loading rate in the slug flow regime is feasible. Field examples are presented together with modelling results that highlight how stable slug flow gas production can be sustained and promoted.
The new approach to evaluate well stability is based on conventional nodal analysis, but makes use of a total pressure drop curve rather than only looking at the well. This curve includes the wellbore, the choke and – in very tight reservoirs – the pressure drop over the near-wellbore reservoir. The minimum in this combined pressure drop curve yields the minimum flow rate for well stability. This method was applied and tested on several gas wells. Examples include two gas wells with drawdown limitations, one to avoid halite precipitation and one to reduce sand production, and a very tight gas well. Both steady state nodal analysis and dynamic simulators were used.
Whereas a conventional nodal analysis indicated that stable production was not possible since the inflow performance curve and tubing performance curve did not intersect right of the minimum, the total pressure drop curve correctly predicted that these wells could flow continuously below their conventional critical rate. For the wells with drawdown limitations, this meant being able to further choke back the wells to mitigate halite precipitation and sand production, de facto extending the well production life and reducing operational intensity. For the tight gas well, this meant improving forecasting of a well for which intermittent production was deemed necessary. In conclusion, in cases where a choke or tight reservoir adds significant pressure drop, well stability is found to be dictated by the total pressure drop curve. This improved analysis can yield more accurate production forecasts and prevent unnecessary interventions.
The innovative total pressure drop curve presented in this paper shifts a paradigm set by Turner in 1969: gas wells can now produce in slug flow. Furthermore, the fact that this methodology uses the existing and well known nodal analysis will simplify its wide diffusion and implementation.
Inverted ESP Changing the Game in Water Coning Control in Water Drive Reservoirs - North Kuwait Case Study
Authors: Anthony E. , Elaila S. , Al-Maqsseed N. , Areekat M. 
Published: October 2017

Abstract
Water Coning is a reservoir phenomenon that is particularly more challenging in reservoirs where Kv/Kh &gt; 0.5. To maximize production rates and ultimate hydrocarbon recovery from its water drive reservoirs, North Kuwait shifted its exploitation strategy from vertical to horizontal completions. When water broke through, however, remedial efforts were limited, complex, and certainly short-lived since the water moves laterally along wellbore to adjacent compartments. A more effective solution to control the water cone was implemented in a vertical well with good success, but with some operational limits. This completion used a conventional ESP with Y-tool to create a counteractive pressure drawdown just below the Oil/Water contact in an effort to limit the progression of the water cone. The major limitations with this ESP configuration were casing size (can only be used in 9⅝" casings and larger), and rate restrictions (limited to 4,500 BPD injection rate, beyond which shroud erosion is expected). Cone Control technology, is to create a pressure drawdown (ΔP), just below the OWC marginally more than the ΔP across the perforated interval within the Oil leg. This drawdown retards the progression of the water cone, and can best be achieved using an inverted, bottom-discharge high-volume ESP. Inverted ESPs were selected after the limited success achieved from utilizing a shrouded conventional ESP with Y-tool in the original Cone Control completion. Inverted ESP’s eliminated both constraints, and added the advantage of being shorter and more compact, suitable for wells with higher dogleg severities. The Inverted ESP is used for subsurface disposal, and can be injected into an underlying hydrocarbon-free aquifer, or reservoir requiring pressure support.
System Density of Oil-Gas Mixtures: Insights from Molecular Simulations
Authors: Mehana Mohamed , Fahes Mashhad , Huang Liangliang 
Published: October 2017

Abstract
Gravity segregation of reservoir fluids is mainly controlled by system density. While most of the gases used in the field for the purpose of Enhanced Oil Recovery (EOR) result in a reduction in system density, Carbon Dioxide (CO2) can result in an increase of the mixture density upon mixing. Experimental observations confirmed this behavior. In addition, field operations report an early breakthrough for CO2 flooding, which is related to the associated gravity segregation due to the abnormal density behavior. However, the molecular interactions at play that have an impact on the observed macroscopic behavior have not been well-understood or deeply investigated. Molecular simulation of methane, propane and carbon dioxide mixtures with octane, benzene, pentane and hexadecane are studied up to the miscibility limit at temperatures up to 260 °F (400 K), and pressures up to 6000 psi (400 bar). There is a proximity between the molecular simulation predictions of the physical properties and those obtained through experimental work and EOS. It is evident that oil-CO2 mixtures sustain their system density to a higher gas mole percent compared to other gases, with the system density in some cases exceeding the pure liquid hydrocarbon density even when gas density at those conditions is lower. Our results have demonstrated that the intermolecular columbic and induced dipole interactions, and the stretching of the alkane molecules, the proposed mechanisms in literature, might not be the key to understanding the oil-CO2 density behavior. However, the molecular size of the gas seems to play an important role in the density profile observed.
A Generalized Derivative-Free Rate Allocation Optimization for Water and Gas Flooding Using Streamline-Based Method
Authors: Tanaka Shusei , Kam Dongjae , Xie Jiang , Wang Zhiming , Wen Xian-Huan , Dehghani Kaveh , Chen Hongquan , Datta-Gupta Akhil 
Published: October 2017

Abstract
Rate allocation optimization for water and gas injection/production processes is typically complex, requiring multiple simulations to find the optimal reservoir management strategy for improved economic value of the asset. The objective of this paper is to develop and demonstrate a fast and robust derivative-free workflow which improves economic values via optimizing water and gas flooding rate allocation by streamline-based technique.
Streamline-based rate allocation optimization has been demonstrated to be a powerful tool for application to waterflood operations. However, the utility of the technique has been limited in optimizing the Net-Present-Value (NPV) for improving the economics of these operations. In addition, the theoretical assumptions on physics limit its application to pressure-sensitive secondary or tertiary recovery processes such as gas injection. In the proposed workflow the expected NPV of each injector-producer pairs are evaluated at a given future business decision such as next infill time by using static, dynamic, and economic parameters such as price and discount rate along with time-of-flight. Then new flow rates are allocated based on the performance of the wells ranked by expected NPV to achieve better future economic value.
The proposed workflow was first compared with previous streamline-based rate reallocation technique using series synthetic models. Although all tested methods showed better performance when compared with the base scenario, our proposed approach showed improved performance in terms of NPV, primarily due to proper handling of the reservoir dynamics and economic value in the objective function. The workflow was then benchmarked by a case study of a field subjected to waterflood and gas injection. The results of proposed approach were comparable to the population based derivative-free techniques such as Genetic Algorithm (GA) or Particle Swarm Optimization (PSO) where many simulations are required to achieve a similar outcome.
The proposed workflow was coupled with next generation simulator and applied to various field studies. The method provides the ability to simultaneously control injector and producer flow rates for improving the economic value under multiple constraints. The workflow retains advantages of the conventional streamline-based technique such as fast post processing and ease of application to a broad field studies.
Identifying Cost-Effective Waterflooding Optimization Opportunities in Mature Reservoirs from Data Driven Analytics
Authors: Yrigoyen Andres , Saputelli Luigi , Chacon Alejandro , Chegin Jorge 
Published: October 2017

Abstract
Evaluating waterflooding process performance is one of the main concern prior to implementing such secondary recovery method. Big and complex numerical models are not the best tool for daily surveillance and monitoring. However, by applying analytical and data driven models to provide fast solutions and efficient diagnosis of waterflooding processes opens a new window to examine process advantages to improve injected water distribution and to provide recommendations for accelerated short-term production scenarios. By incorporating data driven techniques to perform history matching and forecast the reservoir management process gets improved because early action can be taken to minimize water production, well operational problems and cost reduction.
Data analytics techniques also help to reduce time-consuming data preparation and processing, and data uncertainty (i.e. geological, petrophysical, reservoir engineering). Effective reservoir management needs quick ways to predict injected fluid distribution to improve areal and vertical sweep efficiency during secondary and tertiary recovery processes. Consequently, simpler methods that provide fast results to substitute reservoir simulation (for surveillance and monitoring) are important for continuous reservoir management. In this work Capacitance Resistance Model (CRM), streamlines, and Normal Equation Algorithm (NEA) models were used as proven methods to address the above challenges. CRM and NEA model were used to perform history-matching and forecast based on production and injection scenarios to improve waterflood process oil recovery factor.
During this study, two scenarios were designed to test each model to investigate the advantages of (CRM) and NEA by incorporating different levels of data perturbation and to compare prediction accuracy. CRM and data driven models were able to reproduce historical data with low degree of error. CRM quickly compute allocation factor between injector and producer pairs. Allocation factor calculation allow the evaluation of waterflood performance by pattern while identifying the poor sweep efficiency areas. Better connectivity zones were easily identified by matching high allocation factor for the injector-producer pairs.
This work is an effort to demonstrates the value of predictive and prescriptive data analytics to effectively replicate production history, and generate solutions in a simple and fast approach, yet powerful to find optimal solutions in a short period of time. Using data driven models, a larger number of scenarios were run to optimize reservoir performance without performing expensive numerical simulation computations and to reduce engineering load to build, maintain and update models by around 80%.
Integrated Analysis of Reservoir Architecture and Quality for Effective Production: A Low Permeability Reservoir in Lower Jurassic Sandstones, West Siberian Basin
Authors: Gorbovskaia O. A. , Pishchuleva A. V. , Belozerov B. V. 
Published: October 2017

Abstract
The work deals with a conceptual geological model creation that is necessary for further geocellular modelling and field development scheme optimization. The object of the study is Lower Jurassic terrigenous formations U15 and U14 of Urman-Archin fields group located in south-eastern part of West Siberian basin. Low quality of these reservoirs requires detailed geological analysis for allocation of the most perspective zones. This work integrates the results of seismic, paleogeographic, palaeotectonic, logging, well testing, macroand microscopic core analyses. It was discovered that the formations were deposited in fluvial conditions. Moreover, the evolution of the river system is observed across the interval of U15-U14 formations – braided streams change to meandering ones. The sedimentary processes determine vertical and lateral lithological heterogeneities as well as the primary distribution of grains of different size characterizing the activity of depositional agent. However, it was found that lithology and grain size is not directly related to the presence of reservoirs, so sedimentary conditions are not the key factor of reservoir continuity. Analysis of diagenetic alternations of the formations’ rocks showed that their compaction influenced reservoir quality and its lateral heterogeneity. In some parts of the studied area the rocks are more compacted, and, consequently, they have lower porosity and permeability. Tectonic movements caused non-uniform rock compaction across the area. In addition, they led to reservoir compartmentalization. There are hydrodynamically isolated blocks, which may influence fluid distribution within the formations and should be considered during development scheme planning. Significant influence of diagenetic alternations on the reservoir properties is not typical for the deposits in terrigenous rocks within West Siberian basin, so this conclusion should be taken into account when analyzing similar reservoirs in this region.
A Game of Horizontals: The Dance of Gas Intrusion, Percolation, and Migration vs Mud-Weight Increase.
Authors: Stone Rick , Nauduri Sagar , Medley George 
Published: October 2017

Abstract
Gas intrusion, gas percolation, and bottoms-up gas are very common challenges when drilling and completing deviated, directional, and horizontal wells. Improper assessment and lack of mitigation plans can greatly increase associated risks, resulting in HSE problems and potential catastrophic events.
Several factors impact the manifestation of so-called "gas intrusion," such as the type of formations encountered while drilling and the method of drilling selected by the operator. After a great deal of research, several solutions were developed and became commonplace throughout the industry.
One of the key (yet debatable) techniques has been to increase the drilling mud-weight. This method was developed successfully for controlling gas intrusion during conventional drilling of vertical wells. In some cases, it can have quite the opposite effect, especially in deviated, directional, or horizontal wells. This is primarily because of the differences in the way fluids in horizontal wells interact under the influence of gravity (when compared with vertical wells). Even in this day and age, operators and company men sometimes inadvertently play a "dance" of gas intrusion and migration vs. mud-weight increase, a game of horizontals orchestrated by Mother Nature.
A Multifunctional Coated Proppant: A Review of Over 30 Field Trials in Low Permeability Formations
Authors: Radwan Amr 
Published: October 2017

Abstract
This paper presents a tailored coated proppant that provides improved solutions for various hydraulic fracturing challenges. The coating aims to enhance proppant transport with slickwater fluids while improving the hydrocarbon mobility into the proppant pack and reducing respirable crystalline silica during the operations. The paper discusses results from over 30 field trials in multiple low permeability formations.
The novel multifaceted coating was designed to modify the wettability of proppants’ surfaces to increase the surface's affinity for gases and reduce the generation of respirable airborne particles. By adding small volumes of gases into the proppant-laden slurry, gas bubbles get attached to the surface of the proppant leading to significant reduction in its apparent specific gravity. In order to prove the operational and economic advantages of the multifunctional proppant, a series of novel laboratory experiments were conducted under various operational conditions, followed by numerous field trials in several low permeability formations.
The laboratory tests showed that the coated proppant can stay suspended in the presence of gases for extended period of time. The laboratory evaluation involved testing under pressures and temperatures up to 12,500 psi and 400°F with different fluid systems made from both fresh and high-salinity waters. Oil mobility tests showed that the oil flow rate was increased by 74% compared to uncoated sand. Several multistage fracturing treatments executed with significantly higher proppant concentrations up to 6.1 lbs/gal in typical slickwater treatments when used with 1.5 – 10 % foam quality. Onsite measurements have proven that the coating reduced the generation of respirable airborne particles down to 10 – 30 μg/m3 throughout the proppant lifecycle. Data obtained from numerous field trials showed that the novel proppant technology resulted in improved well productivity, increased oil cuts and reduced water production.
Analyzing Gas Well Production Data through the Application of the Connected Reservoir Storage Model
Authors: Childers D. , Wu X. 
Published: October 2017

Abstract
This work presents a novel approach through the use of the connected reservoir storage model to accurately predict production performance of gas reservoirs, which have a complex reservoir geometry and have a large uncertainty of reservoir energy support. Based on the deconvolution of measured pressures and rate data from a well, a gas reservoir performance will be modeled using a group of normalized quantities with which the wells behavior can be accurately predicted in all flow regimes. No foreknowledge of reservoir geometries, petro-physical properties or fluid properties are required in the development of this analysis.
Reservoir storage is a time function defined as the product of the total compressibility and the reservoir volume at a particular time. Unlike with classical or curve fitting decline curve analysis, the connected reservoir storage model is based on the pressure diffusivity theory by the normalized production rate and normalized cumulative production volume through deconvolution methods. With the knowledge of reservoir volumes, the long term well performance of gas reservoirs can be predicted.
Through the development of the connected reservoir storage model, three profiles can be ascertained, and are interrelated, to shed valuable insight into the production potential, and health, of an unconventional gas reservoir. The three curves are the pressure drop curve, normalized curve and connected reservoir storage curve. Utilizing the three curves stated above embodies a more powerful reservoir performance analysis technique for predicting the production potential of complex reservoirs.
The connected reservoir storage model will be presented from the fundamental material balance approach and mathematical equations will be derived for this model as it relates to gas reservoirs. This concept will then be validated through the development of synthetic models with varying permeabilities, porosities and well geometries through the use of a reservoir simulation suite with known reservoir parameters along with the utilization of deconvolution techniques. Limitations involved with this method will be highlighted in the development procedures.
The connected reservoir storage model allows for the bridging of the production decline and reservoir pressure response from production data found in the public domain. This concept allows one to evaluate and forecast current and future volume production, reservoir pressure behavior, average reservoir pressure and determine original fluids in place with no prior knowledge of reservoir geometries, petro-physical data or fluid properties. With the development of this model decline curve analysis (DCA) can be extended into the transient regime of the production period.
Deep Learning for Steam Job Candidate Selection
Authors: Cheung Chung Ming , Goyal Palash , Tehrani Arash Saber , Prasanna Viktor K. 
Published: October 2017

Abstract
Choosing the most profitable wells for steam jobs is of high value given the cost and resources required for the procedure. To find the best candidates, we develop a system with two parts: i) An autoencoder to reduce the dimensionality of input data, ii) A kernel regression to predict the production gain. We show the benefit of application of autoencoder-extracted features by comparing the resulting accuracy with manually extracted features. To train our system, we use a training data set consisting of 3200 steam jobs and evaluate it on a testing data consisting of 800 steam jobs. We use various metrics, e.g., mean squared error (MSE), Spearman correlation and overlap coefficient, to evaluate the performance of the proposed system. We show that our system improves upon the existing methods significantly. For example, it can choose 50 steam job candidate wells out of 800 such that 98% of them are in the top 100 wells. The system also outperforms the wells chosen by engineers working in oilfield. We achieved an average percentage gain in production of 176% compared to 124% achieved by engineers.