Topside payloads range from 5 to 50,000 tons, producing oil, gas, or both. A vast array of production systems is available today (see Figure 1). The concepts range from fixed platforms to subsea compliant and floating systems. In 1859, Col. Edwin Drake drilled and completed the first known oil well near a small town in Pennsylvania, U.S.A. This well, which was drilled with cable tools, started the modern petroleum industry.
Figure 1.6--The Baldpate Compliant Tower is one of the tallest free-standing structures in the world – Empire State Building (right) for comparison (Web Photograph, Amerada Hess Corp., New York City). Figure 1.9a--Worldwide fleet of installed and sanctioned semisubmersible FPS (courtesy of BP). Figure 1.9c--Worldwide fleet of installed and sanctioned spars (courtesy of BP). Figure 1.10--Semisubmersible FPS planned for the Thunder Horse field (courtesy of BP). Figure 1.11--Alternative proven technology field development options (courtesy of BP). Figure 1.12--Subsea production trees used in conjunction with a fixed jacket structure (Intec Engineering, Houston).
Each of these is discussed briefly in the next two sections. Thereafter--except for another section on probabilistic procedures near the end--the chapter will focus on deterministic procedures because they still are more widely used. Both procedures need the same basic data and equations. Reserves calculated using such procedures are classified subjectively on the basis of professional judgments of the uncertainty in each reserve estimate and/or of pertinent regulatory and/or corporate guidelines. Probabilistic procedures recognize that uncertainties in input data and equations to calculate reserves may be significant.
Transmitting electrical current to the subsurface can create special considerations. Successful application of electromagnetic heating often requires a multi-disciplinary approach combining electric engineering and petroleum engineering. To assist petroleum engineers considering this approach, this article identifies some of the issues that an electrical engineer might normally anticipate and address. In most practical situations, we are concerned with fields that vary periodically in time (the sinusoidal steady state generally). In these cases the electrical phenomena are properly described by Maxwell equations in terms of complex vector field intensities of electric and magnetic fields (E and H); complex vector field electric, magnetic, and current densities (D,B,J); complex charge concentrations (ρc); and complex material parameters: conductivity, permittivity, and permeability (σ, ε, μM).
Emulsions are always a drain on the operating budget. It is almost impossible to eliminate emulsions during crude production; however, emulsion problems can be reduced and optimized by following good operating practices. The following points should be included in operating practices. Chemical-Demulsifier Development Based on Critical-Electric-Field Measurements. Husveg, T., Bilstad, T., Guinee, P.G.A. et al. 2009 A Cyclone based Low Shear Valve for Enhanced Oil-Water Separation.
Selecting the best tool for a specific type of reservoir condition is a crucial part of a fluid sampling job. Moreover, uncertainty in sample quality increases when the fluid phases are miscible. On a recent logging job, a formation tester was used to acquire water samples across a zone drilled with water-base mud (WBM). We examine the performance of several probe configurations (both existing and prototype) under equivalent reservoir conditions to quantify and optimize filtrate cleanup efficiency. The study is carried out using a compositional simulator for a water-saturated reservoir invaded with blue-dye tracer included in WBM filtrate.
History matching of field measurements allows the calibration of the model for further modification to account for a variety of reservoir conditions. Complex tracer dynamics of a blue-dye WBM invading a water-saturated formation and fluid pumpout are accurately and expediently modeled using a flexible numerical algorithm to account for different probe types and tool configurations. Under normal operating conditions, the chosen formation tester would have taken around one hour to clean the filtrate contamination to a target value of 5%. On the other hand, the best choice was the Focused Elliptical Probe, for which fluid cleanup would take less than 40 minutes. Additionally, a different tool configuration with a combination of multiple probe geometries spaced radially around the tool would provide faster cleanup times of only 32 minutes, thereby saving rig time.
We rank eight formation testing tools designs under equivalent reservoir conditions. The examples highlight the importance of probe geometry and configurations together with reliable and expedient numerical modeling during the pre-job phase to reduce cleanup time in anticipation of complex reservoir conditions. Furthermore, numerical simulations compare the fluid cleanup efficiency for various commercial formation-testing probes together with innovative probe designs that could potentially lead to a new tool or probe development. Perfecting both probe geometry and fluid pumping schedule is the most important output of our study.
Jia, Ying (Petroleum Exploration and Production Research Institute, SINOPEC) | Shi, Yunqing (Petroleum Exploration and Production Research Institute, SINOPEC) | Huang, Lei (Research Institute of Petroleum Exploration and Development, Petrochina) | Yan, Jin (Petroleum Exploration and Production Research Institute, SINOPEC) | Sun, Lei (SouthWest Petroleum University)
The YKL condensate gas reservoir is one of the biggest condensate gas reservoirs in China and has been developed more than 10years. At present, the combination of subdivision layer, production speed optimization and horizontal well drilling has been the key to economically unlocking the vast reserves of the YKL condensate gas. The primary recovery factor, however, remains rather low due to high capillary trapping and water invasion. While primary depletion could result in low gas recovery, CO2 flooding provides a promising option for increasing the recovery factor.
The objective of this work is to verify and evaluate the effect supercritical CO2 on enhancing gas recovery and analyze the feasibility of CO2 enhance gas recovery (CO2 EGR) of condensate gas reservoir.
Firstly, novel phase behavior experimental procedures and phase equilibrium evaluation methodology for gas-condensate phase system mixed with supercritical CO2 with high temperature were presented. A unique phase behavior phenomena was also reported. Then, CO2 floodingmechanism in condensate gas reservoir was analyzed and clarified based on experiments. Finally, a series of numerical simulation work were conducted as an effective and economical means to maximize natural gas recovery with the lowest CO2 breakthrough by varying strategies, including CO2 injection rate, injection composition, andinjection timing. Meanwhile the CO2 storage volumes of different strategies were calculated.
The results show that higher gas recovery factor can be achieved with CO2 injection through appearing interphase between two fluids, maintaining reservoir pressure, driving gas like "cushion" and controlling water invasion. All strategies have moderate to significant effects on gas production. The control of injection and production ratio needs to be balanced between pressure transient and CO2 breakthrough over the producer to obtain the maximum gas production. The varying injection pressure shows a positive effect of enhancing gas production. Numerical simulation indicated that the recovery of gas reservoir was improved by around 10 percent. The total CO2 storage would be around 30-40% HCPV.
The research showed that CO2 flooding presents a technically promising method for recovering the vast condensate gas while extensively reducing greenhouse gas emissions.
Recent studies have indicated that Huff-n-Puff (HNP) gas injection has the potential to recover an additional 30-70% oil from multi-fractured horizontal wells in shale reservoirs. Nonetheless, this technique is very sensitive to production constraints and is impacted by uncertainty related to measurement quality (particularly frequency and resolution), and lack of constraining data. In this paper, a Bayesian workflow is provided to optimize the HNP process under uncertainty using a Duvernay shale well as an example.
Compositional simulations are conducted which incorporate a tuned PVT model and a set of measured cyclic injection/compaction pressure-sensitive permeability data. Markov chain Monte Carlo (McMC) is used to estimate the posterior distributions of the model uncertain variables by matching the primary production data. The McMC process is accelerated by employing an accurate proxy model (kriging) which is updated using a highly adaptive sampling algorithm. Gaussian Processes are then used to optimize the HNP control variables by maximizing the lower confidence interval (μ-σ) of cumulative oil production (after 10 years) across a fixed ensemble of uncertain variables sampled from posterior distributions.
The uncertain variable space includes several parameters representing reservoir and fracture properties. The posterior distributions for some parameters, such as primary fracture permeability and effective half-length, are narrower, while wider distributions are obtained for other parameters. The results indicate that the impact of uncertain variables on HNP performance is nonlinear. Some uncertain variables (such as molecular diffusion) that do not show strong sensitivity during the primary production strongly impact gas injection HNP performance. The results of optimization under uncertainty confirm that the lower confidence interval of cumulative oil production can be maximized by an injection time of around 1.5 months, a production time of around 2.5 months, and very short soaking times. In addition, a maximum injection rate and a flowing bottomhole pressure around the bubble point are required to ensure maximum incremental recovery. Analysis of the objective function surface highlights some other sets of production constraints with competitive results. Finally, the optimal set of production constraints, in combination with an ensemble of uncertain variables, results in a median HNP cumulative oil production that is 30% greater than that for primary production.
The application of a Bayesian framework for optimizing the HNP performance in a real shale reservoir is introduced for the first time. This work provides practical guidelines for the efficient application of advanced machine learning techniques for optimization under uncertainty, resulting in better decision making.
The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS.
This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers.
Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles.
This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.
One of the main uncertainties when designing polymer floods is the polymer injectivity, an important parameter that can affect the economics of the process. Reservoir simulation can be used to forecast injectivity, but the process is not straightforward and can be affected by grid size and other factors. Analytical methods are also available for that purpose, but they are considered too simplistic to deal with realistic reservoir conditions. The aim of this paper is to show that this is not the case and that simple analytical tools can be accurate and of great help to predict or history match polymer injectivity.
The analytical method has been developed by Lake in his classical textbook on Enhanced Oil Recovery, but few applications are documented in the literature. This paper will review the method and corresponding equations before presenting several actual field cases of injectivity in polymer flood pilots or tests from several countries that have been matched analytically.
Although it has not been used very often, the method has been found to give very good results in most of the field cases tested in a variety of situations; these cases will be presented along with recommendations on how to apply the method and a discussion of the results. Sensitivities to the various parameters will also be presented. Once the equations are programmed in a spreadsheet, the matching process takes only a few minutes and it is easy to run various scenarios and sensitivities.
Polymer injectivity remains one of the less understood and less predictable aspects of polymer flood projects. This paper will encourage engineers who are planning such projects to use simple yet accurate analytical tools before embarking in more complex and time-consuming reservoir simulations.