bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic Effect of Thermally Stable Polymers for HPHT Brine-Based Drill-in Fluids
Authors: Zhou Hui , Galindo Kay A. , Zha Weibin 
Published: February 2017

Abstract
This paper discusses two high-temperature-resistant polymers (Polymers A and B) that have been developed as thermally stable, dual-functional viscosifiers and fluid-loss additives. Polymer A was designed for monovalent brines, while Polymer B works for divalent brines. These polymers enable the formulation of brine-based drill-in fluids that are stable at high to ultra-high temperatures, which is a significant improvement when compared to conventional biopolymer-based drill-in fluids. When combined, the two polymers work synergistically to further reduce fluid loss in monovalent brines.
The two thermally stable polymers were readily incorporated into various drill-in fluid formulations containing either monovalent or divalent brines over a broad range of densities. These drill-in fluids exhibited exceptional thermal stability and showed no stratification after static aging at 400°F for three days or at 375°F for seven days. A minimal change in fluid behavior was observed when comparing the rheological properties of the un-aged and aged samples. The samples provided excellent fluid-loss control, even after aging. A synergistic effect was observed between Polymers A and B when used in monovalent brines to further reduce the HPHT fluid loss with no negative impact on fluid rheology. Core flow tests showed that both fluids were non-damaging after acid-breaker treatment. It is anticipated that these polymers will extend the envelope to which water-based drill-in fluids can be successfully used to drill high- and ultra-high-temperature reservoirs. Recent successful field trial of the divalent brine-based fluid as a testing fluid further proved the robustness of these fluids for these reservoirs.
ESP Pump Considerations for Thermal Recovery Applications
Authors: McManus D. F. , Coates B. C. , Montilla C. A. 
Published: February 2017

Abstract
Steam-assisted gravity drainage (SAGD) and other thermal recovery applications require electrical submersible pump (ESP) equipment which can withstand extremely harsh oilfield environments with well conditions typically including high gas, sand, and scale concentrations in addition to the extreme temperatures and temperature cycles generated in the process.
Thermal recovery pump construction specifications were developed as part of a new tiered product line covering deployment of equipment in wells with bottom hole temperatures (BHT) as high as 250°C. Special construction considerations were implemented for stage compression, thrust handling, bearing design and materials of construction.
The new pump technology combines high temperature and abrasive handling features to extend product life and provide consistent reliability in thermal recovery applications. Enhanced temperature tolerance is achieved through reduced thermal stresses on internal components leading to better reliability and increased run life.
This next generation of thermal recovery pumps has been extensively field validated with systems utilizing the new technology currently installed and operating in over 400 wells.
Using Digital Rock Modeling to Estimate Permeability and Capillary Pressure from NMR and Geochemical Logs
Authors: Zhang Hao , Yuan Peng , Wu Jianghui , Mezzatesta Alberto , Jin Guodong , Satti Rajani , Koliha Nils , Bautista Juan , Crouse Bernd , Freed David 
Published: February 2017

Abstract
Permeability is one of the most important characteristics of hydrocarbon-bearing formations. Many approaches exist for estimating permeability. Formation permeability is often measured in the laboratory from core samples or evaluated from well test data. However, core analysis and well test data are expensive and available only from a limited number of wells in a field. On the other hand, logging data are available from almost all wells. Therefore, accurate prediction of the formation permeability using logging data becomes very attractive.
This paper describes a unique integrated modeling approach to predict formation permeability. By combining digital rock physics (DRP) and downhole logging measurements, formation permeability and capillary pressure were predicted using computational analyses. In this approach, a representative geometrical rock model for the formation at each given depth of interest was numerically generated. These numerical rock models are constrained by the formation parameters derived from NMR and geochemical logging data, i.e., all input parameters for the geometrical rock model such as the rock density, porosity, grain-size distribution, and grain mineralogy, are directly or indirectly obtained from downhole logging measurements. Then, using the geometrical rock model as input, pore size information, capillary-pressure curve, and permeabilities were obtained by computational analyses, including fluid flow simulations based on the lattice-Boltzmann method (LBM).
To demonstrate the method's feasibility and applicability, the proposed modelling approach was used on two sets of field data from a North Sea well and an Austin testing well. Permeability and capillary pressure were experimentally determined from laboratory measurements on cores and compared to the simulation results. The predicted permeability values from the proposed DRP approach were in good agreement with measured values from cores. The drainage capillary-pressure curves derived from rock models also matched well with laboratory measurements on core samples. The promising results generated from this study demonstrate the feasibility of a digital core analysis method that integrates a geometrical rock model with downhole logging measurements to accurately and reliably predict formation petrophysical properties in a cost-effective and timely manner.
Best Practices for Effective Wellbore Cleanup and Displacements in Open-Hole Sand Control Completions
Authors: Beldongar M. , Agee D. , Kumar A. , Offenbacher M. , Flamant N. , Lees A. , Gadiyar B. , Parlar M. 
Published: February 2017

Abstract
At some stage after drilling to target depth and before pumping the gravel packing treatment or before putting the well on production, the drilling fluid is typically displaced from the wellbore. Practices in the industry vary significantly depending on the primary drivers of the completion engineers, sometimes with disastrous results. Inefficient wellbore displacements can cause a variety of problems including increased non-productive time, reduced well productivity and incomplete gravel packing through various mechanisms.
In this paper, we detail our best practices to ensure efficient wellbore displacements for sand control completions. In the design phase, these involve various compatibility tests some of which are not commonly done and/or potential problems cannot easily be identified when they are done using conventional test procedures, modeling of fluid-fluid displacements and determining the fluid properties, pump rates and fluid volumes required for effective displacements in a given wellbore geometry and flow paths. On the rig site, they involve several quality control tests, some of which have not previously been implemented.
Development of an efficient Vibration Modeling Technique for Design-Related Optimization of Tools in the Global Drilling Environment
Authors: Hohl Andreas , Heinisch Dennis , Oueslati Hatem , Herbig Christian , Reckmann Hanno 
Published: February 2017

Abstract
Severe vibrations in drilling systems and bottom-hole assemblies can be caused by cutting forces at the bit or mass imbalances in downhole tools such as mud motors. Vibrations can lead to reduced drilling performance, poor measurement quality and reduced reliability. Models are important to understand the phenomena and predict loads. So far models are established that calculate the dynamic behavior of the drilling system from a global point of view: The drilling system is modeled with simplified geometry and placed in the drilling environment under consideration of the wall contacts with the borehole and the fluid properties. Global models are typically used for optimization of drilling parameters such as the rotary speed or the flow rate with respect to estimated dynamic loads. Global models are not suitable for detailed modeling and analysis for optimization on a tool component level.
A system-approach is established to overcome the limitations. A method is developed to connect a detailed 3D-model of a downhole tool with the model of the drilling system and the bit that is placed in the global drilling environment. The method enables new insights into the behavior of downhole tools that can be used to optimize downhole tools with respect to their reliability and their performance: Dynamic loads on tool components such as probes and pockets can be calculated to optimize the tool design and increase reliability. The probe design can be optimized to reduce the dynamic loads on sensor components and significantly increase the measurement quality.
In a case study the method is validated with measurements. Herein, torsional eigenfrequencies and corresponding mode shapes which are localized to the bottom-hole assembly as well as the resulting tool stresses and loads are considered. The impact of a dampening tool to mitigate torsional vibrations is discussed. In a second example the capability of the method to capture lateral vibrations under consideration of wall contacts and mass imbalances is shown. The method is used to optimize the design of a downhole tool to decrease the dynamic loads at sensor components that are placed in a probe.
The system-approach of the method allows to efficiently simulating the vibrational behavior of tool parts in an arbitrary detail and in a global drilling environment. The new method enables improved tool design for performance and reliability and increased measurement quality.
Ensemble-Based Assisted History Matching Using 4D Seismic Fluid Front Parameterization
Authors: Trani Mario , Wojnar Konrad , Moncorgé Arthur , Philippe Berthet 
Published: February 2017

Abstract
An ensemble-based 4D seismic history matching case is presented. Seismic data are re-parameterized as distance to 4D anomaly front and assimilated with production data. The field is a large turbiditic system, with initial fluid pressure close to the bubble point. Production causes the pressure to fall below the bubble point, resulting in a widespread gas-exsolution. The time-lapse change in gas saturation is considered responsible for the observed negative relative changes in seismic velocity seen over the all reservoir. This study is innovative for two reasons. First, the distance-to-front parameterization is applied to the gas-phase which appears everywhere in the field, rather than coming form an injection source like in previous application of the parameterization. Second, the binarization of the simulated time-lapse anomaly is performed circumventing the use of a petroelastic model; the petroelastic model would be necessary to relate the measurements to fluid properties changes and to decide a threshold for binarizing observations and pressure. However, the effect of gas is so widespread and evident that the petroelastic model is replaced by a clustering approach based on the gas saturation change of the reservoir cells. This study shows that adding the 4D re-parameterized seismic data in addition to the production data is keeping a reasonable match with production data while constraining the overall gas distribution in the reservoir to the observed seismic data.
Smart Magnetic Drilling Fluid With In-Situ Rheological Controllability Using Fe3O4 Nanoparticles
Authors: Vryzas Zisis , Kelessidis Vassilios C. , Bowman Michael B. , Nalbantian Lori , Zaspalis Vassilis , Mahmoud Omar , Nasr-El-Din Hisham A. 
Published: February 2017

Abstract
Engineering a drilling fluid tailored to meet specific downhole and environmental demands with tunable rheological properties can revolutionize the drilling industry. This study investigates magnetically controllable, water-based drilling fluid systems containing custom-made (CM) iron oxide (Fe3O4) magnetic nanoparticles (NP). These could potentially offer in-situ control of the drilling fluid viscosity and yield stress, under the application of an external magnetic field.
CM Fe3O4 NP were synthesized by the co-precipitation method. NP were added to the base fluid at two different concentrations (0.5 and 1.0 wt%). The magnetorheological properties were analyzed via a strain- controlled rheometer equipped with a magnetic field source in parallel-plate geometry giving a range of magnetic flux densities of up to 1 Tesla (T). The rheological behavior of the produced fluids was examined at room temperature of 25°C as a function of volume fraction, shear rate and magnetic field strength.
Transmission electron microscopy (TEM) analysis revealed that the NP was spherical with mean diameter of 6-8 nm, while the X-ray diffraction (XRD) pattern revealed peaks corresponding to pure crystallites of magnetite (Fe3O4) with no impurities. Superconducting quantum interference device (SQUID) analysis proved that the prepared NP displayed superparamagnetic behavior. Magneto- rheological measurements of the nanofluids indicated increase in the yield stress of up to +75% upon exposure to a magnetic field of 0.1 T, while larger changes of up to +609% were observed for higher concentrations of NP with intensities up to 0.7 T. The viscosity of the nanofluids monotonically increased under the presence of a magnetic field at all shear rates. The original rheological profile of the developed fluids was recovered upon removal of the magnetic field with an average deviation of +20% from the initial value, reflecting the disintegration of particle chains because of random movements due to Brownian forces.
Results highlight the potential for the development of multifunctional smart fluids that are greener and economical with tailor-made properties that can reversibly modify their rheological characteristics. Their unique ability to withstand a rapid increase in the viscosity and yield stress in the presence of an external magnetic field could enable drillers to formulate drilling fluid systems with instantaneous responses to continuously changing drilling environment, leading to enhanced well control and contributing to decreased non-productive time and costs.
Implementing Hips System in High Pressure Offshore Gas Producing Facilities
Authors: Alfaraj Ali H. 
Published: February 2017

Abstract
The objective of this paper is to demonstrate the design ingenuity and methodology used to complete a unique HIPS system, which was approved and chosen over the conventional and expensive Full Flare System solution for offshore unmanned high pressure gas production facilities.
Some special design features were implemented to fulfill the Safety Integrity Level (SIL-3) requirements and ensure high level of protection for personnel and facilities. Additionally, this paper will illustrate the challenges for facility operators to preserve the HIPS integrity level throughout the lifetime of the facilities.
Improved Resources and Reserves Estimation with the Combined Use of Scenario-Based Geological Models and Flow-Based Connectivity
Authors: Macé L. , Bogush A. 
Published: February 2017

Abstract
Adequate estimation of resources and reserves is critical for any prospect or field in the oil and gas industry. We propose improving the reliability of this estimation, first, by exploring the range of uncertainties through the use of scenario-based geological models; second, by ranking all generated models based on both static and dynamic responses; and, finally, by selecting few models representative of the uncertainty affecting the reservoir.
In any field, the unknowns largely outnumber the known data, and, typically, some of these known data are biased due to preferential sampling. The classical approach controls the range of uncertainties based on multiple equiprobable realizations generated by using different random paths and by randomly sampling the data range. Our method improves that approach by considering additional realistic geological scenarios, which allows expanding the uncertainty space to sample from. A large number of models is generated as a result.
Performing flow simulation on a large range of models would be computationally expensive. The common industry practice is to select models based on static volumetric measurements only. Our approach not only accounts for static volumes, but also adds computation of the flow-based connectivity using streamline simulation to account for the dynamic behavior of the models. A sensitivity analysis allows preserving only the most influential variables and discarding the negligible ones.
Finally, static and dynamic responses from the remaining models are analyzed to identify scenarios with consistent low, mid, and high values for both responses. This results in the selection of few representative models that provide a greater assurance of recovering the probability distribution than would have been achieved by following common industry practices.
Our methodology involves first enriching the uncertainty space by adding a dimension of geological scenarios. Then, it uses both static and dynamic responses to select a handful of representative models while still allowing adequate estimation of resources and reserves.
Fast Plane-Wave Reverse Time Migration
Authors: Wang Xiongwen , Ji Xu , Liu Hongwei , Luo Yi 
Published: February 2017

Abstract
Plane-wave RTM could provide quick subsurface images by migrating fewer number of plane-wave responses than the number of shot gathers. However, the long delaying time, which is the ignition time difference between the first and last shots, hinders the practical utilization of plane-wave RTM. In one-way wave equation migration, the long delay-time problem is solved easily by phase shifting in frequency domain. However, in RTM, we can only use imaging condition of time domain since wave modeling is usually accomplished by finite difference method in time domain. In this paper, we proposed a novel method to overcome this long delay-time problem of plane-wave RTM algorithm by wrapping plane-wave source function and its corresponding responses periodically, which makes them periodic. According to the linearity of wave equation, the periodic source function and its responses will, respectively, generate periodic source wave field and receiver wave field. Then we use zero-lag cross correlation of the periodic source wave field and receiver wave field as the imaging condition of RTM algorithm to obtain the migration result. Since the source wave field and receiver wave field are both periodic, the imaging condition of time domain gives the same result as that obtained from imaging condition of frequency domain. The key idea of this proposed method can be captured as periodic plane-wave RTM, which extends the source wave fields and receiver wave fields periodically and uses the cross correlation of periodic wave fields to replace the imaging condition of frequency domain. The computation cost for a plane-wave RTM is no more than two times compared to a shot profile RTM, so we name the new method as Fast Plane-wave RTM (FP-RTM). In some application, the number of plane waves to be migrated could be dramatically less than the number of shots and FP-RTM can help us to save significant computational costs. Therefore, FP-RTM can be applied in practice for any-angle of plane waves in any size of velocity models. In addition, FP-RTM provides us plane-wave domain CIGs (PD-CIGs) without any extra computation cost, which makes FP-RTM a practical velocity model building tools. Numerical examples on both synthetic and field data validate the efficiency and correctness of the proposed PP-RTM method.
Uncertainty Assessment in Production Forecast with an Optimal Artificial Neural Network
Authors: Guérillot D. R. , Bruyelle J. 
Published: February 2017

Abstract
Decisions for field development of oil and gas reservoirs are often based on uncertainties assessment on forecast productions and other variables which are highly impacted by the uncertainties on the reservoir characteristics. Using geostatistical models, it would require thousands of flow simulations of several hours each to consider the geological uncertainties. Each of these simulations would require several hours even with current high power computers. To bypass this restriction due to the computation time, one approach consists to replace the simulator by an approximation of it, also called proxy. This paper focuses on the use of Artificial Neural Networks (ANN) proposing an innovative method to build an optimal ANN.
Reservoir Fluids Saturation Diagnostic and Hydrocarbon Targets Identification Workflow
Authors: Faqehy M. , Katamish H. , Al-Towijri A. , Al-Ismael M. 
Published: February 2017

Abstract
Though there are various methods to assess reservoir performance, historical methods seem to focus the assessment on a single or couple of parameters. These include traditional methods to evaluate the reservoir sweep through average oil saturation-thickness maps, remaining oil volume maps, etc. Optimum reservoir management is a challenging and time consuming process since it usually involves analyzing many reservoir properties such as porosity, permeability, thickness, hydrocarbon saturation, fluid properties, relative permeability, net-to-gross ratio and pressures. In this work, we incorporate all these parameters into an automated workflow for reservoir diagnostics; and identification and ranking of optimum hydrocarbon (HC) targets.
The proposed workflow extracts static and dynamic information from reservoir simulation outputs and performs additional post-processing calculations on each grid cell for all time steps. The methodology involves classification of the reservoir simulation grid cells based on fluid saturation, relative permeability, pressure changes and displacing phase fluxes. After that, Produced, Mobile and Immobile oil volumes are calculated for each cell. These volumes are then grouped into six categories, namely, Produced, Highly Contacted, Moderately Contacted, Minimally Contacted, Uncontacted and Immobile Oil. In addition, the workflow incorporates different indicators for determining grid cell quality. These indicators are Reservoir Opportunity Index (ROI) and Simulation Opportunity Index (SOI); and we proposed a new reservoir quality indicator that incorporate changes in pressure over time. Finally, the workflow identifies connected cells with high quality indices and ranks these regions based on size and/or grid cell quality as potential targets for infill drilling.
The presented automated workflow is introduced as an integral part of well placement optimization workflow. It has been tested on several simulation models and successfully identified and ranked un-swept reservoir regions which proved through dynamic simulations to be credible future drilling targets.
CFD Simulation of Pressure Losses in Eccentric Horizontal Wells
Authors: Rushd S. , Shazed A. R. , Faiz T. , Kelessidis V. , Hassan I. G. , Rahman A. 
Published: February 2017

Abstract
In the oil and gas industry, various methods involving Computation Fluid Dynamics (CFD) are used to predict pressure losses while cleaning/operating horizontal drilling facilities with non-Newtonian fluids. Studies on the factors which influence such predictions are important to the successful design, development and operation of wellbores. The effects of hydrodynamic roughness along with eccentricity and rotational speed of a drill pipe are evaluated in the present study. Simulations are conducted using the commercial CFD code, ANSYS CFX 16.2 and the results are validated using experimental data. The current research shows that the pressure losses are strongly dependent on the equivalent roughness of a drilling annulus and, eccentricity and rotational speed of the drill pipe. The knowledge gained from this project is beneficial for designing, operating and troubleshooting drilling facilities.