Africa (Sub-Sahara) Bowleven began drilling operations at its Zingana exploration well on the Bomono permit in Cameroon. Located 20 km northwest of Douala, Cameroon's largest city, the well will target a Paleocene (Tertiary) aged, three-way dip closed fault block. The company plans to drill the well to a depth of 2000 m and will then spud a second well in Moambe, 2 km east of Zingana. Bowleven is the operator and holds 100% interest in the license. Asia Pacific China National Offshore Oil Company (CNOOC) has brought its Dongfang 1-1 gas field Phase I adjustment project on line ahead of schedule. The field is located in the Yinggehai basin of the Beibu Gulf in the South China Sea and has an average water depth of 70 m. The field is currently producing 53 MMcf/D of gas and is expected to reach its peak production of 54 MMcf/D before the end of the year.
Africa (Sub-Sahara) Eni started production from the West Hub development project's Mpungi field in Block 15/06 offshore Angola. The startup follows the project's first oil from the Sangos field in November 2014 and the Cinguvu field last April. Mpungi will ramp up West Hub oil production to 100,000 B/D in the first quarter from a previous level of 60,000 B/D. The project also includes the future development of the Mpungi North, Ochigufu, and Vandumbu fields. Eni is the block operator with a 36.84% stake. Sonangol (36.84%) and SSI Fifteen (26.32%) hold the other stakes.
Chen, Meiyi (College of Earth Science, Northeast Petroleum University) | Ji, Qingsheng (Exploration and Development Research Institute) | Chen, Shoutian (No.1 Geophysical Exploration Company of Daqing Drilling and Exploration Engineering Corporation) | Qin, Longpu (Exploration Department Daqing Oilfield Company Ltd) | Cong, Peihong (No.1 Geophysical Exploration Company of Daqing Drilling and Exploration Engineering Corporation)
Based on the seismic prediction difficulties of the tight sandstone reservoir in Fuyu formation in Zhaoyuan area, single-well sequence division and connecting-well sub-layer correlation are carried out according to logging and lithologic data, and short-cycle interface position is calibrated precisely after a mutual calibration of logging and seismic data. Horizon tracing in the whole area is also carried out to build highfrequency isochronous stratigraphic framework. On this basis, the log facies modes and the sedimentary facies of the short-cycles under a high-frequency isochronous stratigraphic framework are analyzed in the target area, sand-body geometric scale parameters and their relations and sand-body development degree are calculated out, and a sand-body geological model is also built out. According to the seismic data and layer-by-layer geological model of sand bodies, a spatial distribution probability model of facies-controlled sand bodies is built out, which is used to constrain the pre-stack seismic data in facies-controlled inversion calculation. Based on the results of facies-controlled inversion, the tight sandstone prediction is carried out. Finally, a method of isochronal facies-controlled pre-stack seismic inversion prediction of tight sandstone reservoir is formed and it realizes the effective prediction of superimposed sand bodies in target area. Compared with actual drilling results, the sandstone of more than 2m has clear depiction and the sandstone of between 1-2m also has response, which indicates that this method is feasible and practicable.
Y. Hu, Q. Gan, A. Hurst, University of Aberdeen; D. Elsworth, Pennsylvania State University Pressure transient data may be acquired from wells during exploration, appraisal and production. Each data set provides important dynamic information that facilitates the decision-making process at the various phases of reservoir development. The course will summarise the fundamentals of pressure transient analysis and discuss some of the recent advances including deconvolution. Emphasis will be placed on the value of information. The course will combine explanations of theory (with course notes), worked examples (using Excel) and presentation of real case examples from both oil and gas reservoirs.
ABSTRACT: This paper presents a coupled transient thermal-hydro-mechanical model with strain-dependent hydraulic conductivity for heavy oil formation under steam injection. 3D numerical analysis is performed for the purpose of estimating the scope of area of steam penetration into the unconsolidated sandstone formation at True Vertical Depth (TVD) depth around 200 m. This analysis is part of a pilot application of a set of Cyclic Steam Stimulation (CSS) wells, which will be converted to steam flood at a later time. The following processes are performed for simulating the coupled behavior of steam penetration in heavy oil formation: 1) Build a coupled thermal-hydro-mechanical model for simulation behavior of steam penetration in heavy oil formations. Strain-dependency properties have been introduced into the model by assigning thermal conductivity and hydraulic conductivity that both vary with related values of strain component. Strain-dependent elastic stiffness has also been implemented into the model. 2) Numerical analysis has been performed for temperature distribution caused by steam penetration with Finite Element software set. Totally 13 wells are modeled in this work. Predictions of T-contour development are made for 2 kinds of scenarios of operations of steam injection plan: First one is for the case without further steam injection but only time increase; the second one is for the case with steam injection and intermission. For both cases, there are productions of oil/liquid at other wells. The case study provides a case study for numerical modeling of steam penetration in the heavy oil formation with coupled thermal- hydro-mechanical modeling. A best practice of performing this kind of analysis with Finite Element method is presented.
The process of steam penetration in enhanced heavy oil production is complicated (Al-Hadhrami et al, 2014; Boone et al, 1995; Settari et al, 2001; and Zhao and Gates, 2013). In this process, super-heated steam, whose temperature can be as high as 250°C or even higher, is injected into the heavy oil formation. As the steam flow contacts the formation, heat transfer begins between the steam and formation along with the porous flow of steam within the formation.
The Sea Lion Field is an Early Cretaceous turbidite fan complex, located in the North Falkland Basin, 220 km north of the Falkland Islands. The reservoirs are dominated by amalgamated high density turbidites (Bouma Ta and liquefied sediment gravity flows), but also contain low density turbidites, linked debrites and interdigitated lacustrine mudstones. An integrated dynamic modelling workflow which incorporates the latest understanding of the Sea Lion Field sedimentology and reservoir heterogeneities is presented.
The workflow focuses on capturing and retaining reservoir heterogeneity throughout the reservoir modelling process. Coarse-scale heterogeneity is captured during the construction of the full-field geological (static) model and conserved in the dynamic model by using the same grid dimensions. Sedimentological features (fine-scale heterogeneity) below the grid resolution are captured in separate, 3D core-scale models. Through a process of
Detailed interpretation of the available core data enables a statistical evaluation, which underpins the construction of core-scale models for the individual rock types. The resulting 3D core-scale models are representative of the reservoir and the development concept in terms of reservoir dip, lithology, petrophysical and fluid properties and well spacing. Matching the coarse model behaviour to the core-scale model forecast is an inverse problem with multiple possible solutions; therefore, assisted history matching is a valuable tool for quickly obtaining, comparing and ranking possible upscaled relative permeability functions and
This integrated dynamic modelling workflow allows for the direct use of detailed geological models characterising the main heterogeneities impacting flow behaviour, while retaining the ability to investigate and capture small-scale heterogeneities below the resolution of the full-field static model, thus avoiding the cumbersome process of upscaling geological properties. Assisted history matching and optimization have been integrated into the workflow, providing a robust method to produce upscaled relative permeability functions that replicate the expected waterflood behaviour.
Fiona MacAulay will become CEO of Echo Energy effective 4 July. MacAulay, the current COO at Rockhopper Exploration, is a geologist with more than 30 years' experience in the oil and gas industry including stints at Mobil, Amerada Hess, and BG. She joined Rockhopper in 2010 following the companies Sea Lion discovery and was a member of the senior team that managed the appraisal of the Sea Lion field as well as discoveries of the Casper, Casper South, and Beverley fields. She holds a BSc in geology from University College London and an MSc in sedimentology from the University of Reading.
Mahmoud (Mudi) Ibrahim and Gregor Hollmann, Wintershall Summary Brownfields in this paper are defined as mature fields where production declined to less than 35-40% of the plateau rate and where primary and secondary reserves have been largely depleted. Big data, high field complexity after a long production history, and slim economic margins are typical brownfield challenges. In the exploration-and-production (E&P) industry, "sequential" field-evaluation approaches (first "static," then "dynamic"), have proved successful for greenfield development, but often do not achieve satisfying results for brownfields. This paper presents a new work flow for brownfield reevaluation and rejuvenation. The "reversed" geo-dynamic field modeling (GDFM) rearranges existing elements of reservoir evaluation to obtain a purpose-driven, deterministic reservoir model, which can be quickly translated into development scenarios. The GDFM work flow is novel because (1) it turns upside down the discipline-driven sequential work flow (i.e., starts with the history match) and (2) it uses dynamic data as input to calibrate seismic (re-) interpretation that acts as a main integration step. It combines all available data already during horizon and fault mapping. Field diagnosis, flow-unit identification, well-test reanalysis, and petrophysical and geological interpretations are all combined in a cross-discipline interaction to guarantee data consistency. This directly ensures a fully integrated, "geo-dynamic" model that forms the basis for reservoir modeling.
Expansion of oil pipelines in western Canada will significantly increase tanker traffic and the probability of oil spills in the Salish Sea. To study the potential environmental effects from an oil spill, a state-of-the-art three-dimensional oil spill model was forced by a newly developed, high-resolution, hydrodynamic and atmospheric model, to simulate the fate and transport of three selected oils in the Salish Sea. A stochastic approach under a wide range of environmental conditions indicated that there is a very high probability for contamination of the Haro Strait area and the majority of the oil would stay on the surface and accumulate on the shoreline, rather than disperse into the water column.
Oil and gas resources, which account for more than 70% of Canada’s primary energy production, are of significant national economic importance. The production of crude oil in Canada reached 167.4 million m3 (1,053 million barrels (bbl)) in 2010, and the industry is still growing. Currently, there are a number of oil and gas platforms already in production off the east coast of Canada, and several new explorations have either started or been proposed. Three major pipeline projects (Trans Mountain, Northern Gateway, and Energy East) have been planned that could significantly increase oil tanker traffic from coast to coast. Increasing oil and gas activities lead to increased risk of marine oil spills. The recent example of the Deepwater Horizon oil spill has shown that it is essential to have a readily available atmosphere–ocean– oil spill system to predict the trajectory of oil and help to allocate the limited response resources (Thibodeaux et al., 2011; Mariano et al., 2011). Unfortunately, such a system is currently unavailable in Canada, and there is an urgent need to develop a coupled system to support emergency response anywhere in Canadian waters.
To fill this research gap, research and development projects to develop both fixed and relocatable coupled atmosphere–ocean prediction systems are in progress within the Marine Environmental Observation Prediction and Response (MEOPAR) academic Centres of Excellence. The main goals are to build and test a coupled atmosphere–ocean forecast system that can be set up within hours of a marine emergency, anywhere in Canadian waters; to provide short-term forecasts (hours to days) of physical properties of the atmosphere and ocean to guide response to a marine emergency; and to build the basis for an integrated observation and prediction system for Halifax Harbour in Nova Scotia, and for the Salish Sea in British Columbia, which is an area that is expecting increased tanker traffic and increased risk of oil spills from the proposed Trans Mountain pipeline.
Mahmoud (Mudi) Ibrahim and Gregor Hollmann, Wintershall Summary Brownfields in this paper are defined as mature fields where production declined to less than 35-40% of the plateau rate and where primary and secondary reserves have been largely depleted. Big data, high field complexity after a long production history, and slim economic margins are typical brownfield challenges. In the exploration-and-production (E&P) industry, "sequential" field-evaluation approaches (first "static," then "dynamic"), have proved successful for green field development, but often do not achieve satisfying results for brownfields. This paper presents a new work flow for brownfield reevaluation and rejuvenation. The "reversed" geo-dynamic field modeling (GDFM) rearranges existing elements of reservoir evaluation to obtain a purpose-driven, deterministic reservoir model, which can be quickly translated into development scenarios. The GDFM work flow is novel because (1) it turns upside down the discipline-driven sequential work flow (i.e., starts with the history match) and (2) it uses dynamic data as input to calibrate seismic (re-) interpretation that acts as a main integration step. It combines all available data already during horizon and fault mapping. Field diagnosis, flow-unit identification, well-test reanalysis, and petrophysical and geological interpretations are all combined in a cross-discipline interaction to guarantee data consistency. This directly ensures a fully integrated, "geo-dynamic" model that forms the basis for reservoir modeling.