bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced Petrophysical Evaluation in Complex Lithology Using Advanced Analysis of Cuttings Data: A Case Study from Saudi Arabia
Authors: Hashem Mohamed M. , AlGhamdi Tariq M. , Ibrahim Azizi M , Zeriek Rachad , Taher Ahmed 
Published: July 2016

Abstract
Advanced analysis of cuttings (ACA) provides qualitative measurements of the gamma ray spectrum and allows for quantifying of mineral elements for each sample in mud logging. The advancement in technology permits the ACA measurements to be conducted in near real time, which enables integration with the conventional log measurements for the purpose of constructing robust, multi-mineral petrophysical model. The result of the data integration prevails in the petrophysical mineral model.
The ability to acquire samples at a higher sampling rate, proper sample treatment and oxides correction, had improved the quality of data acquired from ACA when compared to the initial trials. ACA sample resolution had been improved immensely when compared to the first trial, because it reached the level where it can resolve the layering of the reservoir in the targeted formations. LWD measurements are essential in real-time petrophysical evaluation but slim neutron spectroscopy (NS) tool is not available, and only some contractors have slim spectral gamma ray (SGR). ACA was used to complement the previously mentioned deficiency in LWD technology. A reliable carbonate multi-min petrophysical model was successfully built and implemented in near real time evaluation using ACA and LWD data integration. In addition, the ACA has the advantage of acquiring the SGR and NS in high temperature (&gt;320°F) slim (&lt;4 inches) hole. As a result, the combination of ACA and wireline logs were used to evaluate a deep reservoir. The ACA is more cost effective when compared to similar measurements from conventional logs.
This paper discusses the ACA and its integration with conventional log data for petrophysical interpretation of the carbonates and clastics formations, respectively. The availability of SGR and NS are very important in complex lithology evaluation. This case study shows that advanced mudlogging data integrated with standard logging measurements, assisted in building enhanced petrophysical model, where the SGR and NS logging measurements were absent.
Operating a Sampling While Drilling Tool in Low Permeability Carbonates and Lessons Learned on Hydrocarbon Breakthrough
Authors: Abdelkader Ramy , Berkane Mustapha , Deering James R. , Ceyhan Adil G. 
Published: July 2016

Abstract
It is more effective to capture clean reservoir fluids as early as possible during drilling operations, and with the realization of formation-sampling-while-drilling (FSWD), this goal is fast becoming a reality. This paper summarizes one example from Saudi Aramco and shows the benefits of this evaluation procedure.
Our experience in sampling oil bearing formations drilled with water-based mud, has seen that the data from these instruments, which are now able to withstand the rigors of the drilling environment, can be used in real-time to control the sampling process, capture high quality samples, and also place the well where required. In this case study, a tight carbonate reservoir was the objective with the oil column being near saturation pressure. Under these circumstances, the challenges presented to us while sampling, included maintaining low flow rates and potential three-phase conditions, due to unavoidable drawdown while minimizing the time on the wall.
During sampling, pump efficiency was consistent with low-mobility formations, even with the various multiphase flow regimes encountered. Hydrocarbon breakthrough was significantly faster than historical wireline sampling performed in the same reservoir. FSWD greatly improves our costs by saving rig time. Also, FSWD was utilized to evaluate low-resistivity-pay zones and observe if they hold a movable water fraction. We see this as crucial for geosteering wells to prevent drilling through the zones with movable water, which will enhance the productivity index of the wells.
As a first time experience of FSWD in tight zones, a valuable lesson came to light where additional real-time monitoring improvements can be made, including the need to improve real time data quality, to accurately determine clean-up fractions while sampling. Based on this experience, we have formulated operational guidelines for improving real-time data analysis and determining the most opportune time to sample during the drilling process.
Acoustics Deep Shear Wave Imaging DSWI Analysis in Fractured Carbonate Reservoirs
Authors: Zeghlache Mohamed Larbi , Silva Andre , Gouda Mohamed , Zaid Ahmed Abou 
Published: July 2016

Abstract
Carbonate reservoirs evaluation is challenging from different aspects related to stratigraphic and structural features heterogeneities. One of the major challenges is fractures evaluation in terms of fractures nature, intensity, aperture and extension. Near and far field evaluation techniques had been utilized to achieve advanced fractures evaluation and modeling. This later is a key factor for a successful carbonate reservoir development.
Resistivity images and cores help in the quantitative analysis of near wellbore fractures intensity and aperture; high resolution seismic data can help to evaluate major structural features at a bigger scale. It is essential to bridge the gap between the borehole and field scale to further enhance evaluation of these fractures.
Using acquired sonic log and special processing; deep shear wave imaging (DSWI) uses cross-dipole shear wave components to "image" reflectors up to 70 ft (radius of investigation) away from the borehole, whether intersecting the borehole or not. This radial distance coverage can be even further away depending on many parameters.
The combination of resistivity imaging and acoustics deep shear wave imaging techniques is a great value added to fractured carbonate evaluation; this paper discusses a case study and lessons learned in a challenging evaluation well where both techniques were deployed to validate this process and enhance petrophysical and reservoir characterization models.
Future work will involve integration between results of acoustics deep shear wave imaging technique and both borehole seismic and surface seismic data to enhance the fracture model; and ultimately optimize well placement as well as reservoir performance.
Impact of Chemical Flood Implementation Time on Ultimate Recovery and Net Present Value
Authors: AlGeer Mohammed A. , Alshehri Amar J. , AlKhatib Ali M. 
Published: July 2016

Abstract
During waterflooding processes, injected water disconnects oil droplets as it flows through pores/throats in the reservoir. These disconnections are a consequence of capillary effects hindering the mobilization of oil through pores/throats of the reservoir. Thus, mobilizing the remaining oil in place by any enhanced oil recovery (EOR) process becomes very challenging.
Chemical flooding has been identified as an effective EOR method, which is usually implemented in tertiary mode, where field development has reached a mature level. At this stage, the efficiency of waterflooding, in terms of mobilizing remaining oil, declines due to capillary trapping. Chemical EOR (CEOR) methods such as polymer-surfactant flooding are used to reduce this trapping and mobilize the remaining oil.
Although most EOR processes have been implemented in tertiary mode, earlier implementation is more desirable, because capillary trapping is less prominent. This study investigates the impact of post-waterflood implementation time of surfactant-polymer flooding on ultimate recovery and net present value (NPV), given this capillary trapping. A series of numerical experiments was conducted to test this effect while accounting for operating expenses associated with both flooding options. Capillary pressure curves for the waterflood case and the chemical flood case were added to incorporate capillary trapping effects. Then the chemical-flood implementation time was varied to evaluate its impact on the ultimate oil recovery. These experiments were performed on two stylized reservoir models PUNQ-S3 and SPE10M reservoir models.
Given our assumptions, the ultimate recovery did not significantly change with varying the CEOR implementation time. There is, however, an optimum implementation time for CEOR at which NPV is maximized. The optimum implementation time becomes sooner as the geologic model is more heterogeneous.
A Roadmap to Successfully Select a Proper Gel Treatment Technology
Authors: Aldhaheri Munqith N. , Wei Mingzhen , Bai Baojun , Alsaba Mortadha 
Published: July 2016

Abstract
Polymer gels have been effectively applied to extend the productive life of mature oilfields by mitigating water production and enabling the recovery of bypassed oil reserves. A key component for a successful conformance improvement treatment is the identification of the most appropriate gel technology for a targeted reservoir. Gel projects are capital sensitive and involve high degree of risk; therefore, it is crucial to select a proper gel technology and provide an optimized design project.
This paper presents the first generalized comprehensive selection system for injection well gel technologies based on the comparative analyses of the characteristics of conformance problems in gel field projects. 111 field trials of three in-situ gel systems including bulk gels, colloidal dispersion gels, and weak gels were summarized from 1978 to 2015. First, reservoir/fluids characteristics, diagnosis indicators used in the evaluation of drive-fluid channeling strength, and treatment operational parameters were summarized. Then, problem zone volumes were estimated using a design rule of thumb and the problem development status was indicated using some production-related parameters. Finally, all characteristics of conformance problems were compared for different gel systems to identify factors implicitly used in the nomination of gel technologies in the field projects.
We recognized that gel selection process starts by matching characteristics of conformance problems with technical specifications and mechanisms of the gel systems. Then, the initial candidate technology is confirmed by screening criteria to ensure gel system compatibilities with reservoir and injected fluids. We identified that the most influential characteristics in the selection process are drive-fluid channeling strength, volume of problem zone, problem development status, existence of cross-flow, and the nature of the required solution whether it depends on gel strength or volume. It was recognized that the existence of crossflow or high oil saturation in the offending zones turns a limited conformance problem into a large volume issue that needs the application of the flood-size treating technologies. For these situations, current oil saturation in the problem zones is the key factor rather than oil saturation in the less conductive zones because it is guaranteed by the high reservoir permeability heterogeneities. In addition, the problem development status does not only affect the selection of a gel system, but also its design parameters such as polymer concentration. The novelty of the new gel selection system is in its utilization of standardized general parameters and provision of distinct parameter cut-offs for each gel technology.
Automatic Calibration of Uncertainty Estimates Using Anchoring Heuristics
Authors: Dossary Mubarak 
Published: July 2016

Abstract
The difficulty of assessing uncertainty has been well-documented by many authors (Capen 1976, Begg, Bratvold et al. 2003, Bickel and Bratvold 2007). Part of this difficulty is attributed to the biases that affect estimation and decision-making. This has also been documented in the literature (Tversky and Kahneman 1974, Welsh, Bratvold et al. 2005, Welsh, Begg et al. 2007, Virine 2008). The best solution to resolving those biases is the calibration of the uncertainty estimates (Capen 1976, McVay, Lee et al. 2005).
Calibration is incorporating past experiences in the new estimation process by applying correction factors to the raw estimates, based on the reliability of past estimates, to give calibrated estimates. This cannot be done instantly because it requires tracking past probabilistic predictions and comparing them to actual outcomes. Such information is not usually available because it requires project management discipline, corporate knowledge management, and appreciation for the value of quantifying uncertainty.
The objective of this paper is to demonstrate an automatic calibration method that can be readily applied for any uncertainty estimation without requiring past information about the reliability of previous estimates. This method combines two components: anchoring heuristics as demonstrated by Tversky and Kahneman, and the graphical demonstration by Capen (1976). The results of this study show that any general estimate of an uncertain parameter (e.g. Porosity, Permeability) can be calibrated by doubling the range while anchoring in the central tendency of the estimates. The process was applied to survey results a la Capen (1976) and showed an increased confidence in the estimate from 34% to 72%.
Determination the Rheological Properties of Invert Emulsion Based Mud on Real Time Using Artificial Neural Network
Authors: Elkatatny S. M. 
Published: July 2016

Abstract
Drilling fluid rheology properties play a critical role in the drilling operations. These properties such as, plastic viscosity, yield point, apparent viscosity, flow behavior and flow consistency should be monitored during the drilling operation. In normal operation, these properties are measure twice a day, while the mud density, Marsh funnel viscosity, and solid content, which are measured every 10 to 20 minutes. Previous models were introduced only to predict the apparent viscosity of the drilling fluid from the Marsh funnel viscosity with large errors.
The objective of this research is to introduce a new model to predict the drilling fluid rheological properties from the Marsh funnel viscosity, solid content, and density measurements in real time. A developed mathematical model was obtained from the weights, biases, and the transfer functions used in the Artificial Neural Networks (ANNs). The ANNs black box was converted to white box to obtain a visible mathematical model that can be used to predict the drilling fluid rheological properties only using Marsh funnel viscosity, solid content, and density.
Field measurement for 9000 drilling fluid samples were used for model training and testing, the viscometer readings at 300 and 600 rpm were predicted using the visible mathematical model from the ANNs. The rheological parameters such as yield point, plastic viscosity, apparent viscosity, and consistency index were determined from the viscometer readings at 300 and 600 rpm. The predicted rheological parameters were compared with the measured ones from the field and the match was very good. The average absolute error for the various parameters ranges from 1 to maximum 5 compared to 60 if we used the previously developed correlations. The developed model is a robust technique and tool that can be used to predict the real time drilling fluid rheological parameters that are essential for the drilling hydraulics design and also to predict the performance of drilling fluid.
Real-Time Well Integrity Diagnostics Using the Latest Developments in Visual Logging Technology; a Case Study.
Authors: Al-Hajri Nasser M. , Al-Ajmi Mohammed D. , Al-Subaie Fehead M. , Hognestad Andre , Johannessen Erik 
Published: July 2016

Abstract
This paper will present a case study that illustrates wide-ranging capabilities of the latest improvements to visual logging technology. The well studied was identified as having a wellbore obstruction during a routine wireline survey. Conventional well accessibility diagnostics were run that include multi-size drifting tools and lead impression blocks. This assessment was inconclusive, which was attributed to wellbore geometry (deviation). A downhole bailer sample was taken at the wellbore obstruction depth. Extensive composition identification laboratory analysis was conducted on the sample. Physical examination of the sample using magnet attraction and acid solubility was performed along with a solvent extraction test to identify hydrocarbon content in the sample. Additionally, the sample crystalline structure was identified using X-ray diffraction and X-ray fluorescence to determine elemental composition. Laboratory analysis has indicated that the sample is mainly iron sulfides containing iron oxide and calcium carbonate as minor components.
In light of the above findings, two possible sources of the downhole obstruction were conceived: Severe casing collapse induced by galvanic corrosion.Scale funneling along the casing wall due to high iron and sulfate contents in the injected water leading to iron sulfide precipitation.
To ascertain the source of obstruction, the latest visual logging technology was deployed in this well. This technology provides extreme wide-angel (185/360°) images along the entire wellbore length through its lens and image capturing design. An advanced operating system inside the tool adds flexibility for image enhancements and real-time data transmission. Specially designed software was used to view the recorded data and align images with time, depth, and tags for log interpretation. The software uses advanced image logarithms to add pan, tilt, and zoom capabilities during live inspection and views of stored images. Visual logging has revealed scale build-up inside the wellbore and ruled out casing collapse.
Improved Fluid Efficiency for High-Temperature Viscoelastic Surfactant Based Stimulation Fluids Using Synergistic Effects of Nanoparticles
Authors: Sangaru Shiv Shankar , Yadav Prahlad Kumar , Huang Tianping , Al-Rabah Mohammed , Sarmah Pranjal 
Published: July 2016

Abstract
A viscoelastic surfactant (VES) based fluid has been proven to be a cleaner alternative to the conventional polymer based fluid. However, there are still certain technical challenges that need to be overcome to make it as a viable alternative. High fluid loss observed with VES fluids is one such issue that is investigated in this paper. It is known that certain nanoparticles can improve the rheology and fluid loss efficiency of VES fluid when added individually. Lab experiment results demonstrate that in certain conditions adding two different nanoparticles can act synergistically to improve the fluid efficiency more than when adding only one of the nanoparticles.
Reservoir Simulation Assisted History Matching: From Theory to Design
Authors: Shams M. 
Published: July 2016

Abstract
Petroleum reservoirs are geologically large and complex. In order to technically and economically optimize the exploitation of these hydrocarbon reserves, multimillion dollar investments, reliable numerical reservoir simulation models should be constructed to predict the reservoir performance and response under different production scenarios. Reservoir numerical simulation models can be only trusted after good calibration with actual historical data. The model is considered to be calibrated if it is able to reproduce the historical data of the reservoir it represents. This calibration process is called history matching, and this is the most time consuming phase in any numerical reservoir simulation study. Traditional history matching is carried out through a trial and error approach of adjusting model parameters until a satisfactory match is obtained. The biggest challenge that faces the simulation engineer during this critical phase is that, several combinations of reservoir history matching parameters might be satisfactorily matching the past dynamic behavior of the system which makes the process ill-posed due to the non-uniqueness solution issues. Traditional history matching is accordingly a time-consuming, expensive, and often frustrating procedure and as a consequence, the assisted history matching technique has been arisen.
In assisted history matching technique, the simulated data is compared to the historical data by means of a misfit function, objective function. The history matching problem is translated into an optimization problem in which the misfit function is an objective function bounded by the model constraints. The objective function is minimized using appropriate optimization algorithm and thus the results are the model parameters that best approximate the fluid rates and pressure data recorded during the reservoir life.
The objectives of this paper are to clarify the idea behind assisted history matching process and discuss its different aspects, experimental design, proxy models, and optimization algorithms, and show how these aspects are integrated to overcome the frustrating nature of the history matching problem. Finally, guide lines are provided to enhance the design of the assisted history matching process.
Model-Assisted Examination of Disposal Systems Capacity Based on Injected Water Quality
Authors: Al-Ajmi Mohammed D. , Al-Hajri Nasser M. , Al-Subaie Fehead M. 
Published: July 2016

Abstract
The sustainable operation of disposal systems that are part of wet crude handling facilities, is essential to ensure uninterrupted oil production from such plants. This paper will present the results of hydraulic simulation modeling of the capacity of a wastewater disposal system through an examination of the quality parameters for injected water. Applicable formation damage characterization methods, such as pressure transient analysis and continuous flow measurements, were utilized in this study to build representative models for each disposal well connected to System-A. The models were calibrated in a manner that couples surface and subsurface flow from the disposal pump all the way to the reservoir.
Water quality monitoring of disposed water was conducted by measuring the oil in water content. These data were, then, history matched with respective well injection performance to identify potential sources of well injection impairment.
An all-inclusive analysis, utilizing hydraulic simulation techniques, was performed to model the current injection performance and forecast the future reliability of a System-A disposal network, taking into account the impact of water quality and reservoir pressure variations. The collective inputs from laboratory analysis along with hydraulic simulation aided in formulating several key findings and recommendations with regard to setting appropriate limits of water quality control parameters.