The increasing attention and development of unconventional resources has many in the industry searching for suitable analogs to supplement their evaluation. A common approach is the use of type wells. Type wells are created by averaging the rate of several analogous wells. This type well rate and corresponding volume is used as a benchmark for evaluating and guiding forecasts for similar wells. The concept of type wells is not new but there are aspects that can be refined to improve results.
The current industry practice has a flaw that when combined with development practices will provide inaccurate results. When creating a type well from historical data only, forecasts are implicitly calculated for wells that do not have enough production to reach the end of the type well time interval. Adding to this is the fact that operators will optimize profit by drilling their best wells first. In this instance the type wells will have a greater rate profile and expected ultimate recovery (EUR) than the underlying data will support. This is because the implicit forecasts for the newer, less productive wells are created from the older, better wells. Conversely, type wells will under-predict rate and EUR in technical plays where performance improves with experience. This paper proposes an approach to address the flaw.
When historical production data is merged with reliable production forecasts to build a type well, the resulting type well is the best available representation of the underlying data. Measures to ensure accurate forecasts on individual wells are recommended.
As an extension to predicting a single rate for similar wells, type wells are also employed to predict different percentile outcomes for similar wells. A common method considers all of the data and calculates a percentile at each time step (Time Slice approach). This approach does not produce consistently reliable results. This paper will propose an alternative approach to creating Type Wells at varying percentiles by analyzing actual wells whose outcome is close in value to the desired percentile.
As the high demand for fossil fuel pushes the frontiers of oil exploration and production into more hostile environments, issues associated with flow assurance have become increasingly important. This is especially true of paraffin wax precipitation and deposition in areas of reduced temperatures, such as the Polar Regions and in deep sea environments. In order to reduce costly remedial operations aimed at removing pipe/tubing blockages resulting from wax deposition, it is essential to predict when, where and how much paraffin wax is deposited during the working life of oilfield installations. In this study, a computer application model capable of predicting wax precipitation and deposition in oilfield installations under various conditions of flow was developed. Thus, a computational flow dynamics (CFD) program named "WD-Predictor?? using C++ language was designed and developed with mathematical models that approximate the physical behavior of wax crystallization and deposition systems such as; Property Transport Models (Energy, Momentum and Mass),Thermodynamic Equilibrium Model and Wax Deposition & Erosion Model. The mathematical models developed were discretized while numerical solutions to the discretized models were then developed using appropriate algorithms and pseudo-codes. The "WD-Predictor?? was used to estimate the Wax Appearance Temperature (WAT) of three crude samples. The results obtained were compared to an experimental results published; Exp.WAT for oil sample 1 was 87.800oF and Predicted was 89.888oF, for oil sample 2- the Exp. WAT was 114.35oF and predicted was 115.76oF and for oil sample 3, Exp. WAT was 72.950oF while Predicted was 70.620oF. Again, WD-Predictor results were compared with the experimental data extracted from Cordoba and Schall (2001). Above all, WD-Predictor output on wax deposition thickness was also compared with the enthalpy-porosity model proposed by Banki et al. (2008) and in all the WD-Predictor showed consistence in results, in line with these published experimental results. Finally, WD-Predictor was validated with a well-tested simulator PROSPERTM on pressure and temperature profiles using Beggs & Brill Correlations.
This article, written by Editorial Manager Adam Wilson, contains highlights of paper SPE 152257, "Advances in Measurement Standards and Flow Properties Measurements for Tight Rocks Such as Shales," S. Sinha, SPE, E.M. Braun, SPE, Q.R. Passey, SPE, S.A. Leonardi, SPE, A.C. Wood III, T. Zirkle, SPE, J.A. Boros, SPE, and R.A. Kudva, SPE, ExxonMobil Upstream Research, prepared for the 2012 SPE/EAGE European Unconventional Resources Conference and Exhibition, Vienna, Austria, 20-22 March. The paper has not been peer reviewed.
Popov, Yu (Schlumberger Research Center) | Parshin, A. (Schlumberger Research Center) | Chekhonin, E. (Schlumberger Research Center) | Gorobtsov, D. (Schlumberger Research Center) | Miklashevskiy, D. (Schlumberger Research Center) | Korobkov, D. (Schlumberger Research Center) | Suarez-Rivera, R. (Schlumberger Innovation Center) | Green, S. (Schlumberger Innovation Center)
Kang, Jaemo (Geotechnical Engineering Research Division, Korea Institute of Construction Technology) | Lee, Jangguen (Geotechnical Engineering Research Division, Korea Institute of Construction Technology) | Kim, YoungSeok (Geotechnical Engineering Research Division, Korea Institute of Construction Technology) | Hong, SeungSeo (Geotechnical Engineering Research Division, Korea Institute of Construction Technology)
Falser, Simon (Centre for Offshore Research and Engineering, Department of Civil & Environmental Engineering, National University of Singapore) | Loh, Matilda (Centre for Offshore Research and Engineering, Department of Civil & Environmental Engineering, National University of Singapore) | Palmer, Andrew (Centre for Offshore Research and Engineering, Department of Civil & Environmental Engineering, National University of Singapore) | Tan, Thiam Soon (Centre for Offshore Research and Engineering, Department of Civil & Environmental Engineering, National University of Singapore)
Hydrogen sulfide (H2S) generated by aquathermolysis—a high-temperature reaction of condensed steam (water) with sulfur-bearing bitumen in the reservoir rock—may increase the risk of sulfide stress cracking (SSC) in cyclically steam stimulated (CSS) wells. In a given field, H2S levels and wellbore conditions vary significantly among wells and so do their SSC-susceptibility. Identifying the SSC-susceptible wells is important in terms of reducing SSC risk by allocating resources and implementing pro-active intervention measures to the SSC-susceptible wells. A comprehensive research program, with a dedicated instrumented CSS well as the centerpiece, has been undertaken by Imperial Oil Resources with the objectives of characterizing H2S evolution in the wellbore and developing a tool for identifying the SSC-susceptible wells. The research includes laboratory and field tests, and statistical, phase behaviour and kinetic modelling. The SSC-susceptible zone for Cold Lake CSS has been established from Cyclic Slow Strain Rate (CSSR) laboratory tests incorporating CSS fluid chemistry, stress-strain environments, casing metallurgy, and variable temperature and H2S partial pressure. A statistical logistic model matches the experimental CSSR data well. The instrumented well data validate the phase behavior model, which in turn explains the measured H2S profile in the wellbore. An aquathermolysis kinetic model has been developed for the instrumented well and validated with data from nine other CSS wells. The research has led to the development of an engineering tool for identifying the wells at the risk of falling into the SSC-susceptible zone.
A novel method of delivering thermal energy efficiently for flow assurance and for improved heavy oil production/transport is described. The method, an improved form of magnetic induction heating, uses superparamagnetic nanoparticles that generate heat locally when exposed to a high frequency magnetic field oscillation, via a process known as Neel relaxation. This concept is currently used in biomedicine to locally heat and burn cancerous tissues.
Dependence of the rate of heat generation by commercially available, single-domain Fe3O4 nanoparticles of ~10 nm size, on the magnetic field strength and frequency was quantified. Experiments were conducted for nanoparticles dispersed in water, in hydrocarbon liquid, and embedded in a thin, solid film dubbed "nanopaint". For a stationary fluid heat generation increases linearly with loading of nanoparticles. The rate of heat transfer from the nanopaint to a flowing fluid was up to three times greater than the heat transfer rate to a static fluid.
Heating of nanopaint with external magnetic field application has immediate potential impact on oil and gas sector, because such coating could be applied to inner surfaces of pipelines and production facilities. A nanoparticle dispersion could also be injected into the reservoir zone or gravel pack near the production well, so that a thin, adsorbed layer of nanoparticles is created on pore walls. With localized inductive heating of those surfaces, hydrate formation or wax deposition could be prevented; and heavy oil production/transport could be improved by creating a "slippage layer" on rock pore walls and inner surfaces of transport pipes.