As a young female student in year 10 in high school, I had no idea what to pursue as a career after graduating. However, one day in our science class we heard a guest speaker talk about the oil and gas industry. I was immediately fascinated by the story and decided that this was the place to be. Two years later, I found myself at the University of Western Australia (UWA) studying engineering and pursuing a career in the oil and gas industry. I had found my path.
Devon Energy and its debt gets smaller, as Canadian Natural Resources adds to its huge, long-term bet on Canadian heavy and ultra-heavy crude. The recent production freefall could accelerate even further as US sanctions-related deadlines pass, the US Energy Information Administration said. The authors of this paper propose a novel work flow for the problem of building intelligent data analytics in heavy-oil fields. This paper presents the data collected by an ultrasound downhole scanner, demonstrating a novel method for diagnosing multilateral wells. Against the background of a low-oil-price environment, a redevelopment project was launched to give a second life to a shallow, depleted, mature offshore Congo oil field with viscous oil (22 °API) in a cost‑effective manner.
An appraisal program involving the Bentley field located on the UK continental shelf has addressed the key technical concerns associated with developing viscous crude in an offshore environment. The number of aging offshore facilities in the Asia Pacific region is increasing. The decision to extend the service life of an offshore asset is made on the basis of detailed technical analyses combined with detailed economical evaluations.
Shale gas is becoming increasingly important globally. The nature of these reservoirs pose special considerations in reserves estimation. What follows was written in 2001 and needs to be updated based on current experience. Nonetheless, some of the considerations mentioned remain appropriate. As reported in mid-2000, natural gas produced from shale in the US has grown to be approximately 1.6% (0.3 Tcf annually) of total gas production.
Case studies can be instructive in the evaluation of other coalbed methane (CBM) development opportunities. The San Juan basin, located in New Mexico and Colorado in the southwestern U.S. (Figure 1), is the most prolific CBM basin in the world. It produces more than 2.5 Bscf/D from coals of the Cretaceous Fruitland formation, which is estimated to contain 43 to 49 Tscf of CBM in place. For a long time, the Fruitland formation coals were recognized only as a source of gas for adjacent sandstones. In the 1970s, after years of encountering gas kicks in these coals, operators recognized that the coal seams themselves were capable of commercial gas rates. CBM development benefited greatly from drilling and log data compiled from previous wells targeting the deeper sandstones and an extensive pipeline infrastructure that was built to transport conventional gas. These components, along with a U.S. federal tax credit and the development of new technologies such as openhole-cavity completions, fueled a drilling boom that resulted in more than 3,000 producing CBM wells by the end of 1992. The thickest Fruitland coals occur in a northwest/southeast trending belt located in the northeastern third of the basin. Total coal thickness in this belt locally exceeds 100 ft and individual coal seams can be more than 30 ft thick. The coals originated in peat swamps located landward (southwest) of northwest/southeast trending shoreline sandstones of the underlying Pictured Cliffs formation. The location of the thickest coals (Figure 1) coincides with the occurrence of overpressuring, high gas content, high coal rank, and high permeabilities in the San Juan fairway ("fairway"). The overpressuring is artesian in origin and is caused by water recharge of the coals through outcrops along the northern margin of the basin. This generates high vertical pressure gradients, ranging from 0.44 to 0.63 psi/ft, which allow a large amount of gas to be sorbed to the coal. Coal gas in the San Juan basin can contain up to 9.4% CO2 and 13.5% C2 . Chemical analyses suggest that thermogenic gases have been augmented by migrated thermogenic and secondary biogenic gas sources, resulting in gas contents ranging up to 700 ft 3 /ton. Coal rank in the fairway ranges from medium- to low-volatile bituminous and roughly coincides with those portions of the basin that were most deeply buried. Coals in the fairway typically have low ash and high vitrinite contents, resulting in large gas storage capacities and excellent permeabilities of 10 md from well-developed cleat systems.
Chin, Adam (NCS Multistage) | Staruiala, Adam (NCS Multistage) | Behmanesh, Hamid (NCS Multistage) | Anderson, David (NCS Multistage) | Alonzo, Christopher (NCS Multistage) | Jones, David (Chesapeake Energy) | Barraza, Saul Rivera (Chesapeake Energy) | Lasecki, Leo (Chesapeake Energy) | McBride, Kyle (Chesapeake Energy)
As most of the major unconventional plays in North America are well into the development phase, optimizing infill development is a central focus for most operators. There are numerous case studies where operators have invested in several different technologies (micro-seismic, tracers, fiber optics, interference tests, etc.) to try and better understand and optimize child well performance (Jaripatke et al. 2018, Kumar et al. 2018, Manchanda et al. 2018). These case studies have revealed many phenomena which can impact infill performance including depletion, asymmetric fracture growth, and geo-mechanical effects. These factors frequently lead to less productive infill wells. It is not uncommon for child wells to under-perform their type well, which is often generated based on parent performance, and potentially scaled up to account for modern completion design. This is a major issue for operators when it comes to booking reserves and allocating capital to the most economic projects. In order to help address this issue, this paper proposes an analytical workflow designed to account for the adverse impacts that depletion and geo-mechanical effects may have on a child well, generating probabilistic forecasts that accurately predict a range of outcomes that the child well is capable of.
The physics that govern the interactions between parent and child wells are very complex. Attempting to model these physics by integrating a geo-model, hydraulic fracture modeling, geo-mechanics and reservoir simulation is a massive time investment and requires a high degree of technical expertise in several domains. Furthermore, each of these exercises comes with a set of assumptions, the impacts of which can be compounded upon integration. The focus of this paper is to present a practical workflow that can be used to predict child well performance. This workflow has been applied to a set of wells in the Marcellus. The first iteration of the workflow accounted for the effects of pressure depletion on initial reservoir pressure determination, however it over-predicted the infill type curve. This led to a second iteration of the workflow which incorporated the impact of geo-mechanical effects on the cluster efficiency of the child well. This refined workflow was validated using several parent-child datasets from the study area, as well as additional data from surrounding areas. This workflow incorporates empirical field data to tune certain inputs, making it adaptable to different formations.
High-resolution discretizations can be advantageous in compositional simulation to reduce excessive numerical diffusion that tends to mask shocks and fingering effects. In this work, we outline a fully implicit, dynamic, multilevel, high-resolution simulator for compositional problems on unstructured polyhedral grids. We rely on four ingredients: (i) sequential splitting of the full problem into a pressure and a transport problem, (ii) ordering of grid cells based on intercell fluxes to localize the nonlinear transport solves, (iii) higher-order discontinuous Galerkin (dG) spatial discretization with order adaptivity for the component transport, and (iv) a dynamic coarsening and refinement procedure. For purely cocurrent flow, and in the absence of capillary forces, the nonlinear transport system can be perturbed to a lower block-triangular form. With counter-current flow caused by gravity or capillary forces, the nonlinear system of discrete transport equations will contain larger blocks of mutually dependent cells on the diagonal. In either case, the transport subproblem can be solved efficiently cell-by-cell or block-by-block because of the natural localization in the dG scheme. In addition, we discuss how adaptive grid and order refinement can effectively improve accuracy. We demonstrate the applicability of the proposed solver through a number of examples, ranging from simple conceptual problems with PEBI grids in two dimensions, to realistic reservoir models in three dimensions. We compare our new solver to the standard upstream-mobility-weighting scheme and to a second-order WENO scheme.
Lu, Mingjing (China University of Petroleum, Colorado School of Mines) | Su, Yuliang (China University of Petroleum) | Wang, Wendong (China University of Petroleum) | Zhang, Ge (Xianhe Oil producing Plant, Shengli Oilfield, Sinopec)
Refracturing treatment are performed since stimulation effect won't last for entire life. Screening wells for refracturing needs a systematic analysis of huge amounts of data. With literature review, it is obviously that there are many factors controlling the success of refracturing and factors may vary in different oilfields. Proper factors and data processing are the primary principle in candidate selection. The Integrated Multiple Parameters (IMP) method is presented to provide assists in selecting candidate wells.
After deeply researching over 200 restimulated wells, all factors thought to be related with success of refracturing are listed and analyzed, results show that single factor may have great influence on restimulation but no significant patterns can be obtained since too many factors making things complicated. The IMP method proposes five parameters which are all integrated by those single factors. It is emphasized that all parameters have physical or engineering meanings which makes it easier to quantify their correlation in refracturing. Besides, all the parameters are dimensionless which makes it easier for using in mathematical models and statistical analysis.
The five dimensionless parameters are developed considering the most important aspects of candidate wells selection which are showed as followed: fracture reorientation, well completion, reservoir depletion, production decline, oil-water well connectivity. Parameters are calculated for all the restimulated wells to dig into their correlation with the outcomes of refracturing. A simple decision model is built to help with screening wells for refracturing. Results shows that it is more executable to evaluate and predict the success of refracturing with these dimensionless parameters. Fracture reorientation parameter is the primary one to be considered since it leads to fracture reorientation which brings significant production increment. Then two types of potential wells are picked: (a) wells with dissatisfied initial well completion, low production decline rate and high oil-water connectivity parameter; (b) wells with satisfied initial well completion, high well completion parameter, low production decline parameter, reservoir depletion parameter and low oil-water connectivity parameter for wells that are not easy for fracture reorientation. Wells selected are proved to be refracturing potential which verify the reliability and accuracy of IMP method.
The IMP method is an improved approach integrating most of the important factors which makes candidate selection much more predictable and it succeeds in screening out more than 80% of the potential wells in field test. Also, it can be applied widely in different oilfields since all the parameters are dimensionless. By combining with some mathematical methods such as neural networks, it can even predict increment of the restimulation treatment.
Asset-intensive companies face tighter maintenance budgets, stricter regulations and increased pressure to improve asset performance, whilst confronted with aging assets and workforce. Managing an asset with these challenges requires informed decision-making based on insight, knowledge and forecasting. Data is a powerful tool to achieve this goal. 'Internet of things' innovations have led to a rapid increase in the availability of technical and business data. A few years ago, techniques that were complex and expensive are now more affordable, accessible and increasingly important in order to compete in this world of rapid change. Field data is faster and immediately available for processing, while more relevant measurements and observations of similar or better quality are leading to more reliable information for decision-making. The transition from data to information has been made possible through development in the usability of applications in the field of data science, and more advanced software and information systems are on the market for data analysis, diagnostics and simulation.