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This paper highlights a systematic and robust computer assisted reservoir simulation workflow to place oil producers and water injectors in the optimum areas of hydrocarbon reservoirs. The workflow offers modeling of several types of well pattern designs, including five-spot, fork-type, line-drive, and peripheral injection, allowing the multidisciplinary subsurface team to evaluate several development plans very efficiently. The workflow relies on automating the process of well placement across areas of interest with integration of static geological and dynamic simulation models. Opportunities within the reservoir are targeted using different well types, including vertical, horizontal, and multilaterals. This process incorporates different elements of well pattern designs, including well spacing, lateral length, azimuth, dogleg severity (DLS), and completions. For example, star-shaped offshore platforms with multiple wells are placed parallel to structure contours of the reservoir honoring oil-water contact (OWC) and gas-oil contact (GOC). Multiple zone lateral placement is achieved by positioning each lateral in targeted reservoir layers. This workflow was evaluated on a conceptual tight heterogeneous reservoir with several development strategies, including star-shaped platforms with peripheral water injection. Each platform consisted of several dual and trilaterals targeting different horizons of the reservoir. The development plans were evaluated through numerical simulation and well performance was analyzed. The analysis indicated considerable improvement in field cumulative oil production and ultimate recovery. Different field development plans (FDPs) are generated in a few minutes instead of months when using traditional workflows. Overall, a 90% reduction in time has been observed in this work. The significance of this workflow increases when preparing FDPs for geologically heterogeneous reservoirs with complex well designs and challenging operational constraints. The results achieved using this workflow demonstrate a unique opportunity in creating a variety of well designs automatically to target huge and complex reservoirs under a secondary drive production mechanism. This workflow is not only valuable in early phase field development planning, but also applicable in designing multiple sidetracks and reentry wells as part of the infill drilling program in mature fields.
Lee, Taeyeob (Korea Gas Corporation) | Jeong, Daein (Schlumberger Information Solutions) | Jang, Sangyup (Korea Gas Corporation) | Kim, Junggyun (Korea Gas Corporation) | Mo, Cheolhoon (Korea Gas Corporation) | Jeong, Hoonyoung (Seoul National University) | Choe, Jonggeun (Seoul National University)
Abstract Determining optimal infill well placements is a complex problem that depends on reservoir properties and specifications of well and surface network. A numerical simulation is often the most appropriate method to evaluate the feasibility of the candidates. An integrated asset model of A field in the Middle East is built that couples a subsurface reservoir model with a surface network model. The integrated asset model is used to find optimal locations of 10 infill wells which are scheduled to drill in the future. This paper proposes a step-wised approach for finding multiple infill well locations considering constraints of surface network. Firstly, an optimization process is conducted for all infill wells using an evolution strategy. Next, the same process is repeated exclusive of some wells, whose locations are already determined from the 1 optimization. This step improves an efficiency of the optimization and therefore, gives increased cumulative oil production results. Finally, integrated asset models are constructed for the 5 best cases, and elevation profiles of flowlines and trunklines are extracted from a geographic information system (GIS) at this time. The optimal well locations are quite far from previous producing wells. It is good for avoiding production interferences, although these locations have negative impacts on delivering produced fluid to a facility because of pressure losses. The integrated asset model could evaluate several effects simultaneously and could give practical infill well locations for the target field.
Voevodkin, V. L. (LUKOIL-Engineering LLC) | Lyadova, N. A. (PermNIPIneft Branch of LUKOIL Engineering LLC in Perm) | Raspopov, A. V. (PermNIPIneft Branch of LUKOIL Engineering LLC in Perm) | Baryakh, V. A. (PermNIPIneft Branch of LUKOIL Engineering LLC in Perm) | Minin, A. Yu. (PermNIPIneft Branch of LUKOIL Engineering LLC in Perm)
The PDF file of this paper is in Russian.
Perm region has its long-time oil production history. Nowadays significant part (61%) of residual oil here is associated with low-productive carbonate formations. Horizontal well drilling is one of the main ways to achieve commercial success in these geological conditions. Widely spread lateral drilling has high demand on well placement service to maintain horizontal sections within the reservoir. Well placement is the process of interactive positioning of a wellbore based on real-time geological data and technological measurements. In general, horizontal drilling in Perm region is focused on three carbonate formations: Upper Devonian - Tournaisian, Upper Visean - Bashkirian and Kashirian - Werenian. The article describes different well drilling approaches depending on each formation’s own features. At present time, lateral drilling in Perm Region is supported by geosteering service based on real-time LWD data. Paper describes LWD methods and well placement approaches which are used in Perm region. Geosteering is a proven technology that allows increasing of effective lateral length of the well despite downward geological environment: net pay decrease, high heterogeneity etc. More than 40% of annual production rate (from new wells) is based on horizontal wells landed with well placement service. Horizontal well placement brought the opportunity of profitable production for fields with complicated geology which weren’t consider earlier as a target for lateral drilling because of high failure probability.
Пермский край относится к старым нефтедобывающим районам. Значительная доля (61 %) остаточных извлекаемых запасов приурочена к объектам с карбонатным типом коллектора, которые характеризуются пониженной продуктивностью. Бурение горизонтальных скважин – это один из основных способов обеспечений рентабельной разработки таких объектов. Широкое распространение практики бурения скважин с горизонтальным окончанием предъявляет особые требования к применяемым технологиям, обусловливает необходимость повышения эффективности их проводки по пласту. В Пермском крае бурение горизонтальных скважин в трех основных карбонатных нефтегазоносных комплексах: верхнедевонско-турнейском, верхневизейско-башкирском и каширо-верейском. Каждый комплекс характеризуется своими особенностями геологического строения и связанными с ним различиями в стратегии проводки горизонтальных стволов. В статье дано описание типовых подходов к проводке скважин в различных геологических условиях. В настоящее время бурение всех горизонтальных скважин осуществляется с контролем проводки на основании геолого-геофизической информации LWD, поступающей с буровой в режиме реального времени с использованием средств геонавигации. Рассмотрены методы применяемых в процессе бурения исследований, а также используемые методики геонавигации и их особенности. Применение геонавигации позволяет обеспечивать рост показателей эффективной проходки горизонтальных участков стволов, несмотря на ухудшение геологических условий бурения: уменьшение эффективных толщин, рост расчлененности и др. Ввод в эксплуатацию горизонтальных скважин, пробуренных с применением геологического сопровождения, обеспечивает значительную долю (более 40 %) годовой добычи из новых скважин. Бурение горизонтальных скважин с геонавигацией позволяет вовлекать в рентабельную разработку объекты со сложным геологическим строением. Ранее эксплуатация таких объектов горизонтальными скважинами не рассматривалось по причине значительных рисков.
Lin, Lihwa (US Army Engineer Research and Development Center) | Li, Honghai (US Army Engineer Research and Development Center) | Brown, Mitchell E. (US Army Engineer Research and Development Center) | Andes, Lisa C. (US Army Corps of Engineers) | Wu, Frank (US Army Corps of Engineers)
This paper describes the numerical modeling of nearshore placement of dredged material at Noyo Harbor, CA. The numerical models include the US Army Corps of Engineers (USACE) Short-Term FATE model (STFATE), Coastal Modeling System (CMS), and Particle Tracking Model (PTM). The STFATE simulates the spatial distribution of dredged material in open water after it has passed through the water column on release of the barge load. The CMS calculates wave transformation, flow circulation, water levels, sediment transport, and morphology change. The modeling provides technical information necessary to evaluate a location site that is economically feasible for the optimum sediment placement. The model simulation showed small onshore sediment transport in typical summer and winter months. The calculated fine sediment transport during the dredged material release at the placement site indicated more longshore movement as the result of strong wind driven current along the coast.
Latest technological developments and applications made optimal control methods usage in optimal well placement in intelligent fields practical and beneficial to increase the production. Effective usage of these methods strongly depends on the detailed evaluation of the economic view and performance in reservoirs that have high uncertainty, particularly. There are several methods of optimization of well placement ranging from classical reservoir engineering to derivative-free and hybrid methods.
TNO's Olympus model used globally as a benchmark model in ISAAP-2 Challenge in used. Geological modeling software is coupled with the commercial full-physics reservoir simulator as well as the optimization software in order to produce different geological realizations to represent the geological uncertainty and run the simulation model with differing inputs of optimization and uncertainty in a loop. Results are outlined in detail in a comparative way including comparison to the previous study to illustrate the challenges and benefits of smart wells and optimization of placement of them in intelligent fields.
Results indicate that classical reservoir engineering principles still prove useful in the beginning of the optimization process. Then, derivative-free and hybrid methods introduce significant improvement on economics. There are certain challenges in CPU requirements however the state-of-the-art facilities provided significant reduction in runtimes along with the help of the hybrid methods where proxies are built and used for faster runtimes. Despite higher initial capital expenses, smart wells provide significant advantages in recovery and economics compared to that of the conventional wells where these is less control on the production/injection at the layer level. Literature lacks a comprehensive study that takes into account the optimization of well placement in smart fields focusing on smart wells and the all major available methods for optimization. This study closes that gap providing a strong reference building on top of the previous study extending it to intelligent fields which are becoming very common and useful in oil and gas industry in conventional and unconventional applications.