Below is a list of basins and fields; however this is a short list since there are more than 65,000 oil and gas basins and fields of all sizes in the world. However, 94% of known oil fields is concentrated in fewer than 1500 giant and major fields. Most of the world's largest oilfields are located in the Middle East, but there are also supergiant ( 10 billion bbls) oilfields in India, Brazil, Mexico, Venezuela, Kazakhstan, and Russia. Add any basins or fields that are missing from this list!
To estimate Rt under a variety of different logging conditions and in different formations, a simple three-parameter, step-profile invasion model is often used. This model consists of a flushed zone of resistivity Rxo and a sharp boundary at diameter di, with the uninvaded zone of resistivity Rt. Three independent, borehole-corrected resistivity measurements with appropriately chosen depths of investigation contain enough information from the formation to reliably solve for Rt using this model. Measurements with the following features should be chosen: small, correctable borehole effects; similar vertical resolutions; and well-distributed radial depths of investigation--one reading as deep as practical, one very shallow reading, and one intermediate reading. In conductive muds, the Dual Laterolog (DLL) Resistivity– Rxo combination tool provides simultaneous measurements suitable for evaluating Rt, Rxo, and di. It should be said that the value of Rt in a given bed is an interpreted parameter, and is almost never measured.
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.
Gaol, Calvin (Clausthal University of Technology) | Wegner, Jonas (Clausthal University of Technology) | Ganzer, Leonhard (Clausthal University of Technology) | Dopffel, Nicole (BASF SE) | Koegler, Felix (Wintershall Holding GmbH) | Borovina, Ante (Wintershall Holding GmbH) | Alkan, Hakan (Wintershall Holding GmbH)
Utilisation of microorganisms as an enhanced oil recovery (EOR) method has attracted much attention in recent years because it is a low-cost and environmentally friendly technology. However, the pore-scale mechanisms involved in MEOR that contribute to an additional oil recovery are not fully understood so far. This work aims to investigate the MEOR mechanisms using microfluidic technology, among others bioplugging and changes in fluid mobilities. Further, the contribution of these mechanisms to additional oil recovery was quantified.
A novel experimental setup that enables investigation of MEOR in micromodels under elevated pressure, reservoir temperature and anaerobic and sterile conditions was developed. Initially, single-phase experiments were performed with fluids from a German high-salinity oil field selected for a potential MEOR application: Brine containing bacteria and nutrients was injected into the micromodel. During ten days of static incubation, bacterial cells and in-situ gas production were visualised and quantified by using an image processing algorithm. After that, injection of tracer particles and particle image velocimetry were performed to evaluate flow diversion in the micromodel due to bioplugging. Differential and absolute pressures were measured throughout the experiments. Further, two-phase flooding experiments were performed in oil wet and water wet micromodels to investigate the effect of in-situ microbial growth on oil recovery.
In-situ bacteria growth was observed in the micromodel for both single and two-phase flooding experiments. During the injection, cells were partly transported through the micromodel but also remained attached to the model surface. The increase in differential pressure confirmed these microscopic observations of bioplugging. Also, the resulting permeability reduction factor correlated with calculations based on the Kozeny-Carman approach using the total number of bacteria attached. The flow diversion of the tracer particles and the differences in velocity field also confirmed that bioplugging occurred in the micromodel may lead to an improved conformance control. Oil viscosity reduction due to gas dissolution as well as changes in the wettability were also identified to contribute on the incremental oil. Two-phase flow experiments in a newly designed heterogeneous micromodel showed a significant effect of bioplugging and improved the macroscopic conformance of oil displacement process.
This work gives new insights into the pore-scale mechanisms of MEOR processes in porous media. The new experimental microfluidic setup enables the investigation of these mechanisms under defined reservoir conditions, i.e., elevated pressure, reservoir temperature and anaerobic conditions.
EBN is the Dutch state energy company that is a large non-operating partner of over 10 different operators that produce from more than 200 on- and offshore assets with more than 850 projects defined on them. Estimating budget production, medium and long-term forecasts and its associated operating and capital expenditures are of vital importance to EBN. Larger companies with many assets and even more projects, at varying degree of maturity, have great difficulty to reliably predict an aggregated forecast.
Historically, EBN would copy and risk operator data, which led to continuous overestimation of both budget production and longterm forecasts. A straightforward correction method was developed; that consists of two parts: firstly, the budget production is set for all producing assets and projects by assessing technical, subsurface, infrastructural and human factors on the operator's fields and projects performance. Secondly, the medium and longterm forecast is delayed with 1 to 4 years for respective SPE PRMS resource classes "justified for development" to "project unviable" and the associated project forecasts are risked with a chance of development according to their subclasses of the contingent resource classes.
Data analytics on almost 10 years of reserve reporting according to SPE PRMS standards led to a straightforward solution to reduce short and medium-term forecasting error. The short-term absolute average error used to be 8%. Through the implementation of the new method, 7 years ago, the absolute average short-term forecasting error dropped to 4%. The long-term aggregated forecast, obtained by simply copying the operator data, resulted in an overestimation of up to 50% 5 years ahead. The overestimation was reduced to an absolute average error of 23% by an earlier correction method, which only used risking factors on contingent projects, but no time delay. This paper presents a new method, that uses both risking factors and time delays on the realization of projects. The method reduced the error in the long-term forecast to an uncertainty band of a few percent.
Various causes for the overestimation were identified. The budget production errors were primarily attributed to wrong uptime predictions. Longterm forecast errors are impacted by the overestimation of the number of executed projects, while the timing and performance of new projects affects both the short and middle term forecasts.
The solution presented is the first methodology for EBN that is able to predict aggregated forecasts of hundreds of projects of several operators with an accuracy within a 5% margin over a lengthy period. The described risking factors described, and delay times, are dependent on the portfolio maturity and investment climate. Historic data has to be utilized to determine these factors for your portfolio.
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.
Concentrations of carbon dioxide in the atmosphere surged at a record-breaking speed in 2016 to the highest level in 800,000 years, according to the World Meteorological Organization's Greenhouse Gas Bulletin. The abrupt changes in the atmosphere witnessed in the past 70 years are without precedent. The Netherlands will reduce production of its Groningen gas field by 10% from October to limit the risk of earthquakes, the country’s economy minister said in a letter to parliament on 18 April.
The Netherlands will reduce production of its Groningen gas field by 10% from October to limit the risk of earthquakes, the country’s economy minister said in a letter to parliament on 18 April. The Pawnee Nation filed a lawsuit on 3 March in tribal court in Oklahoma against 27 oil and gas producers, seeking damages for an earthquake they said was caused from man-made activity related to hydraulic fracturing.
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.