84th EAGE Annual Conference & Exhibition

Drilling through carbonates and open karsts is very challenging due to potential severe mud losses and hole instability. In case hydrogen sulphide is present in high concentrations in these geological conditions, this could lead to hazards that are difficult to cope with. The objective is to reveal innovative drilling experience of the first ever exploration well on the Fedynskiy High in the Norwegian Barents Sea, on the borderline of Norway in the Barents Sea. Various methods of drilling and coring in karstified carbonate formations with presence of sour gas in high concentrations have been explored.

During planning, it was demonstrated that modern modelling techniques allow comprehensive analysis of H2S formation process in the reservoir fluid in the Norwegian Barents Sea, especially if both chemical and regional factors are taken into account. This is the first frontier exploration well drilled from a mobile unit on the NCS remotely with risks associated with karst and H2S.

New approaches have been developed to deliver the well in a safe and efficient manner.

Much effort has been used on modeling and regional studies. Experience uncovers new cost-efficient and safe solutions that can be considered in other regions worldwide with similar overall risk picture.

Mitigation of asphaltene within the tubing has been a major challenge resulting in severe economic consequences through time. A number of mitigation attempts have been made in the recent past in wells producing from the lower Jurassic reservoirs with very limited encouraging results.

Various chemical inhibitors available haven’t performed well, or could have exhibited some results with very extremely high dosages, thereby rendering them to be not economical for use.

Mechanically scrapping of the asphaltene deposit from the tubing using coil tubing is the most widely used method to mitigate the buildup of asphaltene in the tubing.

Additionally, the use of fluoropolymer coated tubing’s have shown promising results after having them deployed in one of the deep Marrat wells. To realize the full potential of this methodology, more wells could be taken up for coating and ultimately this approach could be expanded to the entire field.

Seismic diffraction imaging (DI) is applied to a field in the Norwegian North Sea, with a focus on two targets, an injectite reservoir and a deeper basement section. The DI is supported by customization to interpretation all along the workflow. A suite of DI volumes is produced to sample the continuum between diffractivity and reflectivity. This provides a clear uplift in resolution of the injectite complex and a highly faulted basement. The 3D geological organization of the diffraction image is demonstrated by extracting geobodies from the DI and comparing the forward model response of these geobodies to a premigration stack.

The era of easily producible oil and gas has ended for quite some time, and new oil and gas fields are slowly being discovered in low to high combinations high pressure and high temperature (HPHT) wells. Generally, HPHT wells are classified under a pressure range of 10,000 to 30,000 psia and a temperature range of 350 °F to 500 °F. High density fluid systems have the ability to control the well high pressure for wellbore stability with high density, which contains fewer solids and maintains rheological stability at the HPHT reservoir for minimizing the formation damage and satisfy environmental requirements. This has demanded that new and novel packer and completion fluid designs be developed for low to high combinations HPHT wells. In this paper, developed fluid has shown with high specific gravity and optimum rheology. The calculated apparent viscosity (AV) was found low value which is desired for packer and completion fluid. Our firm belief is that the fluid can be designed optimally for a particular set of requirements specific to aid the completion process with efficient cost, less and high efficiency. From the industrial application point of view, it needs to be free from weight enhancing solid particles.

GPR and Resistivity surveys results are presented for the Central-East region of São Paulo State, Brazil. This region is a groundwater recharge zone at an outcrop area of the GAS-Guarani Aquifer System in the Paraná Basin. GAS is one of the largest transboundary aquifers in the world with ~1.2 million km² underlying four countries in South America (Paraguay, Uruguay, Argentina and Brazil). Our objective was to map the stratigraphic heterogeneity and hydrogeological characteristics using GPR and Resistivity methods to improve a groundwater conceptual model. GPR results of 200 MHz suggested that near to the main drainage the water table is in a layer of sandy materials. Moving away from the creek, the water table is in a layer with higher clay content and strong reflection, which may be related to a transition zone from recent sediments to the Botucatu Formation residual. Saturated and unsaturated layers were defined in a resistivity profile. Geophysical results showed good agreement with the lithological information from wells and soil samples. The zone of highest hydraulic conductivity was identified near to discharge areas in the Onça creek basin. The results contributed to improve a numerical model of groundwater flow in the GAS recharge zone.

When seismic waves propagate in the underground medium, the stable wavelet is affected by several factors. The purpose of surface-consistent correction is to eliminate the influence of complex factors at source and receiver on residual statics, phase, and amplitude of wavelets from the same stable reflector, which is typical deconvolution. Surface-consistent deconvolution can be referred to as a Bayesian estimation problem. However, it requires a great deal of computation, the statistical method should be more efficient. Based on statistics and physical understanding, maximizing the CMP stack has been proved to eliminate residual statics and phase changes, and particle swarm optimization (PSO) algorithm is used to explore the non-convex parameter space. Then, under the physical assumption that the energy of wavelets from the same reflection interface changes steadily, the prediction-energy-change equation is introduced. The spatial mutations of amplitudes are corrected by solving a nonlinear equation system. Theoretical and practical applications show the effectiveness.

We propose a novel wavefront operator-based seismic data reconstruction method to reconstruct spatially undersampled data. The methodology is based on the existing nonlinear beamforming (NLBF) framework used for seismic data enhancement. Traveltime operators are established and describe kinematic wavefronts on a sparse grid. The sparse wavefronts are then interpolated to the desired spatial resolution. We applied our NLBF reconstruction algorithm to a synthetic Society of Exploration Geophysicists Advanced Modeling (SEAM) Arid dataset with high-quality reconstruction results achieved. The NLBF reconstruction results of the synthetic SEAM Arid dataset show high trace fidelity to the ground truth in both the t-x and f-k domains. These results show the potential of the NLBF reconstruction method to become a common data reconstruction tool used in the seismic industry.

The fluid and clay have important influences on the migration and accumulation of oil and gas. It is a key problem to effectively distinguish the fluid and clay in reservoirs. Fluid and clay are also an important factor in reservoir prediction using seismic data, which has a great impact on P and S wave velocities. Therefore, seismic data can provide effective information for identifying fluid saturation and clay in reservoirs. P wave is affected by many factors, and shear wave field is mainly affected by rock matrix. The comprehensive utilization of P wave and S wave data can improve the reliability and accuracy of oil and gas seismic exploration. The seismic responses of PP-, SV-SV and SH-SH waves are analyzed based on seismic physical model. It is found that PP- wave is more sensitive to the fluids, while the SH-SH wave is not sensitive to the fluids and have better imaging results. The SV-SV wave is still affected by the fluids, and the imaging results is not as good as the SH-SH wave. It also shows that SH-SH wave can have better responses to the changes caused by clay. The multiwaves can help for better fluid identification and reservoir description.

This paper shows results of Curie point depth (CPD) analysis of the Japanese Islands using magnetic data based on fractal theory. CPDs by magnetic data (Dcmag) with 50km window size range 6–9km deep in volcanic areas and are deeper than 9km in non-volcanic areas, which are concordant with the previous study. Cutoff depths calculated by JMA unified catalogue are 10km or shallower in volcanic areas, deeper than 20km in the forearc side and concordant with Dcmags. Dcmags across Kakkonda geothermal power plant (GP) gradually become shallower from 6.8km west Akita-Komagatake toward to 4.6km near Iwate volcano. The depth-to-temperature curves from drillhole database around Kakkonda GP show that thermal gradients between Iwate volcano and Kakkonda GP range 0.157–0.222K/m. Assuming that these thermal gradients continue from the bottom of hole to the deeper part, the depths reaching 580°C (Dchole) are determined. Dcholes are concordant with Dcmags in the west of Kakkonda GP and much shallower than Dcmags in the east. This suggests that Dcmags in the west represent CPD, but miss to delineate a local high temperature area smaller than 50km square in the east.

Hydrogen has become a very promising energy carrier. Large scale hydrogen production facilities have been constructed in order to satisfy the growing demand for hydrogen derived products.

A major current process to generate hydrogen is autothermal reforming that utilizes oxygen, steam and carbon dioxide together with methane (derived from natural gas) in order to produce hydrogen.

A crucial challenge in the optimization of the hydrogen production process while ensuring to minimize the overall carbon dioxide emissions into the atmosphere, is to optimize both natural gas production and CO2 sequestration.

The framework was examined on the New Zealand McKee reservoir structure model with multiple producing wells and a separate CO2 sequestration reservoir. Simulated historical production and injection data were generated for a time period of three years for various production and injection levels. A robust global optimization approach, based on an artificial intelligence genetic optimization, allows for simultaneously optimization of an injection pattern and uncertainty quantification. Results indicate potential for significant reduction in required carbon dioxide, while maximizing hydrogen production. The developed deep learning framework represents an innovative approach towards enhancing sustainability optimizing hydrogen production. The framework can be easily expanded to other types of reservoirs and production environments.