Gan, Thomas (Shell Trinidad & Tobago Ltd) | Kumar, Ashok (Shell Trinidad & Tobago Ltd) | Ehiwario, Michael (Shell Exploration & Production Company) | Zhang, Barry (Quantico Energy Solutions) | Sembroski, Charles (Quantico Energy Solutions) | de Jesus, Orlando (Quantico Energy Solutions) | Hoffmann, Olivier (Quantico Energy Solutions) | Metwally, Yasser (Quantico Energy Solutions)
Borehole-log data acquisition accounts for a significant proportion of exploration, appraisal and field development costs. As part of Shell technical competitive scoping, there is an ambition to increase formation evaluation value of information by leveraging drilling and mudlogging data, which traditionally often used in petrophysical or reservoir modelling workflow.
Often data acquisition and formation evaluation for the shallow hole sections (or overburden) are incomplete. Logging-while-drilling (LWD) and/or wireline log data coverage is restricted to mostly GR, RES and mud log information and the quality of the logs varied depending on the vendor companies or year of the acquisition. In addition, reservoir characterization logs typically covered only the final few thousand feet of the wellbore thus preventing a full quantitative petrophysical, geomechanical, geological correlation and geophysical modelling, which caused limited understanding of overburden sections in the drilled locations and geohazards risls assessment.
Use of neural networks (NN) to predict logs is a well-known in Petrophysic discipline and has often used technology since more than last 10 years. However, the NN model seldon utilized the drilling and mudlogging data (due to lack of calibration and inconsistency) and up until now the industry usually used to predict a synthetic log or fill gaps in a log. With the collaboration between Shell and Quantico, the project team develops a plug-in based on a novel artificial intelligence (AI) logs workflow using neural-network to generate synthetic/AI logs from offset wells logs data, drilling and mudlogging data. The AI logs workflow is trialled in Shell Trinidad & Tobago and Gulf of Mexicooffshore fields.
The results of this study indicate the neural network model provides data comparable to that from conventional logging tools over the study area. When comparing the resulting synthetic logs with measured logs, the range of variance is within the expected variance of repeat runs of a conventional logging tool. Cross plots of synthetic versus measured logs indicate a high density of points centralized about the one-to-one line, indicating a robust model with no systematic biases. The QLog approach provides several potential benefits. These include a common framework for producing DTC, DTS, NEU and RHOB logs in one pass from a standard set of drilling, LWD and survey parameters. Since this framework ties together drilling, formation evaluation and geophysical data, the artificial intelligence enhances and possibly enables other petrophysical/QI/rock property analysis that including seismic inversion, high resolution logs, log QC/editing, real-time LWD, drilling optimization and others.
This course discusses the fundamental sand control considerations involved in completing a well and introduces the various sand control techniques commonly used across the industry, including standalone screens, gravel packs, high rate water packs and frac-packs. It requires only a basic understanding of oilfield operations and is intended for drilling, completion and production personnel with some sand control experience who are looking to gain a better understanding of each technique’s advantages, limitations and application window for use in their upcoming completions.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders.
The large independent put together a team of data scientists, software developers, and petrotechnical staff to create a forward-looking vision for how to use digital technology to solve problems. Baker Hughes is still a GE company, but it has partnered with a second company for artificial intelligence expertise, C3.ai. The deal is expected to speed the integration of AI into oilfield operations by the company which also markets GE’s device analytics platform, Predix. Marathon Oil says its shale fields are producing more oil and gas with less hands-on work from company personnel thanks to a growing arsenal of digital technologies and workflows. Malaysia’s Petronas, Shell Malaysia, and Thailand’s PTTEP are now in the midst of full-scale digital adoption.
PETRONAS FLNG SATU (PFLNG1) is a floating liquefied natural gas facility producing 1.2 million tonnes per annum (mtpa) of LNG, on a facility that is 365m long, and 60m wide, making it among the largest offshore facility ever built. The PFLNG1 project is the first of its kind in the world and is the first deployment of PETRONASâ€™ Floating Liquefied Natural Gas (FLNG) technology, consolidating the traditional offshore to onshore LNG infrastructure into a single facility. This will see a giant floating facility capable of extracting, liquefying and storing LNG at sea, before it is exported to customers around the globe. The FLNG journey has come a long way since 2006, with many technological options explored to monetise and unlock the potential of small and stranded gas fields. Moving an LNG production to an offshore setting poses a demanding set of challenges â€“ as every element of a conventional LNG facility needs to fit into an area roughly one quarter the size in the open seas whilst maintaining safety and increased flexibility to LNG production and delivery. The keynote address describes the breakthrough features of PFLNG1 â€“ the worldâ€™s first floating LNG facility; and the pioneering innovation that it brings to the LNG industry.
Decisions in E&P ventures are affected by Bias, Blindness, and Illusions (BBI) which permeate our analyses, interpretations and decisions. This one-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact. Bias refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion. Blindness is the condition where we fail to see an unexpected event in plain sight. Illusions refer to misleading beliefs based on a false impression of reality.
The key technical considerations and decisions involved in selecting a progressing cavity pump(PCP) for a particular application include pump displacement, pressure capability, geometric design, elastomer type, and rotor coating characteristics. Other factors, such as local vendor choice and economics can also affect pump selection. Figure 1 provides a flow chart of the key decisions. When selecting a PC pump, the two most critical requirements are adequate displacement capacity and pressure capability to ensure that the pump can deliver the required fluid rate and net lift for the intended application. It is typical to select pumps with a design (i.e., theoretical) flow rate that is somewhat higher than the expected fluid rate to reflect pump inefficiencies during production operations.
Dutta, Sandipan (Cairn Oil & Gas, Vedanta Ltd.) | Kuila, Utpalendu (Cairn Oil & Gas, Vedanta Ltd.) | Naidu, Bodapati (Cairn Oil & Gas, Vedanta Ltd.) | Yadav, Raj (Cairn Oil & Gas, Vedanta Ltd.) | Dolson, John (DSP Geosciences and Associates LLC) | Mandal, Arpita (Cairn Oil & Gas, Vedanta Ltd.) | Dasgupta, Soumen (Cairn Oil & Gas, Vedanta Ltd.) | Mishra, Premanand (Cairn Oil & Gas, Vedanta Ltd.) | Mohapatra, Pinakadhar (Cairn Oil & Gas, Vedanta Ltd.)
The Eocene Lower Barmer Hill (LBH) Formation is the major regional source rock in the Barmer Basin rift, located in Rajasthan, India, and has substantial unconventional shale potential. The basin is almost completely covered with 3D seismic, providing an opportunity for more surgical mapping of the rapid structural and stratigraphic changes typical with any syn-rift deposit. Thick sections of organic-rich black shales reaching 400 meters thickness with TOC up to 14 wt. %, were deposited during a period of widespread basin deepening. Algal-rich type I oil prone kerogens dominate in north and generate oil, with very little gas. These shales mature at much lower temperatures than the mixed type I and III kerogens in the south, which also generate much larger amounts of gas and oil, and at higher threshold temperatures. The variable kinetics, as well as rapid facies variations typical of rifts, provide challenges to high-grading and testing unconventional shale plays.
Extensive Rock Eval pyrolysis and source rock kinetic databases were combined with petrophysical analysis to determine log-based porosity and saturations and productive potential. Modified Passey techniques calibrated to NMR log porosities provide estimates of organic richness as well as maturity and shale oil saturation. Basin modeling using Trinity software provides probabilistic ranges of generated and expelled hydrocarbons to determine storage capacity. The modeled oil window storage capacity varies between 6 to 13 MMBOE/km2, comparable to the values observed in Eagle Ford and Barnett Shale plays, but in a rifted basin and not broad cratonic shelf deposits.
Excess pore pressure was modeled using the kinetics of kerogen-to-oil conversion, and is noted in some of the deeper wells in tight sandstones, but not confirmed in the undrilled grabens. These pressure-gradient maps, along with oil properties (viscosity and oil mass fractions) derived from the geochemical model, are used to compute the producibility index. Composited storage capacity and producibility index maps have high-graded potential pilot areas.
In contrast to cratonic shale plays such as the Bakken or Eagle Ford, rapid and substantial facies variations occur due to local input of clastics and variable turbidite geometries which form potential targets for horizontal drilling. Increasingly more detailed paleogeographic maps are highlighting both the challenge and potential of the rich source rock in this basin.
This paper will cover how geochemical, structural, paleogeographic, petrophysical and other data are being used to derisk unconventional potential in this rich and complex rift system. Learnings from future testing of the Barmer Basin shale plays will be important to understand how to develop shale plays in other lacustrine rift basins.
The Jurassic age Hanifa and Tuwaiq Mountain Formations are regionally established source rocks that charged majority of the oil fields in the region. These formations are comprised of dark carbonate mudrocks with high organic richness and dominantly calcite mineralogy. Several studies were conducted regionally to evaluate the potential of these Jurassic intervals as an unconventional play.
In April 2018, The Kingdom of Bahrain announced the discovery of a major unconventional resource in Khalij Al Bahrain basin following the production of light oil from Tuwaiq Mountain Formation. These results confirmed the viability of the Jurassic source intervals as an Unconventional asset. However, the nature and the location of the resource present a number of operational challenges in a region where development of unconventional resources is at its infancy. This instigates the need to address and tackle these challenges through innovative approaches to enable the effective appraisal and subsequently development of the asset.
This publication introduces the emerging unconventional play in Khalij Al Bahrain basin and discusses the adopted strategies to appraise and develop the asset. The areas for optimization considered include well design, drilling and completion, facilities and shallow offshore/onshore logistics.
The Hanifa and Tuwaiq Mountain formations are Jurassic in age (Figure 1) and consist of a mixed section of dark organic rich limestone beds. These formations are regionally established as the principle source rock that charged majority of the overlying Jurassic reservoirs in the region, and in Bahrain, the cretaceous reservoirs as well. These source rocks are the main targets of the recently discovered Khalij Al Bahrain (KAB) basin in Bahrain with initial resource estimates indicating potentially up to 80 billion barrels of unconventional oil and 14 trillion cubic feet of gas in place.
Location and Geological Settings
KAB basin is located in the eastern part of the Arabian basin straddling the area towards the east of Saudi Arabia, west of Qatar Arch and south of the Zagros fold belts. Majority of the basin today falls within the land bound shallow waters around the main island of Bahrain. Major fields in the area include Awali, Dukhan and Abu Safah which are likely to have been sourced from these Jurassic source rocks (Figure 2). KAB basin also lies in close proximity to the Jafurah basin which is a significant Jurassic unconventional play in Saudi Arabia targeting the same formations .