Traditionally, mechanical property estimation is carried out by destructive testing, which is costly and time consuming. Sometimes, the time schedule in the mill is so tight that coils are dispatched, while the samples are still under investigation; thus, knowledge of the strip quality immediately after rolling without mechanical testing can save a lot of time and money. As the rolling process is complex and final mechanical properties of steel depend on many parameters, it is almost impossible to develop an accurate first principle based mathematical model, so an artificial neural network based model to predict the mechanical properties of hot rolled steel strip has been developed. This paper describes the neural network based online system that helps in predicting mechanical properties of interstitial free (IF) steel strip and also elaborates how this models can help in capturing various metallurgical phenomena during rolling.

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The paper describes the experience of polymer injection pilots from both subsurface, surveillance and facilities perspective. It also discusses the optimization approach for revising the full field polymer plans. Bhagyam is an onshore oil and gas field in Rajasthan, India. The main producing unit is Fatehgarh multi-storied fluvial sand stone of Paleocene age. The oil is moderately viscous (20 cP to 400 cP) with a vertical viscosity gradient. Reservoir quality is excellent with porosity in the range of 25-30% and permeability of 1 to 10 Darcy. Bhagyam was developed as an edge water injection drive with 153 development wells and put on production in 2012. Polymer flood was recognized early in field life as a viable secondary recovery process. Bhagyam has several characteristics suited for polymer flood like high initial oil saturation, high rock permeability, low reservoir temperature, low connate water and low water salinity. A full field polymer development plan was envisaged in 2013 with a combination of pattern polymer flooding and peripheral polymer injection in water leg. But the field performance under water flood was way below expectations. Along with the fall in crude prices in 2014, the project turned economically unviable. Two polymer injection pilots were done to de risk the polymer flood. A multi-disciplinary team worked to optimize the pilot and full field development plan and improve the modeling of water flood. The two pilots used skid mounted polymer preparation units installed at the well pad and focused on data gathering. An online viscometer and special sampler with chemical stabilizers were used for polymer viscosity measurements. PLT, IFOs and polymer quality parameters like filter ratio, viscosity etc were also regularly measured. A revamped reservoir model was built for the field which helped better characterize the water flood performance. The tests were successful with the wells injecting at or better than expected rates. The offset response was good with WOR drop and oil rate increase in many nearby producers. The conformance of some injectors was successfully managed with selective completions installed. To reduce costs, additional well drilling count was reduced by focusing on high net pay areas, reducing polymer consumption by cutting back on water leg polymer injection, and optimizing polymer viscosity. Pipeline requirements were reduced and polymer injection facilities modified from centralized to skid based. The optimization significantly reduced costs compared to the earlier plan. The economic viability of the project was established at lower oil prices and the modeling efforts along with pilots helped significantly reduce the uncertainty associated with the project.

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The directional drilling companies in oil industry usually provide well placement services using proprietary geosteering software that utilize conventional Logging-While-Drilling (LWD) data. Usually online access to the recorded logs is available to end users, but often very limited capability exists within the oil companies to test geosteering interpretations and advise. Present paper shares the case studies of some wells in which Gas-While-Drilling (GWD) data was used in conjunction with the LWD data for well placement. Furthermore, the Geosteering Module of a third party 3D Geological modeling software was used independently within the West Kuwait Fields Development group of KOC for well placement. Well D-08 was drilled as vertical producer in a West Kuwait Marrat carbonate reservoir, produced economic quantities of oil during initial testing, but it started cutting high amount of water due to the effect of a fault. Therefore, the well was re-entered and sidetracked at a high angle, away from the fault. Similarly, the U-73 vertical well which encountered poor reservoir facies on flank of the field, was re-entered for productivity enhancement into a thin porous reservoir layer as horizontal sidetrack towards the crest. Both these wells were monitored and geosteered in near real-time using a geosteering software module which combines the overall structural framework provided by 3D geological model, along with the well log responses characteristics from offset wells, to produce a detailed pre-drill model for Geosteering. This is achieved by forward modeling to predict changes in log characters along the planned wellbore profile. The results are displayed both in vertical and measured depth domains along a 2D curtain section with formation tops parallel to the planned well azimuth. In addition to the conventional LWD logs, the GWD logs generated from advanced gas analysis of the drilling mud were used for geosteering during drilling well D-08 and U-73 re-entry sidetrack wells. The LWD and GWD based geosteering were done independent of each other to test the efficacy of GWD method. Geosteering software and advanced mud gas data have been paired for high angle and horizontal well placement for the first time in Kuwait which successfully guided the well trajectory while drilling.

Objectives/Scope This study aims to use modern techniques to re-characterise the diagenetically altered Thamama Group reservoir units of multiple gas-condensate fields in Sharjah, UAE and determine robust rock-typing framework from the full dataset and recent core analysis program. This would be used to reduce mismatches observed in static and dynamic properties and demonstrate that a matched-outcome can be achieved with less model manipulation by focusing on textural variances within the units. Methods, Procedures, Process Results, Observations, Conclusions Four petrophysical rock types were identified and found good equivalence to the identified petrographical rock types; the algorithm separated mono-modal micritic packstones from highly diagenetically altered grainstone-wackestone rudstone facies, with the rock-type clusters also being defined by Winland-r35 and Lucia poro-perm threshold lines. A single rock-typing framework, suitable for all studied fields with observed differences being explained by variability in the rock type proportions. When compared to the previous rock typing framework and reservoir models, better matches were achieved between predicted properties and core data in QC wells. Static model property distributions were more realistic in achieving a volumetric match with produced gas. Better saturation distribution with realistic Swcr and Socr were observed by using the new Rock Typing Sw equations. Rel-perm modification for increasing water production to match the observed data was negligible due to presence of more water saturation in the crest of the reservoir. Multipliers for permeability and porosity were significantly reduced to match the well productivities and tubing head pressure estimations were improved due to less mismatch with liquid production rates. Novel/Additive Information This work represents the first time petrophysical and petrological rock typing was conducted for several gas-condensate fields in Sharjah, UAE. Newly acquired core data, petrographical information and core descriptions were integrated in the study. The previous workflow, established in 1993, was updated using modern machine-learning techniques incorporating new data and a wider range of data than the previous rock typing model that was based solely on porosity measurements, remaining consistent to pore-scale and textural changes.

Several challenges are associated with reservoir characterization of organic-rich, unconventional plays, most significantly with estimating producible hydrocarbons and identifying potential zones to land horizontal wells and subsequent stimulation. This paper illustrates integrated approach towards successful characterization of the Cretaceous carbonate major source rock-a lateral seal Shilaif formation in the recently developing area of syncline shape field in Onshore UAE. The Shilaif formation that was deposited under intra-shelf basinal conditions, contains sediments of argillaceous limestone, mostly fine-grained packstones and shaly lime mudstone-wackestones with subordinate calcareous shales in the lower part. Presence of bitumen and low permeability indicate the requirement to stimulate the wells effectively. Quantification of bitumen and light hydrocarbon through integration of advanced and conventional log data with core data and mud logs plays a critical role in the evaluation and development of these organic-rich reservoirs. Extensive data acquisition was planned with a wireline suite that included resistivity/density/neutron/spectral gamma ray; acoustic logs; resistivity image; nuclear magnetic resonance (NMR); advanced elemental spectroscopy; and dielectric technologies to characterize the hydrocarbon potential of organic-rich Shilaif unconventional play. NMR and Spectroscopy were used to refine lithology and porosity, which reduces the associated uncertinity in the evaluation of total organic carbon (TOC) and volumes. The advanced elemental spectroscopy data provided the mineralogy, the amount of carbon in the rock, and consequently the associated organic carbon within the Shilaif formation. The NMR technology provided lithology-independent total porosity and moveable versus non-moveable fluids quantification when integrated with density/neutron. NMR technology in this present case study was used to identify and differentiate the organic matter and hydrocarbon presence within the Shilaif formation. The water filled porosity and textural parameter from dielectric inversion results helped in more accurate water saturation estimation in the tight formation. Acoustic data results and high-resolution resistivity image logs were used to evaluate the geomechanical properties. In addition, Resistivity image data provided detailed knowledge of geological features, faults and natural fracture networks within the study zone to enable optimization of development scenario based on the reservoir properties. The data integration work illustrated in the paper is a key for unconventional reservoir characterization that enabled identification of the potential zone/zones of interests for horizontal wells and the successful development of the organic rich rocks of the Shilaif formation.

Several challenges are associated with the characterization of low permeability reservoirs, most significantly for the enhance oil recovery operations. The scope of this work presents the integration of petrophysics data and its application in selection of the Microfrac intervals to measure downhole fracture-initiation pressures in multiple carbonate reservoirs located onshore about 50 km from Abu Dhabi city. The objective of characterizing formation breakdown across several reservoirs is to quantify the maximum gas and CO2 injection capacity on each reservoir layer for pressure maintenance and enhance oil recovery operations. This study also acquires pore pressure and fracture closure pressure measurements for calibrating the geomechanical in-situ stress model and far-field lateral strain boundary conditions. The case study concentrates on the multiple carbonate reservoirs that consists of a succession of clean limestone and intermittent dolomitic limestone. The complex carbonate lithology and fabric combined with low permeability presents a challenge to conventional logs and evaluation. Detailed integration of advanced and conventional logs (resistivity, neutron/density, advanced acoustic logs, Dielectric, NMR, Borehole image), Pressure testing & Sampling, Microfrac in-situ stress measurements and analysis plays a critical role in characterizing the reservoir properties and enhance oil recovery operations. Extensive data gathering is conducted with wireline suite, which covered Advanced Straddle Packer/Pressure Test & Sampling - Resistivity/Density/Neutron/Spectral GR – Acoustic logs – Resistivity Image – NMR – Dielectric technologies for reservoir properties of multiple carbonate reservoirs. The advanced acoustic analysis is performed in order to study elastic properties of the formation along with identifying transverse and azimuthal anisotropic intervals. The Geomechanical modeling is performed and stress profile is calculated to identify intervals with a stress contrast, which is important for the following stress measurement interval selection. The Microfrac in-situ stress measurements provide critical subsurface information to accurately predict wellbore stability, hydraulic fracture containment and CO2 injection capacity for effective enhance oil recovery within these reservoirs. The conventional logs, advanced logs, and Microfrac in-situ measurements and analysis enabled reservoir characterization and development plans for enhance oil recovery operations. The NMR technology provided lithology independent total porosity, permeability estimations and reservoir rock quality. Advanced multifrequency Dielectric measurement provided the fluid saturation in the invaded zone and textural parameters. Advanced Acoustic and image logs provided the geomechanical properties that enable to choose the best intervals for the following Microfrac stress measurement. Geomechanical workflow allowed identifying stress measurement intervals with a good stress contrast in multiple carbonate reservoir intervals. The data integration work illustrated in the paper is a key for any reservoir characterization that enabled property evaluation and successful Microfrac stress measurement. These measurements provide critical subsurface information to accurately predict wellbore stability, hydraulic fracture containment and CO2 injection capacity for effective enhance oil recovery within these reservoirs. This in-situ stress wellbore data represents the first of its kind in the field allowing petroleum and reservoir engineers to optimize the subsurface injection plans for efficient field developing.