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Benetatos, Christoforos (Politecnico di Torino) | Codegone, Giulia (Politecnico di Torino / SNAM-Stogit) | Marzano, Francesco (Politecnico di Torino) | Peter, Costanzo (Politecnico di Torino) | Verga, Francesca (Politecnico di Torino)
One of the most useful petrophysical parameters in hydrocarbon reservoir studies is the velocity of the seismic waves propagating in the Earth's subsurface. Seismic velocities have multiple applications in geophysical exploration, well log interpretation and petrophysical and geomechanical characterization. In this study we used publicly available well data (VIDEPI database) covering the Po Plain and the northern Adriatic areas to calculate the P-wave sonic velocity from the analysis of well profiles (1:1000 scale). Data were collected from 134 wells located inside the region of interest that included sonic log registrations. From each of the wells the cuttings interpretation log, the available spontaneous potential or gamma ray logs and the sonic log were digitized from existing profiles whereas the hydrocarbon-bearing-marker (resistivity log readings) and the geological formation log were constructed. The lithological and the geological formation logs were used to analyse the regional stratigraphy while the resistivity log was used to identify and exclude the hydrocarbon bearing intervals affecting the sonic log readings. The various lithologies reported on the well profiles were combined to characterize 9 main lithological groups (6 clastic, 1 marly, 2 carbonatic). For each group a linear regression was applied to extract the relation of velocity versus depth. The results show a gradual velocity increase with depth for most of the lithologies, while limestones and dolomites present constant velocities independently of the depth. Furthermore, at approximately 3.5-4 km the velocities of all lithologies tend to stabilise at a value that remains relatively constant even for larger depths. The results of this study can prove helpful for the construction and calibration of velocity models and for the calculation of dynamic geomechanical parameters (e.g. Young's modulus), which are crucial for the mechanical characterization of the rock during geomechanical studies.
Italy is one of the richest countries in terms of hydrocarbon reservoirs in southern Europe. Gas and oil accumulations in the Italian territory and in the off-shore area are mainly located along the Apennine chain, within the associated foredeep basins and along the Adriatic foreland. The gas fields are mainly concentrated in the Po Valley and within the northern and central Adriatic basin, while the oil fields are located in the Western Po Valley, Southern Apennines and Sicily , . The current geological structure of the Italian territory is the result of a complex tectonic and sedimentary evolution that began at the end of the Palaeozoic period and lasted until the Pleistocene. The Tertiary, the Alpine and Apennine orogenic events produced a chain-foreland-foredeep system whose evolution created the necessary conditions for the formation of hydrocarbon bearing deposits both on-shore and off-shore. The analysis of data from more than 250 hydrocarbon fields shows large amounts of hydrocarbon were produced in the Italian peninsula as well as extensive drilling activity for exploration purposes in a broader area . Over the last decades, more than 7000 wells were drilled in the entire Italian territory  reaching, on average, a depth of 3-4 km inside the earth's crust. In this work we focus on the Po plain and the northern part of the Adriatic Sea where more than 3500 wells provide a large amount of data suitable for the study of the geological characteristics of the sedimentary deposits present in the area.
According to the US Environmental Protection Agency, producing electricity, heat, and industrial power accounts for nearly 50% of global greenhouse gas emissions. Identifying ways to reduce energy consumption in the oil and gas industry will have a significant impact on reducing global greenhouse gas emissions.
For offshore oil and gas operations, a major power consumer is rotating equipment to add energy to the system, either for transporting fluids or increasing recovery factors. Some sort of artificial lift is often required to maintain production from a reservoir because the reservoir pressure drops due to depletion and water cut increases over time. Artificial lift with rotating equipment is a major contributor to CO2 emissions in oil extraction. A main challenge is maintaining production profitability while reducing the emission intensity and thereby the environmental footprint.
This paper explores the energy efficiency and CO2 emission impacts of different artificial lift methods, particularly multiphase boosting technology and gas lift technology, which are both mature and field proven.
A generic field model was developed to analyze the energy consumption using different improved oil recovery (IOR) technologies in gas lift and multiphase boosting. A power ratio between the two lifting techniques was defined for a clear comparison. The CO2 emission and enhanced production effects were analyzed for a range of tieback distances (5-50 km), water depths (50-1,000 m) and different number of wells. Sensitivities with regards to water cuts, separator pressure, and compressor discharge pressure are also discussed.
The study suggested that energy efficiency is dependent on field layout and that the CO2 footprint can be significantly reduced with an optimum artificial lift method.
The United Nations has adopted a set of sustainable development goals (SDGs) for attainment by 2030. Agencies such as IPIECA have outlined how oil and gas industry contributes to SDGs /2/, one of the big contributions is in energy efficiency, which is related to power consumption as well as gas flaring. The IEA estimated that 46% percent of CO2 emission savings would come from end-use efficiency compared with 17% from renewable energy /3/.
The need to adopt strategies for the reduction of the environmental impact related to marine and road transport, as well as the reduction of the fuel running costs with phased replacement of fuel oil with LNG, makes the growth of a "small scale LNG" approach crucial to support the evolution of the fuel market. Saipem recently developed an alternative LNG liquefaction technology designed to comply with the current LNG market scenario, and that is particularly suitable to small scale LNG solutions for bunkering and road fuelling. This proprietary liquefaction process technology has been implemented in a small scale preengineered liquefaction train, providing a compact arrangement with the opportunity to execute a modular installation of standardized equipment. This gas liquefaction process involves very low hydrocarbon and cryogenic liquid inventories, which makes it particularly suitable for onshore areas with reduced plot and severe permitting constraints. This also allows reducing indirect costs associated to process hazard mitigation. In addition, this technology is particularly versatile with respect to both the environment of application (onshore and offshore) and the gas composition to be liquefied. This ensures easy customization of the concept according to the project requirements.
van Elteren, Roy (Knowledge Management, DNV GL Oil & Gas) | Kelleher, Michael (Knowledge Management, DNV GL Oil & Gas) | Alberts, Jeroen (Knowledge Management, DNV GL Oil & Gas) | Verhoeven, Pieter (Knowledge Management, DNV GL Oil & Gas)
Across the global Energy industry organizations are facing the risk of knowledge loss, being the unintended consequences of for example mergers and acquisitions, industry contractions and a reliance on smaller numbers of ‘experts that were there from the start’. Additionally, the industry seeks to increase the economic life of assets, many will remain in operation longer than anticipated. Lessons learned from projects form a major component in the success of the industry. With cost pressures and delivery deadlines, the time and effort required to capture and share those lessons are frequent casualties of those pressures. The unintended consequence that our industry faces is a universal challenge: the retention of critical knowledge. Treating knowledge as an asset to be managed through the management system, addresses that challenge and unlocks the potential organizational benefits that can be gained through active and systematic strategies for knowledge retention. DNV GL has developed a programme for the retention of critical knowledge, to counter this new Industry risk. This programme covers a three-stage process. Firstly, a risk-based approach, enables management to understand and identify the critical knowledge risks both locally and on a company-wide basis and to create plans to mitigate the risks of losing knowledge during these market critical times. Secondly, a plan is developed to mitigate identified knowledge risks and knowledge transfer processes and workshops are designed and facilitated with tooling and guidance that enable experts to share their knowledge with colleagues focused on knowledge retention and reuse. Finally, DNV GL will undertake a detailed evaluation into integrating knowledge retention mechanisms in the company's management system and will propose the improvements to help to establish knowledge retention and reuse as common behaviors.
Whilst knowledge management (KM) is not new to the Oil & Gas sector, with companies such as Shell, Schlumberger and BP, amongst many others, being consistently recognised as leaders in KM within and outside the Energy sector (see, for instance, Collision & Parcell 2001), recent interest has focused attention to a significant risk to organisations in the sector: knowledge loss.
A wide range of technologies and workflows is available to assist in optimising the horizontal drilling process in real time and provide thorough formation evaluation analysis while landing and steering the wells. Traditionally, advanced surface fluid logging (ASFL) has not been relied upon as one of these methods; however, developments in the real-time fluid analysis provided by this technology were utilised to achieve a better understanding of fluid distribution while supporting critical decisions landing the horizontal section of a production well. Understanding the fluid complexity in a Danish North Sea chalk field was the main key in optimising the placement of the well. Initially, it was predicted that due to the migration of the gas cap, the fluids in the oil rim target would have undergone a significant compositional change from the virgin fluid. Placement of the well at the top of the expected oil column was critical to intercept as much of the oil as possible while mitigating against premature water/gas breakthrough and maintaining a minimum standoff from the gas-oil contact (GOC).
Snam-Stogit, among the European leaders for underground gas storage (UGS) development, manages nine depleted fields in silicoclastic geological systems, ensuring safety conditions and compliance with environmental constraints.
Multiple solutions have been deployed to improve technical efficiency and to optimize related costs, adopting the latest technology to perform a green formation evaluation and geosteer horizontal wells in complex tectonic frameworks. Snam-Stogit tested and routinely applied new technologies such as high-resolution resistivity images in slim holes recordings, sourceless formation evaluation platforms, multilayer bed boundary mapping, and reservoir mapping services. This method allowed for improving the storage capabilities while decreasing the number of wells needed for evaluation and to better understand the geological-structural setting.
The logging-while-drilling (LWD) solutions provided the opportunity to acquire data at any well deviation, minimizing the target formation alteration and invasion, often occurring in unconsolidated sands. The possibility for acquiring and interpreting data in real time was effectively used to minimize critical issues related to drilling operations, such as entering a depleted reservoir with inadequate mud weight.
A high number of wells have been drilled, including more than 30 horizontal wells, yielding the possibility to build a solid set of solutions to meet the challenges of drilling in mature gas fields, often with limited predrill data. This paper presents an overview of the evolution and state-of-the art LWD solutions applied to UGS projects. Case studies are also presented to complement the technology description and to demonstrate the impact from applying the solutions.
UGS activity began in North America in 1916 (Marzorati et al. 2012)1 and is presently a commonly used practice. Today, they are more than 600 active storage sites worldwide, with approximately 70% located in the USA and the remaining sites mainly concentrated in Europe. UGS was initially tested in Italy during 1964, converting the depleted gas reservoir of Cortemaggiore (Emilia-Romagna Region) from production to storage. Snam-Stogit, currently the major UGS Italian company, manages nine storage facilities, including Brugherio, Bordolano, Cortemaggiore, Fiume Treste, Minerbio, Ripalta, Sabbioncello, Sergnano, and Settala, (Figure 1), which operates in synergy with the transport and regasification infrastructures of the company, ensuring energy security for Italy. The UGS facilities are located in depleted gas reservoirs with average depths between 1000 and 1700 m. The geology is therefore suitable for UGS, as it worked for ensured containment in the existing natural gas reservoirs existing for millions of years.. The fields are mainly located in the Po Plain, while the Fiume Treste field is situated in the Abruzzo region (central Italy). Miocene to Pliocene poorly cemented sands and gravels, which make up the target reservoir, are covered by several hundred-m thick massive shale, acting as very efficient seal. The geological traps, both structural and stratigraphic, are associated with buried thrusts in medium-complexity geological context. Selecting the storage sites is driven by specialized studies, 3D modelling, and technical- economical evaluations. Continuous monitoring of the field performance is improved by introducing new technology and solutions, and acquiring surface and downhole data. At the well, scale, the information is obtained by wireline reported by Cantini et al. (2010)2, LWD, coring, and continuous acquisition of dynamic records of pressure, temperature, and fluid volumes. Storage performance optimization and future reservoir behaviour used updated numerical models.
Despite the documented presence of high biodiversity values, the preliminary baseline studies included in Environmental Impact Assessment studies (EIAs) in developing countries are often very generic, rely on limited primary data and do not include comprehensive biodiversity baseline surveys including habitat mapping and data on marine fauna aligned with the International Financial Institutions (IFIs) requirements. This becomes a critical issue for companies or financing institutions (IFIs) applying specific standards on biodiversity conservation and protection such as IFC PS6 and EBRD PR6, as well as other recognizes requirements, in the decision making process when studies are located within or in close proximity to legally protected areas, Important Bird Areas, Key Biodiversity Areas and, in general, areas of relevance from a biodiversity conservation perspective. This study presents the rationale and outcomes of a phased biodiversity study (Phased BIA) that has been developed to improve knowledge and fill initial gaps identified in the EIA study of an O&G development project in Egypt, Red Sea. The Phased BIA included: i) a desktop review of biodiversity baseline conditions with preliminary identification of existing habitats and presence of species; ii) a desktop biodiversity habitat mapping with identification of potential modified, natural and critical habitats; iii) the definition of specific coastal and marine biodiversity surveys within the Project area of influence; iv) a subsequent habitat mapping refinement exercise following "Ground-Truthing" techniques and drafting of habitat maps with the aim to provide a more robust and reliable impact assessment.
The first Italian LNG regasification plant was built and started operation near La Spezia in the 70s and in the last two decades the interest on the asset has significantly increased, with several big energy players presenting initiatives for LNG regasification plants along the Italian coast. Today's increasing need of diversification of energy sources and utilization of "clean fossil fuels" shifted the focus on small-scale plants for LNG. However, for a long time, the development of national regulation for such assets did not properly cover all of the plant's relevant aspects, making permitting path quite uncertain; only recently a few updates seems to have solved part of those issues. Notwithstanding what above, the permitting process is still something to be faced very carefully, because both the competent authorities and local communities can originate new showstoppers. RINA has quite a history in providing Environmental & Permitting services for LNG plants and is now working with increasing involvement in the small-scale business, supporting clients throughout the entire authorization process and during the whole life of the project. Lessons taught from previous projects lead us to focus the attention on the following aspects: site location, preferring brownfield underused areas to be converted for "cleaner" productive uses; identification of territorial constraints (land planning, natural protected areas, cultural goods, etc.); adequate baseline data collection, to assess the status of the environment prior the commencement of the work, and to identify potential sensitiveness; in depth impact assessment, crossing the project actions vs the environmental sensitiveness; identification of mitigation measures; definition of monitoring plan for construction and operation phases.
A huge amount of data is made available during well operations (surface and downhole logging data, lithological reports, drilling reports, equipment data,..). An integrated analysis of these multi source data provides highly valuable information for future wells engineering and planning in term of well problems investigation, performance enhancement and, ultimately, cost reduction by anticipating and reducing risks.
The use of a “big data” solution consolidating these multiple sources allows the creation of numerous analytics both on single well and group of offset wells. Particularly, the interpretation of surface logging data through the automatic recognition of operating sequences, when put together with other data sources including standard daily reports, provides a much higher granularity than traditional reporting.
Every operation is accurately measured through objective and detailed KPIs (ROP, tripping speed, weight to weight, connection time, etc.). Technical and performance issues are easily evaluated allowing a better understanding of their root causes, anticipating and avoiding the occurrence of these problems in the next wells and measuring activities and operations potential improvement. This process helps reducing drilling costs through entire well lifecycle:
The novelty of this approach is the combination of multiple data sources that provide unmatched analytics. In fact, these data are usually analysed on individual basis and limited to control in real time drilling operations. Therefore, the approach is creating value out of existing data, with limited resources.
This paper describes a methodology to automatically optimize the settings of the controllers of a plant. This approach is applied to a process dynamic simulation representing a real operated oil field. The controller parameters are tuned for specific process disturbance or setpoint change scenarios, with the aim of providing a faster control action and bring the plant back to normal operating conditions in the shortest possible time. The proposed method described in this paper uses a genetic algorithm to perform a plant-wide optimization of the PID controller parameters. The optimized parameters values, tuned with the algorithm, are particularly efficient in managing the process disturbances, upsets and setpoint changes scenarios. The controller parameters can be further optimized by including in the method other operating scenarios of interest and those critical for the considered plant simulation. The genetic algorithm, thanks to its better convergence rate with a high number of parameters and constraints compared to other optimization methods, allows to achieve an accurate tuning of the controllers of larger plant sections with a limited computing power. It should also be noted that the code structure of the method presented in this paper is easily modifiable, allowing the controller parameters optimization to be readily extended to other plant sections or even applied to completely different systems.