The different mechanisms for the recovery of hydrocarbons from reservoirs has usually been divided into three types: primary, secondary and tertiary recovery mechanisms. Although this nomenclature suggests a chronological order among these stages, their application is subject to the specific characteristics of the reservoir and to the field production strategy. However, primary recovery is generally..
Recent developments in computational intelligence, particularly in machine learning, have strongly improved empirical modeling. The field which encompasses these new techniques and approaches is known as data-driven modeling. This is based on analyzing particular system data in order to find links between the system variables (input, internal and outputs) with no explicit knowledge of the..
By definition, a streamline is characterized as a line that is tangent to the local velocity field at all points at a given time. Applying it to the oil and gas context, a streamline is the path of fluid particles flowing from the injection well to the production well, representing a one-dimensional flow channel which..
The fluids in reservoir rocks are trapped within the pores of the rocks and will require sustained drive (i.e. energy) to be produced or flow out of the rocks. This energy is commonly referred to as natural or primary energy, which is a result of all the events that occurred during the reservoir formation process…
This is a new post of our series of publications regarding to Reservoir Engineering in Kraken’s blog. Here, one can expect a succinct discussion about Decline Curve Analysis (DCA) and its importance in forecasting production. Afterwards, the readers are encouraged to subscribe to have access to a more detailed technical contents within DCA practise. These..
Diamond Petroleum Services, also known as DPS, and Kraken have signed a distribution agreement enabling the British company to sell the powerful reservoir data management tool to its market. “Kraken offers our clients cost-effective, user-friendly and highly efficient tool that allow them to optimize their post-simulation workflow analysis to save time and minimize interpretation errors..
Reservoir simulation involves the mathematical manipulation of a significant amount of information, most of which is subject to uncertainties due to factors such as insufficient measurements, lack of accuracy and spatial heterogeneities, as previously discussed. Consequently, it is imperative to quantify the impact of these parameters’ variations on the simulation workflows (modeling, analysis and..
It is well known and documented that exploration of hydrocarbons is inherently a high-risk activity given a large number of uncertainties that may be present at any particular stage. The most common uncertainties are related to geological features such as structures, seals, and faults. On the other hand, economic analyses present uncertainties related to costs,..
In recent years, continuous improvements in computing and software technologies have considerably enhanced several aspects of reservoir simulation techniques. Simulation runtimes have sharply decreased due to advancements in hardware and processing power. In spite of this, the level of detail built into a geological model continues to exceed the current computational capabilities. Typical reservoir simulators..
The Reservoir Engineering has an extensive bibliography, including textbooks and published articles. As it comprises various themes of high complexity, it is always recommended searching for reliable references, most of the times provided by distinguished professionals in the oil industry. This post aims to indicate some of the best textbooks related to this area. Subjects..