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The single well chemical tracer (SWCT) test can be used to evaluate an Improved oil recovery (IOR) process quickly and inexpensively. The one-spot procedure takes advantage of the nondestructive nature of the SWCT method. The single-well (one-spot) pilot is carried out in three steps. First, Sor for the target interval is measured (see Residual oil evaluation using single well chemical tracer test. Then an appropriate volume of the IOR fluid is injected into the test interval and pushed away from the well with water.
Downhole magnetic surveys have been most commonly applied in highly magnetized igneous rocks, which have usually been studied within pure geoscience, especially beneath the ocean floor. These rocks preserve the direction of the Earth's field at the time of their formation (i.e., the prevailing magnetic field is "frozen" in the rocks as they solidify, giving them a strong natural remnant magnetization). A primary application has been to identify points in time at which the Earth's magnetic field has undergone a polarity reversal. These reversals have been dated globally (e.g., isotopically in the case of volcanic series or by correlation with biostratigraphy in the case of volcaniclastics) and have given rise to a geomagnetic polarity time scale (GPTS) that is based on laboratory measurements. This, in turn, has allowed dates to be assigned to a given magnetozone that is bounded by reversal phenomena.
Gravel packing consists of installing a downhole filter in the well to control the entry of formation material but allow the production of reservoir fluids. The gravel-packed completion is perhaps the most difficult and complex routine completion operation because it consists of many interrelated completion practices. There are two primary objectives for gravel packing a well. The crossover circulating technique is the most common method used to place the gravel around the screen. The gravel-pack equipment and service tools allow circulating the gravel down the work string above the packer and into the screen/casing annulus below the packer.
Physicists have been talking about the power of quantum computing for more than 30 years, but the questions have always been: Will it ever do something useful, and is it worth investing in? For such large-scale endeavors, it is good engineering practice to formulate decisive short-term goals that demonstrate whether the designs are going in the right direction. So, scientists at Google devised an experiment as an important milestone to help answer these questions. This experiment, referred to as a quantum supremacy experiment, provided direction for the team to overcome the many technical challenges inherent in quantum systems engineering to make a computer that is both programmable and powerful. To test the total system performance, a sensitive computational benchmark was selected that fails if just a single component of the computer is not good enough.
Nuclear magnetic resonance (NMR) has been, and continues to be, widely used in chemistry, physics, and biomedicine and, more recently, in clinical diagnosis for imaging the internal structure of the human body. The same physical principles involved in clinical imaging also apply to imaging any fluid-saturated porous media, including reservoir rocks. The petroleum industry quickly adapted this technology to petrophysical laboratory research and subsequently developed downhole logging tools for in-situ reservoir evaluation. NMR logging, a subcategory of electromagnetic logging, measures the induced magnet moment of hydrogen nuclei (protons) contained within the fluid-filled pore space of porous media (reservoir rocks). Unlike conventional logging measurements (e.g., acoustic, density, neutron, and resistivity), which respond to both the rock matrix and fluid properties and are strongly dependent on mineralogy, NMR-logging measurements respond to the presence of hydrogen protons.
An understanding of the geology of the reservoir is essential to its development, production, and management. This include both the external geology of the reservoir -- what created the hydrocarbon trap -- and the internal geology of the reservoir -- the nature of the rocks in which the hydrocarbons exist. This article focuses on what an engineer needs to know about the external and internal geology to understand the reservoir from which he or she is planning to produce hydrocarbons. The efficient extraction of oil and gas requires that the reservoir be visualized in 3D space. Engineers need a conceptual model of reservoirs. Conceptual models are an integral part of the decision-making process, whether that process involves selecting perforations or forecasting future production. However, most engineering measurements made on reservoirs have little or no spatial information. For example, a core measurement has no dimensional information, wireline logs and continuous core measurements are 1D, and production data and pressure information are volumetric but with unconstrained spatial information.
In a Culture Matters article (Oil and Gas Facilities, February 2012), psychologist Gary Klein explained how judgment in an emergency situation could be compromised by too much thought. He made the convincing case that in time-pressured situations, such as responding to a gas leak in a transport vessel, swift intuitive judgment that operates by an unconscious pattern matching may be better left unfettered by conscious deliberation, which operates by rules and regulations. We present the counterpoint--a different view of intuition that is supported by considerable research. In particular, we argue that most failures of judgment in upstream oil and gas planning result from too little deliberation and too much acceptance of swift intuitive solutions. Our more pessimistic view of human judgment, known in psychology as the heuristics and biases (H&B) approach, seems to match some important perspectives within the oil and gas industry. Reports from the Independent Project Analysis database indicate that 1 in 8 major projects are a planning disaster.
It happens many times in the oil industry. It may even have happened to you. Someone from R&D has just finished an oral report to management about an exciting, important project. But the managers don't appear to grasp the importance or understand the concept presented. The result is no managerial enthusiasm with little or no support.
Summary The use of recorded downhole rotational speed measurements with a bandwidth up to 9 Hz gives new insights into the conditions under which stick-slip torsional oscillations occur. Observations made while drilling two reservoir sections have shown that, out of all the stick-slip situations identified, 72% of them for one well and 64% for the other well occurred in off-bottom conditions. In these off-bottom conditions, stick-slip was systematically observed while starting the topdrive (TD) until a sufficiently high TD rotational velocity was requested. For these two sections, off-bottomstick-slip was either related to using TD speeds below 120 rev/min or to reaming down during reciprocation procedures. In on-bottom conditions, stick-slip events occurred predominantly when the TD speed was less than 120 rev/min (53 and 32% of the on-bottom cases) but also in association with downlinking to the rotary steerable system (RSS) (23 and 46% of the on-bottom cases), and this, even though the TD speed was larger than 120 rev/min. These on-bottomstick-slip situations did not necessarily occur at a very high weight on bit (WOB) because 98% of them for one well and 46% for the other well took place when the WOB was lower than 10 ton. Downhole measurements have shown that when the drillstring is subject to strong stick-slip conditions, the downhole rotational speed changes from stationary to more than 300 rev/min in just a fraction of a second. Direct observations of downhole rotational speed at high frequency help in discovering conditions that were not suspected to lead to large torsional oscillations. This new information can be used to improve drilling operational procedures and models of the drilling process, therefore enabling increased drilling efficiency.
In well-drilling activities, successful execution of a sequence of operations defined in a well project is critical. To provide proper monitoring, operations executed during drilling procedures are reported in daily drilling reports (DDRs). The complete paper provides an approach using machine-learning and sequence-mining algorithms for predicting and classifying the next operation based on textual descriptions. The general goal is to exploit the rich source of information represented by the DDRs to derive methodologies and tools capable of performing automatic data-analysis procedures and assisting human operators in time-consuming tasks. This is a library discussed in the literature designed to learn word embeddings and text classification.