Polymer rheological behavior in an Enhanced Oil Recovery (EOR) project is one of the critical factors to determine whether the polymer injection would be effective to increase the oil production in a field. Due to complications on the measurement of this parameter and its variation within the reservoir, the challenge of understanding viscosity behavior relies on lab and field tests that become key factors to solve this issue.
This study was conducted during an injectivity test for an EOR project in Los Perales field (Santa Cruz, Argentina) in three wells with different operational and subsurface conditions, and tests were performed twice a day for 30 days each in order to obtain sufficient time span of data.
From lab rheology tests performed at reservoir conditions, where the main objective was to analyze viscosity changes through time, two different tendencies were observed: one that affects in early times and another that becomes preeminent at late times. With these results, a describing equation was developed to predict viscosity evolution over time. The equation consists of three terms including thermal variation, chemical degradation and the final viscosity towards which the polymer tends.
Although the equation properly describes both lab and field polymer solution, there is a considerable difference, especially when the effects mentioned become preponderant. This difference is attributed to both the water used for the mixture and the possible impurities that may be incorporated during the maturation or transfer of the polymer. Since most of the data used was obtained from field tests, this emphasizes the appliance of the equation on the field.
Impurities turn out to be crucial, specially oxygen (O2) and hydrogen sulfide (H2S) combined. Their presence highly impacts the asymptotic viscosity, so a correlation between H2S content and final viscosity was also developed.
Finally, an analysis of the temperature influence on the viscosity was conducted. A correlation between the final viscosity and temperature was found and used to incorporate temperature variations in the predictions and therefore to relate measurements performed at different conditions.
The primary advantage of this study is that the equation and correlations enable the prediction of the polymer solution viscosity at any time. This allows the estimation of actual polymer viscosity in the reservoir from a routine measurement at any temperature and impurities content. The versatility of this equation is what makes it novel and useful in an industry going towards EOR projects.
By International Petroleum Technology Conference (IPTC) Monday, 25 March 0900-1600 hours Instructors: Olivier Dubrule and Lukas Mosser, Imperial College London Deep Learning (DL) is already bringing game-changing applications to the petroleum industry, and this is certainly the beginning of an enduring trend. Many petroleum engineers and geoscientists are interested to know more about DL but are not sure where to start. This one-day course aims to provide this introduction. The first half of the course presents the formalism of Logistic Regression, Neural Networks and Convolutional Neural Networks and some of their applications. Much of the standard terminology used in DL applications is also presented. In the afternoon, the online environment associated with DL is discussed, from Python libraries to software repositories, including useful websites and big datasets. The last part of the course is spent discussing the most promising subsurface applications of DL.
Summary In the past decades, many exploration wells have drilled into igneous rocks by accident because of their similar seismic expression to the common intended targets such as porous carbonate mounds, sheet sands or deepwater sand-prone sinuous channels. In cases where sedimentary features such as channels or fans cannot be clearly delineated, the interpretation may be driven primarily by bright spot anomalies, and a poor understanding of the wavelet polarity may compound this problem. While many wells that are drilled into igneous rocks were based on interpretation of 2D seismic data, misinterpretation still occurs today using high quality 3D seismic data. We propose an in-context interpretation workflow in which the interpreter looks for key clues or parameters above, below and around the target of interest to confirm the interpretation. Introduction Using modern 3D seismic surveys, significant work has been achieved over the past two decades in accurately imaging the geometry of igneous bodies (Hansen and Cartwright 2006; Holford et al., 2012; Jackson et al., 2013; Magee et al., 2014).
This session will discuss open-hole sand control completion, gravel and screen design and field performance. This session will cover production enhancement of carbonate reservoirs using acid and non-acid treatments. Topics of papers in this session discuss evaluation, characterization, and remediation of formation damage in new, secondary recovery, and producing well environments. Rustom K. Mody, P.E., is the VP–Technical Excellence for Baker Hughes a GE Company. Mody has more than 39 years of experience in drilling, completion and production of which 30 years with Baker Hughes a GE company in various executive positions in technology.
Cooper, Norman (Mustagh Resources Ltd.) | Herrera-Cooper, Yajaira (Mustagh Resources Ltd.) | Vernengo, Luis (Pan American Energy LLC) | Trinchero, Eduardo (Pan American Energy LLC) | Stolarza, Raúl (Data Seismic Geophysical Services)
The purpose of this paper is to propose a two-fold solution to a complex noise problem in the Gulf of San Jorge Basin in Argentina. Irregularly shaped Intrusive bodies scattered at shallow depths over large areas above the reservoir generate a severe signal to noise problem that masks deeper reflection signals and inhibits the ability to find prospects. This type of noise is source generated and scatters in a chaotic manner. In order to tackle this problem, a custom tailored present day reprocessing flow is applied to enhance the data quality below the intrusive areas. Significant improvement is observed with regards to reflection continuity, character and frequency content. Nevertheless, the data improvements are not sufficient for quantitative interpretation and a new 3D survey design is proposed. The 3D design focusses on the type and magnitude of noise present as well as on signal. Two sets of parameters are proposed, alternate and recommended, and then compared to those used in the original acquisition. The new sets of parameters have a higher trace density produced by the reduction of line spacing and also have a significant impact on costs. It is important to visualize what the potential benefit may be. A special tool called Data Simulation is applied using local super gathers and the geometry of each survey to simulate stacked sections. In this studied case, it appears that increased design density may be expected to provide the increase in data quality desired by the interpreter in the poor data areas. Data Simulation helps decrease the uncertainty in acquisition parameter selection. Both solutions worked well and required the interaction of many professionals in the processing and the design stages.
Presentation Date: Thursday, September 28, 2017
Start Time: 8:55 AM
Presentation Type: ORAL
When the natural energy of a reservoir is not adequate to lift the wellbore fluid to the surface, it is necessary to use an artificial lift system that supplies the additional energy required to continue the exploitation of reservoirs.
This paper presents a trial jet pump application in the dead well of a mature oil field. The well was completed with dual strings of size 2-3/8 in. in a 7 in. casing and was producing from two separate formations. Both formations, despite of having produced for a considerable amount of time, have high reservoir pressures at present. The upper formation being produced independently via short string was loaded up for almost three years, because the API and Gas Oil Ratio (GOR) from the formation were very low along with high water cut. The lower formation had a substantial amount of gas with no water cut and was producing at significant oil rates. However, the formation being produced through the long string did not flow after shutting in for a Bottom Hole Pressure (BHP) survey. The well was unloaded by reducing surface back pressure, but it exhibited slugging behavior and an increased oil API and therefore was abandoned.
The test with hydraulic jet pump was justified by the need to revive production without a work-over. Thus, a jet pump was installed in the short string in a Sliding Side Door (SSD), and the short string was tested first with the long string being isolated. After the testing of short string independently, an SSD connected to the long string in the middle of two packers, was opened so that both formations can be produced from the same short string.
Based on the results, a dead well was successfully revitalized with the cumulative production of 380 BPD i.e., an average of 100 BOPD and 280 BWPD, which was higher than the targeted production rates evaluated for this well. Apart from this, downhole pressure data was gathered with the objectives to observe the potential of reservoir and to assist the operator for making the decision of installing jet pump on the well with or without a worker-over. Nevertheless, this technique allowed the operator to install jet pump through slick-line and consequently saved the cost of a work-over. Hence, jet pump was found to be the most efficient Artificial Lift System (ALS) and the trial achieved more than the expected performance.
The main goal of all production operators is maximizing production and net profit out in a very safe and environmentally controlled manner. When producing difficult fluids from marginal, mature and brown onshore oil fields, Sucker rod (Beam and Progressive Cavity) Pumping systems are typically the most common artificial lift methods used. The primary challenge is to extend the lifting equipment run life, especially the downhole components. For years, operators have been looking for a reliable and accurate way to automatically control these types of lifting systems to improve their reservoir recovery factor by maximizing production.
The best-proven way for operators to make proactive decisions for well / field optimization, is to have a fully automated closed-loop monitoring and control solution for the entire field of artificially lifted wells. This paper will show how the well automation and real time downhole measurements are used in real time to control and optimize the operation parameters and well production to obtain maximum benefits. Some case histories for Beam and Progressive cavity pumping systems from different oil fields will presented.
Many fields in Argentina have multilayer reservoirs that require various stimulation techniques, mainly hydraulic fracturing. A variety of formations and types of reservoirs, such as conventional (mature fields) and unconventional (tight gas and shale), are present in the Golfo San Jorge and Neuquen basin. The hydraulic fractures created in these basins present a variety of conditions and challenges related to depth, well architecture design, bottomhole temperature (BHT), reservoir pressure, and formation permeability.
In the last decade, new technologies were introduced and developed to help achieve greater efficiency and reduce time and costs associated with completions for these fields. This paper presents experiences gained using two types of technologies.
First, a new conventional straddle-packer system (SPS) was used in conjunction with a workover unit, which was part of a technological collaboration agreement between an operator and service company. It was mainly applied in conventional reservoirs, mature fields, in wells with up to seven fracture stages, and in new or recompletion wells. Second, a pinpoint technique was used, called hydrajet perforating annular-path treatment placement and proppant plugs for diversion (HPAP-PPD). This technique was applied in new wells (rigless completion) and all types of reservoirs, both conventional and unconventional (tight gas and shale), and allowed performing up to 30 separate fracture stages in a single well, with three stages completed in a 12-hr operation.
These completion methods allowed operators to focus treatments in desired zones with specific treatment designs based on reservoir characteristics. Several case histories are presented for different basins, formations, and reservoirs types, as well as lessons learned and completion time reductions.
A geostatistical seismic pre-stack inversion was carried out over a producing gas and condensate field in the Gulf of Thailand, North Malay basin. As the main reservoirs are thin-bedded stacked fluvial deltaic sands of Miocence age, detailed mapping of reservoir distribution was challenging due to limited seismic resolution. To overcome such challenges, a pre-stack geostatistical inversion was initiated. The input dataset consisted of six wells and 250 km2 of 3D seismic data. The well log data passed through rigorous QC and rock physics analysis, while the seismic data were subject to preconditioning to ensure improved CDP gather flatness and signal-to-noise ratio. Starting from geostatistical modeling, the inversion generated multiple detailed realizations of lithology and elastic properties based on Bayesian Inference and Markov-Chain Monte Carlo methods. Statistic of multiple resulting realizations also implied a range of possible solutions of this non-unique inverse problem. In addition, petrophysical properties were simulated by using statistical relationships between inverted elastic and petrophysical properties. By integrating high frequency well logs with low frequency seismic, the geostatistical inversion process provided high vertical resolution and captured spatial variations of the various lithology types and their respective elastic properties. Since a majority of the stacked gas sand reservoirs in the area were below the tuning thickness, the geostatistic inversion results provided significantly improved insight to facies distribution. According to blind well results, precision of net pay estimation provided by the geostatistical inversion improved from 40% to 83%, compared to predrilled prognosis; while, pay estimation uncertainty was reduced by 30%. The generated petrophysical volumes also showed more detailed spatial variation, and can be used to improve in-place volumetric calculations and support field development planning.