Weijermans, Peter-Jan (Neptune Energy Netherlands B.V.) | Huibregtse, Paul (Tellures Consult) | Arts, Rob (Neptune Energy Netherlands B.V.) | Benedictus, Tjirk (Neptune Energy Netherlands B.V.) | De Jong, Mat (Neptune Energy Netherlands B.V.) | Hazebelt, Wouter (Neptune Energy Netherlands B.V.) | Vernain-Perriot, Veronique (Neptune Energy Netherlands B.V.) | Van der Most, Michiel (Neptune Energy Netherlands B.V.)
The E17a-A gas field, located offshore The Netherlands in the Southern North Sea, started production in 2009 from Upper Carboniferous sandstones, initially from three wells. Since early production history of the field, the p/z plot extrapolation has consistently shown an apparent Gas Initially In Place (GIIP) which was more than 50% higher than the volumetric GIIP mapped. The origin of the pressure support (e.g. aquifer support, much higher GIIP than mapped) and overall behavior of the field were poorly understood.
An integrated modeling study was carried out to better understand the dynamics of this complex field, evaluate infill potential and optimize recovery. An initial history matching attempt with a simulation model based on a legacy static model highlighted the limitations of existing interpretations in terms of in-place volumes and connectivity. The structural interpretation of the field was revisited and a novel facies modeling methodology was developed. 3D training images, constructed from reservoir analogue and outcrop data integrated with deterministic reservoir body mapping, allowed successful application of Multi Point Statistics techniques to generate plausible reservoir body geometry, dimensions and connectivity.
Following a series of static-dynamic iterations, a satisfying history match was achieved which matches observed reservoir pressure data, flowing wellhead pressure data, water influx trends in the wells and RFT pressure profiles of two more recent production wells. The new facies modeling methodology, using outcrop analogue data as deterministic input, and a revised seismic interpretation were key improvements to the static model. Apart from resolving the magnitude of GIIP and aquifer pressure support, the reservoir characterization and simulation study provided valuable insights into the overall dynamics of the field – e.g. crossflows between compartments, water encroachment patterns and vertical communication. Based on the model a promising infill target was identified at an up-dip location in the west of the field which looked favorable in terms of increasing production and optimizing recovery. At the time of writing, the new well has just been drilled. Preliminary logging results of the well will be briefly discussed and compared to pre-drill predictions based on the results of the integrated reservoir characterization and simulation study.
The new facies modeling methodology presented is in principle applicable to a number of Carboniferous gas fields in the Southern North Sea. Application of this method can lead to improved understanding and optimized recovery. In addition, this case study demonstrates how truly integrated reservoir characterization and simulation can lead to a revision of an existing view of a field, improve understanding and unlock hidden potential.
The Vega subsea field in Norway has been producing successfully using a continuous Mono Ethylene Glycol (MEG) injection, topped up with corrosion inhibition means. A topside reclamation process allows reuse of MEG, however, limits the possibilities to produce saline water. In order to manage wells producing saline formation water and to increase ultimate recovery, a new flow assurance and integrity philosophy without continuous MEG injection is considered. This paper describes the options on hydrate as well as integrity management and the modifications both on the subsea and topside facilities required to enable an operational philosophy change. This change of the operational philosophy appears feasible, using either timely depressurization or Low Dosage Hydrate Inhibitors (LDHI) as well as a film building corrosion inhibitor in the system.
This paper presents a Digital Twin concept aimed at assets in the oil & gas and wind industry, that provides an accurate estimate of the true fatigue life of these assets in order to unlock potential fatigue life and ultimately extend the life of assets. This concept is divided in four tiers that allow to unlock remaining fatigue life one after the other. The first tier consists of using a high-resolution finite element model of the asset, delivered by Akselos unique RB-FEA technology. The subsequent tiers consist in using data from a few strategically placed accelerometers, as well as wave radar recordings, in order to calibrate the model and estimate the real loading on the asset. This concept delivers a true digital twin of the asset and offers a compelling and costeffective method for offshore assets that are facing life time extension beyond what current methodologies can provide. The concept is being implemented on one of Shell's platforms in the Southern North Sea.
Understanding petrophysical properties well enough to make drilling decisions, particularly for tight gas can be a challenge. A new computer system aims to help analyze the extensive data involved. There are more than 100 accumulations in the southern North Sea that are flagged as stranded fields. One of these stranded tight gas fields, the Kew field, has been developed successfully with the use of a subsea well, horizontal drilling, and hydraulic fracturing.
With the purchase, the growing, privately-held Chrysaor Holdings will expand its UK North Sea production to 185,000 BOE/D. The state-run offshore company has found a gas and condensate field that holds an estimated 250 million BOE. The latest example of the offshore sector's march toward automated wellbore construction will take shape later this year in the North Sea. Just 2 months after issuing more than a hundred licenses, the Oil and Gas Authority begins the process again for a whole new set of blocks. The company announced it would “initiate the process” of marketing its UK Central North Sea fields as part of a portfolio review.
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.
Copyright 2019 held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. ABSTRACT Today, many machine learning techniques are regularly employed in petrophysical modelling such as cluster analysis, neural networks, fuzzy logic, self-organising maps, genetic algorithm, principal component analysis etc. While each of these methods has its strengths and weaknesses, one of the challenges to most of the existing techniques is how to best handle the variety of dynamic ranges present in petrophysical input data. Mixing input data with logarithmic variation (such as resistivity) and linear variation (such as gamma ray) while effectively balancing the weight of each variable can be particularly difficult to manage. DTA is conceived based on extensive research conducted in the field of CFD (Computational Fluid Dynamics). This paper is focused on the application of DTA to petrophysics and its fundamental distinction from various other statistical methods adopted in the industry. Case studies are shown, predicting porosity and permeability for a variety of scenarios using the DTA method and other techniques. The results from the various methods are compared, and the robustness of DTA is illustrated. The example datasets are drawn from public databases within the Norwegian and Dutch sectors of the North Sea, and Western Australia, some of which have a rich set of input data including logs, core, and reservoir characterisation from which to build a model, while others have relatively sparse data available allowing for an analysis of the effectiveness of the method when both rich and poor training data are available. The paper concludes with recommendations on the best way to use DTA in real-time to predict porosity and permeability. INTRODUCTION The seismic shift in the data analytics landscape after the Macondo disaster has produced intensive focus on the accuracy and precision of prediction of pore pressure and petrophysical parameters.
The Slootdorp field has a complex structure with most reserves in Rotliegend sandstone, which is communicating with gas bearing Zechstein carbonates. The Rotliegend reservoir is bounded by a large fault, which might become seismogenic during depletion. A 3D geomechanical model was built, based on the faults and horizons in the geological model. Both the Rotliegend and Zechstein reservoirs were included in the model. The model was populated with geomechanical properties derived from logs, LOT's (leak off tests) and regional data on the stress field. Also, overburden properties from previous studies on nearby fields were used.
The pressure input was obtained from reservoir simulation. It is important to include the water leg pressure in the pressure input since the Rotliegend gas reservoir is in contact with an active aquifer. Pressure reduction drives the compaction of the reservoir, which induces stresses on the faults causing slippage. Since the water is quite incompressible, a large pressure reduction in the water leg may be caused temporarily by a rising gas water contact.
It turned out that slippage is not expected at the lowest gas pressure using a conservative estimate of the critical friction coefficient on the fault of 0.55. Sensitivity analysis on the most important input parameters was performed with a range that can be expected for such a field. The result was that the maximum critical stress ratio could range between 0.46 and 0.53 for the expected uncertainty of input parameters. The geomechanical modeling shows that an active aquifer has a dominant, mitigating effect on seismic risk, which can explain why many reservoirs show no seismicity in the Netherlands, although other effects could also play a role.
This course will discuss the practical state-of-the-art techniques of Volume to Value (VV) to help attendees assess exploratory deepwater offshore oil and gas prospects and quantify economic values of the prospects. Attendees will learn how to develop a preliminary field development plan for a given discovery prospect and estimate oil and gas recovery, wells required, and costs. They will also learn how to conduct economic evaluation for lease sales or farm-in opportunities. Upon completion of this course, attendees should be able to evaluate the commercial potential of original oil and gas in-place in exploratory blocks and develop preliminary field development plans. Attendees should also be able to obtain value of the opportunity in order to make the decision to go ahead and develop the field or walk away from it, as well as identify constraints in terms of geology and engineering that will make it viable or impede the realization of the project.