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Challenging aspects to heavy oil field development are the large volume of data which is collected, in particular from cored evaluation wells, and the difficulty in evaluating of the quality of such data. This paper outlines an approach to summarize coring data and procedures from two heavy oil fields in North Kuwait, and then to compare those summaries with similar heavy oil operations in other countries, in order assess their quality and degree of representativeness.For two North Kuwait heavy oil fields, data was tabulated for the cumulative amounts of core cut and recovered relative to their field areas. This data was then further analyzed to summarize recovery by rock type, and assess the quality and quantity of plug samples collected. Benchmarks were established by summarizing core data from similar heavy oil operations in other countries, and the North Kuwait heavy oil data was then compared with those benchmarks. In a similar manner, documented core handling procedures for North Kuwait Heavy Oil operations were compared with procedures from similar heavy oil operations in other countries.The benchmarks which were used to compare North Kuwait Heavy Oil data summaries with other countries include the following: 1) Coring Well Area Coverage Densities; 2) Coring Well Vertical Coverage of Cap Rock and Reservoir Intervals; 3) Core Plug Sample Rate and Survival Rate; and 4) Core Handling Procedures and Volume of Coring.For many of the benchmarks used, North Kuwait heavy oil operations compare favorably with similar operations from other countries. However areas of improvement were identified from these benchmarks in terms of areal core coverage, vertical core coverage, core plug rates and core handling procedures. It is expected that these improvements, when implemented, will lead to a more representative sampling of the areas and rock types (reservoir rocks, baffles and cap rocks) in North Kuwait. This in turn should lead to a better understanding of fluid volumetrics, reservoir characterization and subsequent life of field development. As well by applying a focused approach to future coring operations, a significant cost savings is expected relative to original evaluation well plans.A significant product from this study is a large summary database of all coring information for two North Kuwait heavy oil fields, which can be queried by area, rock type and sample type. This data base has been compared with similar operations in other countries using a series of benchmarks. Planned future coring and sampling operations have been modified through the use of this benchmarking tool.

Within North Kuwait heavy oil fields, integrated reservoir modelling is challenged by inherent reservoir heterogeneities, regional non-stationarity (i.e. trends), asymmetrical well and seismic distributions, and the need to maintain alignment between various the model scales required and multiple purposes for which the models will be used. This paper presents a number of customized workflows adapted to characterize these reservoir architectures and heterogeneities within one field, appropriately at all model scales and in regions with variable well control.A reliable new rock type classification scheme was derived from cross plot analyses of Gamma Ray and Bulk Density (GR-DENS) logs. Within an initial production area containing over 900 regularly spaced wells, 3D variograms for these lithotypes were estimated, calibrated with 3D seismic and reservoir equivalent surface outcrops. The lithotypes were distributed into full field static models using these variograms and the Sequential Indicator Simulation (SIS) algorithm. An additional declustering step was implemented to express regional trends and account for asymmetrical data distribution. Petrophysical property modeling (shale volume, effective porosity, water saturation) was performed using the Kriging algorithm conditioned to lithofacies.From these full field models, sector models were created to capture geological heterogeneity at a smaller grid increment. Full-field facies were downscaled onto the sector model grids, and then the Sequential Gaussian Simulation (SGS) algorithm was used to interpolate petrophysical properties, constrained by histograms of the kriged background models. This allowed information from wells outside of sector models to be incorporated efficiently into them.The facies and heterogeneities represented within the full-field static models have improved upon earlier versions, by being distributed more consistently relative to known seismic and well control, and to outcrop reservoir analogues. Modelled petrophysical properties also show a more consistent linkage with known values derived from core analyses. This consistent set of models can now be used with greater confidence, to answer questions ranging from in-place volume uncertainties to dynamic production forecasting, to life of field development. This has also led to reduced dynamic model run times, and improved reservoir management and operations optimization.In summary a robust series of full-field and sector models was developed and customized to a North Kuwait heavy-oil field, with information from data-rich areas being elegantly applied to reduce uncertainties in data-poor areas. These nested models can now be matched to the detail required for the model purpose. For example heterogeneities that matter-for-flow in dynamic simulation models can be represented explicitly, whereas for full-field volume estimations property averages can be used.

North Kuwait heavy oil development continues to benefit from detailed study of outcrops at the Jal Az-Zor escarpment that are stratigraphic equivalents to some of their reservoirs. During the 2018-19 field season, focus was placed on recording the internal architectures of specific stratigraphic layers, developing a deeper understanding of the diagenetic processes in the basin and relating these observations to the North Kuwait reservoirs. These are all key controls on reservoir quality and connectivity. Inter-well scale heterogeneities were identified for inclusion into subsurface models to predict steam/polymer conformance and oil production better.Building on work of the 2017-18 field season when the Jal Az-Zor sequence was logged, measured, described and interpreted; units were tracked and correlated laterally for around 3km. Internal architectures of prominent layers were mapped through conventional and drone mounted photographic surveys, and satellite images. X-Ray Diffraction and thin section studies of hand samples were analyzed, to understand mineralogical controls on porosity & permeability.Integrated field trips were conducted with members from subsurface, reservoir and well-engineering disciplines, to engender common perspectives on subsurface uncertainties and development risks. They also served to close the communications gap between disciplines.Interpreted high-resolution photographic data, sediment flow direction measurements and other observations gave clues to environments of deposition and their implications for lateral connectivity for each layer. Observations on vertical connectivity between and within layers were recorded. Geological heterogeneities were considered in the context of the typical inter-well separation spacing for their implications on injected steam or polymer conformance, & water-cut.Depositional models were compiled and interpreted with regard to their implications for reservoir plumbing, H2S risk, top-seal integrity, sand production etc. Additionally, increased awareness of the stratigraphic relationships between zones was utilized to resolve correlation ambiguities for closed spaced wells in a water injection pilot and led to the development of a screening tool to predict water-coning risk in wells and informed a similar study for injected steam-conformance risk mapping.Field analogues at Jal Az-Zor are key to defining and characterizing the key genetic flow units of the heavy-oil reservoirs in North Kuwait and it is rare to have closely linked field-outcrop analogues so readily accessible. They represent an important cost-effective resource for field development and operations as they bridge the scale gap between well-derived and seismic data as they provide insight to the nature of flow unit connectivity (i.e. the reservoir plumbing – heterogeneities that matter-for-flow) in way that other data types do not. Field analogue observations therefore directly inform the grid scale permeability estimates that are used in the dynamic simulator for production forecasting and field development and operations optimization.

This paper presents a method for facies classification derived from cross plots of basic gamma ray and bulk density wireline log data. It has been specifically developed in-house for two North Kuwait heavy-oil fields, and has been calibrated against both field analogues and core sample measurements. This new facies classification scheme has proven to be quick and cost effective, with multiple practical applications for future field development and operation optimization.For two heavy oil fields in North Kuwait basic Gamma Ray and Bulk Density (GR-DENS) curve data from over 1300 wells were cross-plotted. The resulting relationship characteristics were used to delineate eight separate facies, which plot along a continuum from clean porous sands with little cement and clay, to less porous sands with increasing clay and cementation content, to carbonate and shale. The properties for these facies were calibrated against data from core analyses and with outcrop analogues in North Kuwait. These facies were populated into static reservoir models using the Sequential Indicator Simulation (SIS) method, and petrophysical modeling was then conditioned to these facies. These resulting modeled facies, with their associated petrophysical properties, have been used in a wide variety of subsequent analytical studies.The eight facies which have been newly delineated by the GR-DENS classification scheme capture the transitional nature of petrophysical properties for oil saturation, porosity and permeability. This has enabled several improvements for heavy-oil field development including: 1) better delineation of reservoir and baffle zones; 2) better calibration of oil saturation with core data; 3) calibration of facies with 3D seismic amplitude response; 4) better understanding of reservoir geomechanics and seal integrity assessment; 5) greater confidence in the results of static and dynamic reservoir modeling; 6) more effective decision making in the WRFM process; and 7) alignment of the petrophysical and facies characterization approach between two separate heavy oil asset teams, which allows for direct comparisons between their data sets. Although more complex software exists for specialized facies classification, the GR-DENS workflow newly developed for North Kuwait heavy oil has proven to be simple, rapid, accurate and cost effective.In summary a robust facies classification scheme was developed in-house which is appropriately customized for two North Kuwait heavy oil fields. This methodology has enabled the creation of more representative reservoir models, with resulting improvements in understanding for multiple aspects of both fields. These improvements in turn will lead to better production forecasting and optimization as well as enhance future life of field planning.

Boron nitride nanotubes (BNNT) were functionalized under mild conditions, using a difunctional amine, such as glycine, with one of three targeting ligands, folic acid, a nerve growth factor, or an antibody against nerve growth factor. In addition, non-fouling BNNTs were obtained by a facile and versatile, non-destructive method via controlled surface-initiated grafting of polyzwitterions. The BNNTs were loaded with a fluorescent probe for convenient imaging of glioblastoma multiforme cells treated with BNNTs. BNNTs bearing targeting factors on their outer surface demonstrated an increased efficiency of internalization in glioblastoma multiforme cells, compared to non-modified BNNTs. The degree of internalization was affected both by the nature of the ligand/agonist linked to the BNNTs surface and by the presence of serum proteins. The polyzwitterion grafts prevented the spontaneous adsorption of serum proteins on the BNNTs.

A heavy oil field (Field X) in Northern Kuwait is in the early stages of development but it is clear from production pilots that tight units (baffles) of variable lithology, thickness and continuity, within the reservoir will play a key role in influencing steam conformance and recovery efficiency. The high well/core density of the field’s production startup area allows re-evaluation of baffles in light of cross-discipline integration of pilot production data, petrophysical data and detailed core review.A process was followed to update and calibrate all core descriptions against logs, follow a consistently picked set of petrophysically defined markers, compare visually defined lithofacies with log defined ones, and then map out key surfaces. The key next step is to define appropriate reservoir properties by facies/rock types, apply these to understanding pilot behaviour and predict steam conformance for Well, Reservoir and Facilities Management (WRFM) and the next phases of the wider field development planning. The field’s baffles play a role far beyond just understanding steam conformance, they are a first barrier for cap rock integrity and their presence/absence will also influence the path and rate of the aquifer influx.The petrophysical redefinition (Baffle Quality Index) of a "semi-stratigraphic" interval - which will stop or slow steam migration depending on its quality and lateral extent - has enabled efficient communication about the baffle, and allowed the wider team of petroleum engineers from a number of subsurface disciplines to focus on dynamic properties impacting recovery – steam conformance, aquifer influx, windows between isolated reservoir units – and then evolve the development strategy, effectively respond to WRFM issues, optimize observation and infill well placement and increase UR in a cost effective way.

When developing and operating oil and gas fields, a large number of engineering decisions need to be taken. These decisions range from the very high-level such as recovery mechanism, facility sizing or well count to more detailed decisions such as individual well placements, well design and completion strategies. Typically, subsurface models play a role in informing these decisions by testing their effect on forecasted production and it is generally held best practice to test them against a wide range of subsurface conditions, a range that expresses the envelope of subsurface uncertainty. Whilst these commonly held objectives are more or less universal, selecting an appropriate subsurface modelling strategy (i.e. what to model & how to model it) to achieve these objectives usually generates more divergent views. Whilst there are always various valid modelling approaches available which are both geologically and numerically valid, a good modelling strategy pays close attention to the type of the specific decisions being taken for the project and the accuracy required to take those decisions. To align these views, in decision-based modelling, business decisions and their timing were mapped to the models needed to make the estimates that inform them. Dialogue between the disciplines established the accuracy required for these estimates, and these discussions often revealed surprising opportunities to simplify processes and accelerate delivery. The outcome is a common view on a decision-driven modeling strategy that enables business decisions to be taken efficiently. This strategy, and the subsequent delivery plan that is developed from it is seen as a key to success. This paper describes the decision-based approach taken in the subsurface modelling required to support quality development decisions for the development of two of KOC's Heavy oil fields through the Enhanced Technical Service Agreement (ETSA) between Shell and KOC. In this particular application of the process, the suite of models to be built has been mutually agreed at the start by the integrated development team through a structured collaborative workshop, or Model Framing Event. A fullfield and a sector model for 2 different fields are discussed to exemplify the link between required decision and supporting modelling approach.