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.
This paper uses a simulation model to evaluate and compare the thermal efficiency of five different completion design cases during the SAGD circulation phase in the Lloydminster formation in the Lindbergh area in Alberta, Canada. The cost reduction per barrel of oil produced and the extension of sustainable production life by optimization have been two major areas of focus, but the investments in new technologies and recovery-improvement research have not received sufficient attention during the downturn. This paper covers the staged field-development methodology, including analysis and evaluation of various development concepts, that enabled the company to optimize both completion design and artificial-lift selection, reducing downtime and lowering operating costs by nearly 50%. This paper shares experience gained in the Ashalchinskoye heavy-oil field with a two-wellhead SAGD modification. As a result of a pilot for this technology in Russia, the accumulated production of three pairs of these wells is greater than 200,000 tons.
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.
Today many exploration, appraisal and development welltest operations are performed in new frontiers. These include extreme environmental conditions and reservoirs bearing complex reservoir fluids, such as heavy oil, or fluids with a high concentration of H2S, CO2, high wax and asphaltenes content, which have rarely been tested in the past. Many failures and operational issues have hindered the interpretability of data, significantly increased the total costs of such well tests or led to severe HSE incidents.
Currently, such operations are often designed and executed on a case-by-case basis, and there are no practical recommendations available that would summarise the well testing experience in such environments to guide the operating companies through the process of efficiently planning welltest operations. Consequently, operations are often planned on a "copy-paste" basis, with potentially disastrous consequences.
This paper describes in detail the challenges associated with safety, flow assurance, safe handling and disposal of produced fluids, and data quality during current welltest operations with complex reservoir fluids or challenging environmental conditions. Complex reservoir fluids, including highly corrosive fluids, introduce unique challenges that need to be addressed at the design stage of the test, each requiring an appropriate design of surface well test spread and DST string, as well as the overall job operation and equipment planning to incorporate "what-if" scenarios. To address these issues, we summarize the best well-testing practices, and for each of the cases outlined illustrate proven welltesting techniques. Examples show that it is nearly impossible to perform the well test and handle complex reservoir fluids at surface using a traditional approach and standard well test equipment. Novel well testing equipment such as new generation welltest separators equipped with Coriolis mass flow meters, new generation burners and others, in combination with recently developed well testing techniques, allowed us to overcome these challenges.
The paper provides practical recommendations, supported by case studies, highlighting the results and lessons learned from successful operations around the worlds in the following well test areas: Heavy oil testing Well test operations in high H2S and CO2 environment Well test operations in reservoir fluids with high wax or Asphaltene content Deepwater welltest operations with a high risk of hydrate formation Well test operations with production of foamy oil Heat management Viscous fluid management Contingency planning
Heavy oil testing
Well test operations in high H2S and CO2 environment
Well test operations in reservoir fluids with high wax or Asphaltene content
Deepwater welltest operations with a high risk of hydrate formation
Well test operations with production of foamy oil
Viscous fluid management
Recipes for success are provided to ensure that safe operation can be performed in the challenging environment while keeping the cost in line with the AFEs.
Amsidom, Amirul Adha (PETRONAS) | Ghonim, Elsayed Ouda (PETRONAS) | Alexander, Euan (PETRONAS) | Kuswanto, Kuswanto (PETRONAS) | Abdullaev, Bakhtiyor (PETRONAS) | Hassan, Hani Sufia (PETRONAS) | Ishak, M Faizatulizudin (PETRONAS) | Rajah, Benny (PETRONAS) | Gunasegaran, Puvethra Nair (PETRONAS) | Ayad, Kamal (Cornerstone for Business Development) | Madon, Bahrom (PETRONAS) | Hamzah, M Amir Shah (PETRONAS) | Zamanuri, Kautsar (PETRONAS)
About 80% of brownfields in Malaysia use Gas Lift as the artificial lift method. Though it is widely used, the operators are facing numerous challenges which include shortages in gas lift source and compressor reliability issues. Consequently fields’ productivity is impacted and results in higher operating expenditure. A case of change from Gas Lift to ESP was studied however due to high rig costs many of these the projects are uneconomic. Given this is the case PETRONAS had been researching the use of high speed slim, power- cable deployed ESPs for installation inside 2- 7/8" and 3-1/2" tubing (TTESP-CD). The challenge was to develop a deployment method using intervention techniques to comply with process safety requirements and installation over a live well without any workover rig. The associated technologies to enable deployment and operation of the ESP were identified, modified, developed and qualified as required in order to meet API 6A, API 14A and ISO 14310.
In order to meet the project objectives and derisk technical uncertainties, an onshore test run and offshore pilot were planned. These ensured the design requirements of the key deployment technologies met relevant API and ISO standards; 1) wellhead adapter for cable exit and load handling 2) the anti-rotation anchor packer and 3) the insert safety valve, 4) wireline unit, 5) pressure control equipment. Each of the technologies developed or modified are key components of the deployment technique. Through the onshore testing, the deployment procedure and running equipment were improvised to fit the offshore pilot installation.
The deployment of the TTESP-CD system offshore was a success; the ESP was installed within 3-1/2" 9.2ppf tubing to a depth of 1752ft over a live well using the modified deployment package. The actual ESP deployment took around 5days including rig up/down of the deployment package. Running the ESP to depth only took around 8hrs including setting the insert safety valve. Major time consuming events were assembling the ESP, cable space- out, cable termination/splice, landing hanger and cleaning out the electrical connections. Looking forward; this is a technology PETRONAS see great value in for Malaysian and international assets. Currently there are plans for four more installations in 2018 and a minimum of five installations in 2019.
The PETRONAS led team have overcome challenges the industry has faced for many years with regards to this type of ESP deployment by investing in R&D and committing resources. By developing this technology PETRONAS and its technology providers have officially opened up market for low cost ESP deployment which is a significant step change to conventional practice. This will be of great benefit to the upstream oil and gas industry, particularly for offshore assets with little infrastructure.
Shale reservoirs contain predominantly micro and mesopores (<50 nm), within which gas is stored as free or adsorbed gas. Due to the ultra-small pore size, multiple transport mechanisms coexist in shale reservoirs, including gas slippage, Knudsen diffusion of free gas and surface diffusion of adsorbed gas. In this work, we propose a new transport model, valid for all ranges of Knudsen number, which combines all transport mechanisms with different weighting coefficients. To quantify the effects of influence factors, we introduce the compressibility factor for real gas effect and effective pore radius for gas adsorption and stress dependence. The model is proven to be more accurate than existing models since the deviation of the analytical solution of our model (3%) from published molecular simulation data is lower than that of existing models (10~20%). Based on this model, we compare (1) the contribution of each transport mechanism to gas transport in pores of different radii, (2) shale permeability measured in laboratory and at reservoir conditions, and (3) permeability of nanopores and natural fractures. It is found that gas transport is dominated by gas slippage and surface diffusion when the pore radius is over 10 nm and below 5 nm, respectively. Knudsen diffusion only becomes significant when the pore radius is between 2 and 25 nm and pore pressure is below 1000 psi. Furthermore, laboratory measurements usually over-estimate shale permeability. We also propose a promising enhanced gas recovery method, which is to open and prop up closed natural fractures using micro size proppants.
Cross-well tomography as a technology is the bridge between spatially detailed wellbore measurements and regional 3D reflection seismic surveys. Repeat cross-well tomography, if applied properly, is able make high resolution measurements of rock property changes, and similar to 4D surface seismic analysis, data differencing can enhance subtle variations not immediately apparent from a single acquisition.
In this study, cross-well tomography measurements were made before and after hydraulic fracturing of a Marcellus reservoir in Clearfield County, Pennsylvania. Though imaging of the cross-well data was problematic, the change in Pwave and Swave velocities show remarkable patterns that shed light on fractures generated and possible residual fluid and pressure remaining in the fractured zone (Figure 1). Evidence from microseismic recording during hydraulic fracturing supports the possible interpretation that significant induced fracturing occurred above the Marcellus reservoir interval (here referred to as the Lower and Upper Hamilton interval), and that residual pressure was left behind post-fracturing as evidenced by the significant drop in Pwave velocities. A corresponding lack of shear wave velocity change suggests that proppant did not reach the Upper Hamilton and Tully formations, and therefore these fractures did not remain connected to the borehole. Significant rock property changes were introduced in the Lower Hamilton, evidenced by the change in the shear velocities through this interval, but the minor Pwave velocity changes suggest that the zone is in communication with the borehole, and therefore pressure was able to dissipate.
Comparison with the microseismic data recorded between cross-well surveys shows interesting but debatable relationships with the tomography in that the density of microseismic events agrees with the Pwave velocity changes, but the rock property changes interpreted from the shear velocities is inferred. Invoking a bedding-plane slip model (Tan et al, 2016), it is possible that shear-slip events were infrequent through the Hamilton, and tensile fractures dominated until reaching the upper Hamilton and Tully carbonate upper bound on fracturing. The paper concludes with some reflections on tomographic processing and applications for further analysis.
Presentation Date: Tuesday, October 16, 2018
Start Time: 1:50:00 PM
Location: 212A (Anaheim Convention Center)
Presentation Type: Oral
Ockree, Matthew (Range Resources-Appalachia, LLC) | Brown, Kenneth G. (Range Resources-Appalachia, LLC) | Frantz, Joseph (Range Resources-Appalachia, LLC) | Deasy, Michael (Range Resources-Appalachia, LLC) | John, Ramey (Novi Labs)
This paper reviews several Big Data analytical initiatives in the Marcellus Shale. We describe how application of Big Data technology evolved, share challenges and benefits derived from Big Data analytical processes, and discuss lessons learned. We present an overview of Big Data methods employed, show how we integrated results with economic analyses to guide field development, and summarize the significant impact on development economics.
This paper will help operators, analysts, and investors "de-mystify" Big Data technology, and provide insights and guidance to those embarking on Big Data initiatives. We discuss an ongoing initiative that employs cognitive analytics to generate production type curves via machine learning and couples the results with integrated economic analyses to guide field development. Challenges associated with data management, such as automated data QA/QC, sparse datasets, interpolation/extrapolation, model training and evaluation are discussed. Benefits derived from integrating Big Data-generated type curves with economics analyses to guide well/field optimization are also presented.
Our past big data experiences have taught us several important lessons. First, Big Data initiatives are journeys, not destinations, so expect to constantly feel like there is more to learn and do. Nonetheless, implementation of Big Data processes along the journey can add significant value to an asset, as demonstrated in this paper. Second, it is critical to clearly define the problem to be solved; without a crystal-clear mission statement, scope creep is inevitable, because Big Data technology is capable of so much. Finally, partnering with someone that has experience solving similar problems can significantly accelerate the process and add value.
Using Machine Learning to generate forecasts allows the engineers to focus their efforts on increasing business value, rather than managing and manipulating data. In the end, we will demonstrate how a process that once took multiple man-weeks of effort was solved within a single man-day of time. Finally, we present an example of an optimization opportunity identified with the potential to yield approximately 15 Bcfe in additional cumulative production, while maximizing future drilling inventory in the Marcellus Shale. (Note – this is presented as a "theoretical" example in the body of the paper.)