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Petroleum Geologists typically study hydrocarbon bearing reservoirs, understand the geology, and build numerical models to help better produce hydrocarbon. On the other hand, conventional sedimentologists try to simulate the natural process of sedimentation in laboratory through miniature sand box models to better understand such processes. But a proper integration of the laboratory-based techniques in developing subsurface reservoirs models was always lacking in the industry.

Petroleum geologists developed computer based geostatistical techniques based quantitative statistics like variograms, histograms to develop stochastic models of reservoirs which could be used to put a number and range on the geological uncertainty. However, geostatistics deals more with regularly sampled data, describing their spatial variability and directionality. In development oil fields with many wells sampling the reservoir, geostatistics helps us to create a more predictive subsurface reservoir model. However, in the exploratory state of a field with few drilled wells, the data for geostatistical analysis reduces and a robust conceptual geological is needed to build a predictive subsurface geological model where a proper integration of sedimentology and petroleum geology is required.

Different approaches like conceptual block diagrams of depositional models, average sand distribution maps, training images from present day analogs were tried. However, these were less than optimal, deterministic with a long turnaround time for any robust subsurface reservoir model.

A relatively recent addition to the geologist's set of quantitative tools has been Geologic Process Modeling (GPM), also known as Forward Stratigraphic Modeling (FSM) technique. This technique aims to digitally model the natural processes of erosion, transport and deposition of clastic sediments, as well as carbonate growth and redistribution based on quantitative deterministic physical principles (Cross 1990; Tetzlaff & Priddy 2001; Merriam & Davis 2001). The results show the geometry and composition of the stratigraphic sequence as a consequence of sea-level change, paleogeography, paleoclimate, tectonics and variation in sediment input. In other words, GPM brings the sedimentologists laboratory sandbox model to a petroleum geologist in his computer with the opportunity of unlimited experimentation. GPM technique is based solely on numeric modeling of open-channel flow, currents, waves, and the movement of sediment. The observed stratigraphy is the result of modeling a physical system which can then be further used for refinement in a geological facies model. (Tetzlaff et. al 2014) In the current study a 3D reservoir model for a field in Western Offshore India was built based on the results of Geological Process Model (GPM) for the thin deltaic reservoir sands as understanding reservoir continuity from seismic data was not possible. With only 4 wells available in the field, traditional geostatistics based reservoir models were inadequate in explaining the reservoir distribution. GPM based techniques helped not only in mapping the reservoir continuity but also opened up new areas for exploration in the area.

Eni started production from the Perla giant gas field located in the Gulf of Venezuela, 50 km offshore. Consisting of Mio-Oligocene carbonates with excellent characteristics, the reservoir is approximately 3000 m below sea level and lies at a water depth of 60 m. The best wells are estimated to produce more than 150 MMscf/D of gas each. The development plan includes 21 producing wells and four light offshore platforms linked by a 30-in. Two treatment trains have been installed at the facility, each capable of handling 150 Mscf/D and 300 Mscf/D of natural gas.

This case study describes the successful outcomes and learnings from a brownfield tie-back project in offshore Trinidad. The greater Angostura Asset consists of multiple Oligocene-age turbidite sandstone reservoirs with complex geology and compartmentalization. The Asset has produced oil since 2005 from thin oil rims overlaid by large gas caps. This has been supported by significant gas reinjection and constrained by gas coning. Commencement of gas sales added value but also increased gas cap blowdown in the oilfields. The Angostura Phase 3 project was conceptualized to enable gas production from an adjacent gas discovery and extend the overall productive life of the existing oil fields.

Key subsurface uncertainties and operational constraints were identified early in the project. Historically, drilling in the Angostura field has been challenging due to the complex geology and compartmentalization. Poor seismic data in the Phase 3 area added complexity to optimal well placement. Ensuring high deliverability was another critical project requirement. The main reservoir management challenge in the existing fields was optimizing both oil and gas sales while managing voidage and coning. Limited topside facilities and space constrained addition of new gas at flowing at higher pressures.

To address these challenges, a multi-disciplinary project team was formed to plan and execute the project. Material balance, detailed geological modeling and numerical simulation were used to understand the impact of key uncertainties on recovery. The integrated evaluation resulted in an optimized development plan with three subsea gas wells tied back to existing facilities. Production performance of existing wells helped highlight critical performance drivers for Phase 3 wells. Modified completion designs along with a flow back and stimulation program during completion helped to maximize productivity.

Phase 3 wells have performed at the high levels expected during project design and sanction. Detailed surveillance (including pressure transient analysis (PTA) and interference testing during completion, start-up and production phases) has continuously helped to optimize production. Oil production in the existing fields has also been improved by better balancing gas sales and injection. The project added significant value from the increased gas sales and oil production.

This paper discusses the planning, successful execution and impact on the overall value of the Angostura Asset from the Phase 3 project. Optimized completions along with an improved approach for evaluating stimulation options during completion (detailed near well-bore modelling, real-time PTA and simulation) enabled strong well performance. We highlight some of the critical factors for achieving success in brownfield tie-back projects including having (right from project inception): multi-disciplinary project teams, tight coordination with existing operations and a focus on key uncertainties and constraints. Building optionality and flexibility into development plans and being prepared for contingencies have been the other critical learnings from this project

The purpose of this paper is to use 3D compaction numerical simulation method to study the sandstone porosity evolution and high-value porosity area in the few well areas of offshore oilfields. These sandstones are located in the central inversion structural belt of the Xihu sag, East China Sea Basin. Based on geological data, seismic data, log data, thin section, scanning electron microscopy, cathode luminescence, bulk X-ray diffraction analysis, powder particle size analysis and routine core analysis, this study used compaction numerical simulation method to reconstruct the porosity evolution of different grain size sandstones in the fourth (H4) and fifth (H5) members of the Oligocene E3h Formation in the study area. Three aspects of research were carried out, including the distribution model of 3D grain size sandstones, mechanical compaction and chemical compaction parameters, 3D porosity evolution and high-value porosity areas. It was determined that there was no correlation between the porosity compaction loss and quartz cement content in different grain size sandstones in the H4 and H5 members, indicating that chemical compaction did not inhibit mechanical compaction. The mechanical compaction and chemical compaction were simulated separately. Different grain sizes sandstones had different mechanical compaction and chemical compaction porosity reductions. The porosity reductions of medium sandstone, sandy conglomerate and fine sandstone by mechanical compaction were 25.3%, 21.81% and 25.97%, and those by chemical compaction were 0.82%, 1.08% and 0.42%, respectively. The sandstone compaction stages of the H4 and H5 members under different tectonic stages were investigated. In the first phase of the slow subsidence stage, the reservoir temperature of the H4 and H5 members were less than 70°C, and these sandstones were in the stage of mechanical compaction. In the second phase of the slow subsidence stage, the reservoir temperature range of the H4 and H5 members were 70°C–114.63°C and 70°C–120.47°C, respectively; these sandstones entered the coexistence stage of mechanical compaction and chemical compaction. From the rapid subsidence stage to regional steady subsidence stage, the reservoirs temperature ranges of the H4 and H5 members were 114.63°C–159.7°C and 120.47°C–167.05°C, respectively; these sandstones were in the stage of chemical compaction dominated- mechanical compaction supplemented. Finally, the differences of sandstone compaction and porosity between the H4b-6 and H5-6 submembers and in the same layers were analyzed. By integrating sedimentary lithologies, porosity evolution, and reservoir "sweet spot" evaluation criteria, the spatial distribution of favorable areas in the H4b-6 and H5-6 submembers were determined. This study is of theoretical significance to elucidate the compaction characteristics, porosity evolution and high-value porosity area distribution in deep and ultra-deep clastic rocks, and also has reference value for the optimization of the tight sandstone favorable areas.

High angle S-shaped and high displacement L-shaped well profiles are preferred now-a-days in Balimara field located in the northeast region of India. Main targets are the deep Clastic reservoirs of Oligocene age. Major events reported are while drilling against dipping formations with differential stuck pipe situations with variety of drilling complications in the unstable formations owing to shales in Tipam sandstone and thin sections of coal and shale alteration in oil bearing Barail sandstone formation. The substantial risk of wellbore instability in accessing the reservoirs with lateral variation in pore pressure threatened the commercial success of the project. This paper elaborates how geomechanical information along with BHA design and chemicals was integrated into the decision-making process during well design and drilling operations to avoid wellbore instability issues.

Wellbore stability analysis through Mechanical Earth Model was conducted using estimated state of stress and mechanical properties of the overburden and reservoirs. The model incorporated data from several sources including geophysical logs, leak-off tests, advanced sonic far field profile and drilling records collected from the earlier wells. Examination of the deviated well bore profiles suggested occurrence of ledges due to lower mud weight and improper drilling parameters while drilling alternate layers of sand, shale and coal in Barail formation. Horizontal stress contrast increases in Barail formation supporting the need of higher mud weight with increased well deviation towards specific azimuth.

The integrated geomechanical analysis provided key information: The 9 5/8" casing shoe should be set at shale layer of Tipam Bottom to isolate upper differential sticking prone sandstone layers with Barail Argillaceous sequence. This will help to drill 12.25-inch hole with 9.6 ppg-9.8 ppg only. Shale layers at Tipam bottom require 10.0-10.5 ppg, while Barail shale requires 10.5 ppg-11.0 ppg for vertical well. When the well deviation increases up to 30deg, mud weight requirement rises to 11.2 ppg-11.8 ppg. Based on analysis, the mud weight at the start of 8.5inch section was raised sufficiently to 10.5 ppg to avoid the hole collapse experienced in the earlier lower angle wells. Later, continuous review of torque and drag along with cutting analysis helped to raise mud weight up to 11.0 ppg till well TD. As a result, lower UCS shale and coal layers are drilled with minimal shear failure and improved hole condition. However, changes to the mud system were needed to limit fluid loss and avoid differential sticking across the sandstone. For deviated section, rotary BHA has been used to improve hole trajectory vs. planned with lesser ledges. Downhole hydraulics has been maintained with proper flow rate and rpm to main hole cleaning. The new well engineered with the integrated geomechanics information has been drilled from surface to extended TD while saving 15 rig days.

The PDF file of this paper is in Russian.

Petroleum Geologists typically study hydrocarbon bearing reservoirs, understand the geology, and build numerical models to help better produce hydrocarbon. On the other hand, conventional sedimentologists try to simulate the natural process of sedimentation in laboratory through miniature sand box models to better understand such processes. But a proper integration of the laboratory-based techniques in developing subsurface reservoirs models was always lacking in the industry.

Petroleum geologists developed computer based geostatistical techniques based quantitative statistics like variograms, histograms to develop stochastic models of reservoirs which could be used to put a number and range on the geological uncertainty. However, geostatistics deals more with regularly sampled data, describing their spatial variability and directionality. In development oil fields with many wells sampling the reservoir, geostatistics helps us to create a more predictive subsurface reservoir model. However, in the exploratory state of a field with few drilled wells, the data for geostatistical analysis reduces and a robust conceptual geological is needed to build a predictive subsurface geological model where a proper integration of sedimentology and petroleum geology is required.

Different approaches like conceptual block diagrams of depositional models, average sand distribution maps, training images from present day analogs were tried. However, these were less than optimal, deterministic with a long turnaround time for any robust subsurface reservoir model.

A relatively recent addition to the geologist's set of quantitative tools has been Geologic Process Modeling (GPM), also known as Forward Stratigraphic Modeling (FSM) technique. This technique aims to digitally model the natural processes of erosion, transport and deposition of clastic sediments, as well as carbonate growth and redistribution based on quantitative deterministic physical principles (Cross 1990; Tetzlaff & Priddy 2001; Merriam & Davis 2001). The results show the geometry and composition of the stratigraphic sequence as a consequence of sea-level change, paleogeography, paleoclimate, tectonics and variation in sediment input. In other words, GPM brings the sedimentologists laboratory sandbox model to a petroleum geologist in his computer with the opportunity of unlimited experimentation. GPM technique is based solely on numeric modeling of open-channel flow, currents, waves, and the movement of sediment. The observed stratigraphy is the result of modeling a physical system which can then be further used for refinement in a geological facies model. (Tetzlaff et. al 2014)

In the current study a 3D reservoir model for a field in Western Offshore India was built based on the results of Geological Process Model (GPM) for the thin deltaic reservoir sands as understanding reservoir continuity from seismic data was not possible. With only 4 wells available in the field, traditional geostatistics based reservoir models were inadequate in explaining the reservoir distribution. GPM based techniques helped not only in mapping the reservoir continuity but also opened up new areas for exploration in the area.