The paper discusses conceptualization, design and implementation of the first ever inflow tracer technology application in UAE carried out in an Abu Dhabi offshore field. Working in offshore environment has challenges related to operations, cost, resource requirements and HSE that requires innovative and cost-effective solutions to improve efficiency. In recent years, controlled release smart tracers have carved out a niche as a proven solution for extended life fluid flow monitoring, thus allowing the engineers and geoscientists to better understand fluid inflow patterns in a well leading to informed decisions on reservoir management and production optimization. Smart tracers have the capability to detect, quantify and monitor phase breakthroughs and understand subsequent influx behavior in the well. Being a pioneer project, critical focus was placed on design, execution, and cost optimization. Smart tracer technology was chosen over conventional production logging as it provided production profile monitoring over time compared to single time measurement when using production logging, substantially lower operating cost as well as no production intervention. A flowback calculation was used inputting static and dynamic reservoir data to understand the flow dynamics that the tracers would encounter. Reservoir permeability profiles, image logs and hole rugosity were utilized to identify potential areas of influx along the wellbore and strategically place specially designed smart oil and water tracers along the ~3300 feet long lateral. Strictly adhering to local environmental regulations, a thorough offshore job hazard analysis was carried out and a risk matrix was framed. A specialized first of a kind closed loop customized sampling procedure was invented to de-risk a hydrogen sulfide (H2S) hazard present during sampling operations. The paper describes the initial results for the first well in the campaign. Sampling strategy consisted of two phases: high-frequency immediately after well commissioning followed by steady state sampling. Samples were collected at the wellhead and analyzed for tracer breakthroughs. Results showed a good calibration with conventional production logging, confirmed well clean-up and yielded crucial information on zonal flow contribution. Utilizing a local cost model, smart tracer technology was found to offer typical cost savings in the order of US$10 million for a ten well program over five years as compared to conventional production logging. The paper offers insights into the first application of controlled release tracers in offshore Abu Dhabi highlighting the best practices in project design, techno-economics, hazard analysis and operational excellence. The success of the project is the first major step towards embracing this advanced technology for reservoir monitoring and surveillance. This opens opportunities for similar applications elsewhere with significant potential to incentivize life-cycle cost of reservoir management and improve hydrocarbon recovery.
Merging 3D seismic surveys into a seamless single 3D volume, either post-stack stage or pre-stack stage, is a challenging task on seismic data processing. This study describes some tips from coastline Abu Dhabi where we successfully managed merging two partially overlapping surveys during post-stack stage, one from transition zone (land and shallow marine) while the other one from offshore 3D OBC seismic survey, in order to understand subtle geological structure relationship among two areas. Since spatial sampling between two surveys are greatly diverse due to different orientations and grid sizes, a conjugate grid which is identical to a main cube had been applied over the subordinate one that enable the whole dataset to interpolate and process as a same grid. Then we deployed pre-conditioning steps over the subordinate dataset to minimize their quality differences where we particularly focused on residual noise, multiples, frequency contents and event timings. Lastly, a matching filter was designed and applied to the subordinate side to compensate residual amplitude, frequency and phase and produce a final dataset for structure interpretation. A single consolidated seamlessly merged volume was produced throughout the steps as described above along with well-to-seismic calibrations. Seismic interpretation was conducted over the main reservoir between two datasets/fields with a good degree of confidence. The present day structure separation and structure growth history were analyzed as a part of the structure interpretation. Moreover, this case study illustrates the add values of the seismic 3D merge from the aspect of regional structure restoration, and revealing structure relationship between the overlapping surveys. The final merging result outcome of this case study has an amenable structure continuity and seamless horizon mapping of the common reservoir target level between the two surveys. Additionally, the merged seismic cube did showcase a lateral zero phase wavelet stability of the existing wells that verified the reliability of the conducted post-stack seismic merging processing workflow. This case study has successfully demonstrated and summarized key technical tips that are recommended for merging datasets on post-stack domain in the future. However, pre-stack merge is also and still strongly recommended since static corrections, velocity pickings and imaging processing can be applied throughout the two surveys in one go while these cannot be fixed on post-stack merge. From data acquisition perspectives; enough overlap to reaching the full-fold rim of the overlapping surveys is highly recommended.
Objectives/Scope Recently Abu Dhabi National Oil Company has called Whitson (PERA), a world leading PVT modelling consultancy company, to develop a best practice methodology/tool to quantify the condensate liquid production originating from the gas cap that is produced through oil rim producers' wells. This practice is integrating simulation work with field measured data and provided for the first time a solution to an oil and gas industry challenge, which is causing a conflict of interest between shareholders especially when oil rim and the associated gas cap are belonging to different concessions. Methods, Procedures, Process The work has been done for a giant oil field with large gas cap (rich in condensate) where only the oil is being developed since the 1960s. Initially the production GOR was limited to RS, but in 2010 the development strategy changed, and the field was being produced at GOR higher than RS allowing free gas from Gas Cap (rich with condensate) to be produced with oil. The question then arised of how much condensate is being produced through the oil rim producers. The condensate allocation method makes use of all measured well test data (Qo, GOR and API) and compositional reservoir simulation results. The used EOS (equation of state) model has been tuned to all available laboratory PVT data. This method uses a history-matched, reservoir simulation model run with a "dual-EOS" that is constructed by duplicating the tuned EOS model into two identical EOS models - one for the initial gas cap, and the other one for the initial oil zone. The dual- EOS run gives identical performance to single EOS model run. The generated dual-EOS compositional wellstreams are adjusted (1) to honor exactly the historical well test GOR data for each well, and (2) to honor as best possible the historical well test APIs for each well. The resulting wellstream will honor exactly the simulation model oil rates of each well throughout history, exactly the measured well test GOR, and close-to-exact APIs for each well. The final altered well streams are processed through a 4-stage field separator, yielding the well total stock-tank oil and condensate volumes. Results, Observations, Conclusions Historical gas cap condensate volumes produced from wells completed in the oil rim has been achieved during the field history. This was made possible by using (1) well production test data (GORs and APIs), (2) results from a history-matched compositional model, (3) tracking of components originally found in gas cap and in oil rim, and (4) application of a tuned EOS model. The conclusion is that such an integrated approach will result in a consistent and quantitatively accurate volume of condensate production volumes. Novel/Additive Information An innovative quantitative approach to the accurate estimation of condensate volumes originating in the gas cap - but produced from wells completed in the oil rim zone - has been developed and validated and could be applied for other fields, in addition it is fully flexible for future enhancements if needed. This methodology will definitely save time and unnecessary discussion and will provide more consistent results that will lead to more consensus from different parties.
The presence of residual oil below Free Water Level is common in Middle Eastern fields. This later is explained by the presence of a paleo oil-water contact. An early water movement and sweep of the accumulated oil induced by tectonic events after its charging, has led to the trapping of residual oil below the curent Free Water Level. This theory is also supported by the presence of tarmat above and below this Free Water Level along the paleo oil-water contact. In the studied field, the analysis of fluid saturation logs, early well tests and initial fluid gradients have led to the definition of the oil-water contact and the Free Water Level at discovery time. The analyses of cored wells and water saturation logs have demonstrated the presence of oil below this Free Water Level which is explained by the presence of a paleo oil-water contact. Furthermore, this analysis has enabled the definition of the geometry of this paleo oil-water contact, which appears to have a curved shape. This geometry has also been confirmed by the presence of tarmat along the defined paleo contact. Modeling of the water and oil saturations below Free Water Level cannot be achieved by a conventional methodology using a saturation height function. Therefore a specific workflow has been developed. Given that oil saturation below Free Water Level is rock type driven, it could be distributed in 3D as any static property. Water saturation logs were consequently upscaled and populated in 3D using a Sequential Gaussian Simulation algorithm with the rock types as main driver. The resulting grid has been extracted up to the base of the transition zone of the main oil column and merged with the oil saturation grid generated using a saturation height function. A thorough dynamic synthesis of the field has highlighted a specific dynamic behavior of the water injectors perforated below the Free Water Level. In some specific intervals of the reservoir, high shut-in pressures have been identified. These high pressures can be explained by the presence of residual oil below the Free Water Level which acts as a baffle inducing a partial confinement of the injectors. The implementation of this residual oil in the simulation model reduces the injected water mobility and drastically improves the pressure match.
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