bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing Value Through Reducing Differences Between LWD and Wireline Depths
Authors: Bolt Harald 
Published: September 2019

Abstract
Along-hole depth is the most fundamental subsurface measurement made in our business. Driller's depth, the basis of logging while drilling (LWD) data registration, and wireline logged depth are the primary sources of along-hole depth data. These are rarely congruent. This paper sets out a methodology that can be applied to both wireline and drill pipe along-hole depth measurement (Driller's Way-point Depth, DwpD) and provides an uncertainty calculation that results in True Along-hole (TAH) depth. The result is a reduction in differences between drill pipe and wireline depth measurements, increasing confidence in along-hole depth measurements and increasing well data value. A field data set is reviewed that showed up the similarities and the differences between DwpD and the wireline corrections.
In-Situ Stresses in Colorado Group, AB, Calculated from Open-Hole Mini-Fracs and FMI Logs
Authors: Costin Simona , Smith Richard , Yuan Yanguang , Andjelkovic Dragan , Garcia Rosas Gabriel 
Published: September 2019

Abstract
Open-hole mini-frac tests are seldom performed in the Athabasca and Cold Lake oil sands due to the complexity of operations. In this paper we present the results of open-hole injections tests performed in Cold Lake, Alberta (AB), Canada. The objective of the injection tests was to assess the in-situ stress condition in the Cretaceous Colorado Group. The injection tests results combined with the run of formation image logs (FMI) before and after the injection have enabled not only the determination of the in-situ minimum stress in the rock, but also the full 3-D stress tensor, along with the orientation and inclination of the hydraulic fracture.
The tests were performed in IOL 102/08-02-066-03W4 (N10 Passive Seimic Well, ‘PSW’). The injection tests have revealed that the vertical stress in the area is the in-situ minimum stress, consistent with previous measurements. The hydraulically-induced fracture has sub-horizontal to moderate dip angle, mostly owing to the pre-existing fabric of the rock, and peaks in the general NE-SW direction. Numerical modeling of the in-situ stresses has shown that the values of the vertical and the minimum horizontal stresses are close, with the vertical stress consistently being smaller than the minimum horizontal stress in all tested zones.
Downhole Fluid Characterization with Validated Mapping from Optical Sensor Measurements
Authors: Chen Dingding , Jones Christopher , Dai Bin , VanZuilekom Anthony 
Published: September 2019

Abstract
Robust downhole fluid analysis highly relies on quality measurements and data mapping from various optical sensors implemented into modern formation testers. The direct modeling used to determine a multivariate correlation between optical sensor responses and diverse fluid compositions or properties is often cost-prohibitive with sensor-based calibration. This paper presents a novel method based on concatenated optical computing neural networks (COCN), which link sensor-specific signal transformation to generic fluid characterization through validated data mapping.
The COCN models are built separately in the in-house laboratory using optical data transformation networks and multi-analyte fluid characterization networks. To evaluate the uncertainty of sensor signal mapping, additional sensor data prediction networks, which exchange inputs and outputs of sensor data transformation networks to provide reverse data mapping, can be built to produce the simulated sensor responses. The actual sensor measurements are then compared to the simulated sensor responses to validate the optical signal transformation. The degree of matching can be used to identify issues associated with the quality of the sensor measurements and the range of calibration and testing data, and to select the transformation networks in ruggedizing predictions of fluid compositions and properties.
This paper presents the method used and case studies to exemplify the application of the proposed approach for reliable fluid sample characterization using laboratory and field measurement data. Calibrating sensor-independent fluid predictive networks on a large database usually pertains to low uncertainty because the analyzed measurements can be collected from diverse reservoir fluid samples. The construction of data transformation networks, however, is only realistic by using a small number of reference fluids because of their high calibration cost, which conversely challenges the quality of data mapping with new field sensor measurements. In this study, sensor data transformation networks and sensor data prediction networks form two groups of mutually complementing models that can validate one another, making the quality of data mapping observable before applying fluid characterization models. The results of the case studies demonstrate that the consistency between the actual and simulated sensor responses is a reasonable performance index in the prediction of fluid compositions and properties. The laboratory and field examples also justified the importance of using simulation data appropriately to overcome the limitation of sensor measurement data in the calibration of transformation networks.
Acoustic and Nuclear Wireline Logging Validation of Shape Memory Polymer Screen Expansion
Authors: Flores Juan Carlos , Patterson Douglas John , Wakefield John , Chace David , Malbrel Christophe 
Published: September 2019

Abstract
A new shape memory polymer (SMP) sandface completion is entering the market as an alternative to gravel packs. The SMP activation has been well established in the laboratory and successful field deployments has been reported. To confirm the SMP material is fully expanded and to enable long term stability assessment, a practical in-situ evaluation method is needed. Three acoustic and two nuclear services are evaluated for their ability to detect SMP expansion in a simulated formation.
A downhole equivalent in-situ test environment was built for purpose with a section of limestone blocks drilled to 8.5 in. gauge hole and a joint of unexpanded SMP screen placed within. Two cased-hole CBL services evaluated ultrasonic guided mode attenuation response in the base perforated pipe. These modes consisting of two lamb modes, the compressional (S0) and the asymmetric (A0 flexural), along with the shear horizontal (SH) mode. Additionally, a multipole acoustic tool was utilized to analyze the response of both the refracted modes, compressional and shear, and the guided modes, casing tube and flexural waves. Nuclear services employed pulsed neutron and compensated neutron techniques. The SMP was then activated and a second pass logged for each technique. The limestone was removed from the SMP to visually verify expansion. The logs before and after expansion are compared.
In conclusion, several measurements provided good indication of the SMP expansion. The ultrasonic guided mode analysis demonstrated attenuation response increases, with the largest change observed for the A0 mode when compared to the S0 compressional response. Of the lower frequency multipole acoustic methods, the guided casing tube wave demonstrated the greatest response, even greater than the ultrasonic, particularly in the low frequency range below 3 kHz. Generally, excitation modes with particle motion parallel with the base pipe were found to attenuate least while those with normal components displayed the largest change. This is likely due to compression of the base pipe and metal screen layers because the SMP begins to exert force in all directions when it reaches gauge hole, which is short of full expansion as designed.
The pulsed neutron (PN) logs provided a qualitative, yet clear verification of expansion when comparing measurements sensitive to hydrogen concentration. The SMP is an extremely low density organic molecule with hydrogen concentration less than that of water. Comparing before and after PN logs indicates that a change in the hydrogen concentration occurred as a result of SMP expansion. Compensated neutron did not show sensitivity to expansion of the polymer.
This is the industry’s first logging validation of shape memory polymer activation in the annulus of a simulated downhole environment. Prior attempts with a variety of logging services and a simpler test environment were inconclusive.
A Mechanistic Approach for Calculating Oil-Gas Relative Permeability Curves in Unconventional Reservoirs
Authors: Czernia Bartosz , Barrufet Maria 
Published: September 2019

Abstract
A mechanistic approach for calculation of oil-gas capillary pressure curves and relative permeabilities in unconventional reservoirs is presented. The approach accounts for reservoir fluid composition, contact angle wettability and pore size distribution of each specific reservoir and generates a unique set of relative permeability curves based on those inputs. This allows calculation of curves in reservoirs where historical production data is limited.
Phase behavior calculations are computed by coupling the Peng-Robinson equation of state and the Young-Laplace capillary pressure model. This coupling allows for inclusion of the effect of confinement of reservoir fluids on volumetric and transport properties.
The reservoir is modeled as a bundle of tubes with diameters representative of the pore size distribution found in the reservoir. A multi-step depletion is modeled followed by gas injection and a secondary depletion. Separate capillary pressure results are obtained for each part of the process. After the capillary pressure curves are generated, an integration is performed on the capillary results to generate a set of relative permeability curves following the Nakornthap and Evans method (1986).
The multi-step process is used to allow recalculation of the relative permeability curves as the reservoir fluid composition changes due to the initial depletion and then secondary gas injection.The approach yields a unique set of relative permeability results for each set of input parameters.The mechanistic approach is demonstrated on two different oil compositions, a black oil sample and a volatile oil. For each of the oil compositions, two different injection gasses are evaluated (methane and carbon dioxide). The intermediate calculations are summarized and the final permeability results are included in the paper. The results show that for both oil samples evaluated, the gas injection results in an increase in oil relative permeability. Carbon dioxide is more effective at increasing the oil relative permeability than methane for both oil samples. This suggests that carbon dioxide could be an effective option for enhanced oil recovery operations in unconventional reservoirs.
A unique element of the approach presented is that the calculation of relative permeability curves for the initial reservoir depletion is immediately followed by the calculation of new relative permeability curves as the reservoir composition changes due to gas injection. This allows prediction of relative permeability results in an unconventional reservoir for both the initial reservoir depletion and also for hypothetical enhanced oil recovery operations. Since the model can be run quickly and repeatedly, sensitivity analyses can be performed on the permeability curves as a function of initial reservoir conditions and injection gas compositions and amounts.
Fluid Sampling in Tight Unconventionals
Authors: Carlsen Mathias Lia , Whitson Curtis Hays , Alavian Ahmad , Martinsen Sissel Øksnevad , Mydland Stian , Singh Kameshwar , Younus Bilal , Yusra Ilina 
Published: September 2019

Abstract
In this paper we emphasize the duality of fluid sampling: (1) fluid characterization; to collect samples and measure pressure/volume/temperature (PVT) data that can be used to build and tune an equation of state (EOS) model, and (2) fluid initialization; to collect samples to estimate in-situ fluid compositions. It is hard, if not impossible, to obtain truly in-situ representative fluid samples in multi-fractured horizontal wells (MFHW). This paper explains why fluids measured in the lab may be significantly different from in-situ representative fluid samples, even if the fluid samples are collected shortly after the well is put online. The paper also suggests that practically all samples, in-situ representative or not, can and should be used to build a reliable EOS model.
To make a comprehensive assessment of fluid sampling in tight unconventionals, reservoir fluids ranging from black oils to gas condensates have been studied. For a wide range of fluid systems, a compositional reservoir simulator has been used to assess two main scenarios: (1) an initially undersaturated (single-phase) fluid system, and (2) initially saturated (two-phase) fluid system. To quantify how collected surface samples change with time, three properties are studied as functions of time: (1) saturation pressure and type (dewpoint | bubblepoint), (2) producing gas/oil ratio (GOR), and (3) stock-tank oil (STO) API. Observations of how these three properties change with time is used to help explain why elevated saturation pressures, greater than the initial reservoir pressure, often can be observed.
Rapid decline of the flowing bottomhole pressure (BHP | pwf), together with shut-in periods, makes it difficult to obtain in-situ representative samples in MFHW. For slightly undersaturated reservoirs, and saturated reservoirs, it may be impossible to obtain in-situ representative fluid samples because of the near-wellbore multiphase behavior. However, samples which are not in-situ representative can still be used to estimate original in-situ fluids using equilibrium contact mixing (ECM) procedures. In this paper, we propose two ECM methods that can either be carried out by physical measurements in a PVT lab or can be computed with a properly tuned EOS model.
Eliminating Guesswork in Downhole Diagnostics with Definitive Answers from Downhole X-ray Technology
Authors: Hamid Saad , Almulhim Abdulrahman A. , Achihai Radu , Spannuth Melissa 
Published: September 2019

Abstract
When a restriction or non-conformity presents itself in a well, quickly and reliably diagnosing the nature of the anomaly can save diagnostic runs and help prevent similar cases elsewhere, reducing nonproductive time and operating costs. Downhole X-ray diagnostics provide this understanding quickly and reliably under diverse well conditions that limit the effectiveness of other downhole diagnostic techniques. X-ray diagnostics produce real-time, quantitative two-dimensional images and three-dimensional reconstructions of downhole objects and obstructions with high precision. We demonstrate this with a case study in which X-ray diagnostics accurately identified and quantitatively characterized an obstruction due to liner deformation.
Artificial Intelligent Logs for Formation Evaluation Using Case Studies in Gulf of Mexico and Trinidad & Tobago
Authors: Gan Thomas , Kumar Ashok , Ehiwario Michael , Zhang Barry , Sembroski Charles , de Jesus Orlando , Hoffmann Olivier , Metwally Yasser 
Published: September 2019

Abstract
Borehole-log data acquisition accounts for a significant proportion of exploration, appraisal and field development costs. As part of Shell technical competitive scoping, there is an ambition to increase formation evaluation value of information by leveraging drilling and mudlogging data, which traditionally often used in petrophysical or reservoir modelling workflow.
Often data acquisition and formation evaluation for the shallow hole sections (or overburden) are incomplete. Logging-while-drilling (LWD) and/or wireline log data coverage is restricted to mostly GR, RES and mud log information and the quality of the logs varied depending on the vendor companies or year of the acquisition. In addition, reservoir characterization logs typically covered only the final few thousand feet of the wellbore thus preventing a full quantitative petrophysical, geomechanical, geological correlation and geophysical modelling, which caused limited understanding of overburden sections in the drilled locations and geohazards risls assessment.
Use of neural networks (NN) to predict logs is a well-known in Petrophysic discipline and has often used technology since more than last 10 years. However, the NN model seldon utilized the drilling and mudlogging data (due to lack of calibration and inconsistency) and up until now the industry usually used to predict a synthetic log or fill gaps in a log. With the collaboration between Shell and Quantico, the project team develops a plug-in based on a novel artificial intelligence (AI) logs workflow using neural-network to generate synthetic/AI logs from offset wells logs data, drilling and mudlogging data. The AI logs workflow is trialled in Shell Trinidad & Tobago and Gulf of Mexicooffshore fields.
The results of this study indicate the neural network model provides data comparable to that from conventional logging tools over the study area. When comparing the resulting synthetic logs with measured logs, the range of variance is within the expected variance of repeat runs of a conventional logging tool. Cross plots of synthetic versus measured logs indicate a high density of points centralized about the one-to-one line, indicating a robust model with no systematic biases. The QLog approach provides several potential benefits. These include a common framework for producing DTC, DTS, NEU and RHOB logs in one pass from a standard set of drilling, LWD and survey parameters. Since this framework ties together drilling, formation evaluation and geophysical data, the artificial intelligence enhances and possibly enables other petrophysical/QI/rock property analysis that including seismic inversion, high resolution logs, log QC/editing, real-time LWD, drilling optimization and others.
Using Nanoparticles Coating to Enhance Proppant Functions to Achieve Sustainable Production
Authors: Tabatabaei Maryam , Dahi Taleghani Arash , Cai Yuzhe , Yang Santos Livio , Alem Nasim 
Published: September 2019

Abstract
Proppant bed plays a critical role in enhancing oil and gas production in stimulated wells. In the last two decades, there have been consistent efforts to improve shape characteristics and mechanical strength properties to guarantee high permeability in the resultant propped fracture. However tuning wettability of proppants have not yet engineered considerably maybe because natural sand has been a typical raw material for proppant manufacturing. However, water wet proppants may not only limit production due to reduced hydrocarbon relative permeability but also facilitate fine migration through the proppant bed. Fine migration and increasing water saturation may deteriorate oil production over time. Intrinsic hydrophobicity of graphitic surfaces and their two-dimensional geometries made them a promising candidate for coating proppant to alter its wettability. In this paper, we present a methodology for treating proppant surfaces with graphite nanoplatelets. Standard laboratory tests following modified API RP61 have conducted to show the effectiveness of the proposed methodology.
Method of Determining Unconventional Reservoir Saturation with NMR Logging
Authors: Ye Shin-Ju , Scribner Allison , McLendon Darren , Ijasan Olabode , Chen Songhua , Shao Wei , Balliet Ron 
Published: September 2019

Abstract
Nuclear magnetic resonance (NMR) T1-T2 logs from several west Texas wells over various formation layers were acquired to assess the values of NMR logging for fluid typing and saturation quantification in tight mudstone reservoirs. To quantify fluids in those low-porosity formations, high-density NMR data with adequate signal-to-noise ratio (SNR) are essential, and an inversion algorithm capable of resolving fluids on T1-T2 map is needed. These requirements are achieved with multifrequency data acquisition having a short interecho spacing (TE) for all frequencies, which yields a total of 15,400 echoes per depth in a single NMR pulse sequence cycle. This large data density enables less vertical averaging to be needed in both 1D and 2D processing, which is essential for capturing the porosity and fluid volume variation in these layered formations. The use of the inversion-forward modeling-inversion (IFMI) method improves the spectral resolution of the relaxation time distribution and T1-T2 map resolution because the method adequately addresses the effect of gradient differences in NMR responses in multifrequency data acquisition. 2D T1-T2 map fluid resolution of downhole stations and moving logs are compared to determine the minimal stacking required for fluid discrimination. The porosity and water volume are compared with those of conventional and mineralogy logs.
Successful Application of Homogenization Principle in ESPs: Case Study in South America
Authors: Gonzalez Gustavo , Guanacas Luis , Pinto Diego , Montufar Carlos 
Published: September 2019

Abstract
Sand management has become in one of the most vital factors in today's upstream oil and gas industry, more and more are the cases where the sand control systems play an important factor to determine the economic viability of each project. This paper will focus in a solution for sand problems in ESP systems applying to sand slug breakdown using a 10 V-Mesh Sand Screen to homogenize the solid inflow in the system so it would be easier to handle the solids through the ESP's stages. The implementation of the screen intake for the homogenization of solids in an ESP well allowed to efficiently manage sand slugs, improving the pump efficiency and avoiding blocking problems in the pump caused by sand. Furthermore, the system allows increasing the frequency of operation of the ESP motor to have a greater drawdown, increasing the production of the fluid from 1600 BFPD to 1800 BFPD. The behavior of the sensor data such as vibration, current, and voltage remained stable throughout the period evaluated, extending the run life of the system.
Unconventional Reservoirs Next Frontier: Efficient Production Modeling – Part 2
Authors: Ayoub Joseph , Krishnamurthy Shalini , Gao Sunhua , Jimenez Jose , Thambynayagam Michael 
Published: September 2019

Abstract
A novel analytical-numerical hybrid model introduced in SPE 1914441 is used to illustrate through example applications the benefit of having physics-based models that are practical for automation and integration with monitoring and control systems. The solution integrates the reservoir, completion and surface network, resulting in an efficient model that is readily accessible for daily production optimization. It makes a digital twin for every unconventional well affordable by extensive automation and efficient interface enabling management by exception. In this paper, additional example applications complementing those discussed in SPE 191444 are presented. They include optimization of well-hydraulic fractures positioning in multilayer environment and a quantitative discussion of co-linear versus transverse fracture designs and of the benefits of gas lift optimization. The aim is to illustrate the need/utility for a fast, integrated model that can be used to assist in optimizing the completion and that carry over to production enabling daily production optimization that is practical as opposed to solutions that are too onerous to deploy for every well throughout its lifecycle.