Vazquez, Oscar (Heriot Watt University ) | Ross, Gill (Shell Upstream International-Europe) | Jordan, Myles Martin (Nalco Co.) | Baskoro, Dionysius Angga Adhi (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Johnston, Clare (Nalco Champion) | Strachan, Alistair (Baker Hughes)
Oilfield-scale deposition is one of the important flow-assurance challenges facing the oil industry. There are a number of methods to mitigate oilfield scale, such as reducing sulfates in the injected brine, reducing water flow, removing damage by using dissolvers or physically by milling or reperforating, and inhibition, which is particularly recommended if a severe risk of sulfate-scale deposition is present. Inhibition consists of injecting a chemical that prevents the deposition of scale, either by stopping nucleation or by retarding crystal growth. The inhibiting chemicals are either injected in a dedicated continuous line or bullheaded as a batch treatment into the formation, commonly known as a scale-squeeze treatment. In general, scale-squeeze treatments consist of the following stages: preflush to condition the formation or act as a buffer to displace tubing fluids; the main treatment, where the main pill of chemical is injected; overflush to displace the chemical deep into the reservoir; a shut-in stage to allow further chemical retention; and placing the well back in production. The well will be protected as long as the concentration of the chemical in the produced brine is greater than a certain threshold, commonly known as minimum inhibitor concentration (MIC). This value is usually between 1 and 20 ppm. The most important factor in a squeeze-treatment design is the squeeze lifetime, which is determined by the volume of water or days of production where the chemical-return concentration is greater than the MIC.
The main purpose of this paper is to describe the automatic optimization of squeeze-treatment designs using an optimization algorithm, in particular particle-swarm optimization (PSO). The algorithm provides a number of optimal designs, which result in squeeze lifetimes close to the target. To determine the most efficient design of the optimal designs identified by the algorithm, the following objectives were considered: operational-deployment costs, chemical cost, total-injected-water volume, and squeeze-treatment lifetime. Operational-deployment costs include the support vessel, pump, and tank hire. There might not be a single design optimizing all objectives, and thus the problem becomes a multiobjective optimization. Therefore, a number of Pareto optimal solutions exist. These designs are not dominated by any other design and cannot be bettered. Calculating the Pareto is essential to identify the most efficient design (i.e., the most cost-effective design).
One of the biggest challenges in designing squeeze treatments is ensuring appropriate chemical placement along the completion interval. Generally, the chemical slug is bull-headed; therefore, in long horizontal wells and/or crossflow wells, exposing the chemical to all the completion intervals might be difficult. In this paper we introduce a method to evaluate placement efficiency. If placement is inadequate, some sections of the well will be unprotected, resulting in an undesirable situation: the well may appear to be protected because the inhibitor return concentrations measured at surface are above the threshold, but there is a loss of production due to scale deposition in areas of the well not contacted by chemical. In these circumstances inhibitor placement can be accurately determined by production logging, but this can be prohibitively expensive. An alternative is to use tracers to evaluate the layer flow rate distribution, and therefore quantify chemical placement. The objective of this paper is to determine if a tracer package could be deployed as part of a squeeze treatment in challenging wells, in particular in the overflush stage. If there are zones in the wellbore at different pressures, then producing the tracer back in steps at different rates will result in the tracer return concentration profile having characteristic features that can be interpreted to estimate chemical placement.
Two three layer cases with crossflow are considered. In both cases, a tracer package was included in the overflush, and the resulting return profiles showed clearly the desired features. The main advantage of this approach is that there is no significant increase in the operational expense. The only additional expense will be the cost of the specific tracer and the subsequent analysis. It is envisaged that the cost is less than 5% of the total squeeze treatment cost. The results of this novel multi-rate post squeeze production stage following injection of tracer demonstrate the feasibility of including such a tracer package in a squeeze treatment. Data collected may then be used to optimise the design of subsequent treatments, to ensure that appropriate placement is achieved by rate control or by diversion, if necessary.
Reliable and accurate analysis of inhibitors is vital for decisions on efficiency and cost-effectiveness of scale inhibitor squeeze treatments. Recent developments have resolved issues for residual sulphonated polymer chemistries which were previously difficult to isolate. Attention now is directed to challenges associated with phosphonate based inhibitors, particularly when assay is required from a multi-component produced water sample containing other P based inhibitor species which currently poses a significant challenge.
This paper describes the advantages and limitations of techniques used for phosphorus assay including inductively coupled plasma spectroscopy, ion chromatography and wet chemical methods (e.g. Phospho-molybdenum blue, PMB) approaches. Field examples are discussed to emphasize the analytical challenge with cases whereby speciation is readily achieved and others where this is not the case.
To overcome the limitations of these methods, novel approaches for analysis of P – containing inhibitors (in the presence of other –containing additives) include time resolved fluorescence spectroscopy (TRF) and mass spectrometry (MS) detection (which also require development) are considered with potential benefits and limitations / interferences highlighted. These are discussed with highlights of TRF development presented. This technique shows significant scope and potential with promising results showing speciation and discrimination of both polymeric and phosphonate based scale inhibitors as well as a phosphate ester based corrosion inhibitor.
This paper highlights the concept that for residual scale inhibitor assay, one analytical approach does not fit all environments and applications. However the availability of a range of techniques, some of which are still in development, allows for effective monitoring in complex, multi-component environments. The paper highlights development opportunities for some of the newer approaches such as TRF and MS as well as discussing their limitations in complex produced fluids.
Islam, M. S. (Dhofar University Salalah) | Kleppe, J. (Norwegian University of Science and Technology) | Rahman, M. M. (Bangladesh University of Engineering and Technology) | Abbasi, F. (Dhofar University Salalah)
Low salinity water-flooding (LSW) is a promising Improved Oil Recovery (IOR) process in which the salinity of the injected water is controlled to progress oil recovery over conventional seawater-flooding and other EOR methods. Published laboratory studies and field test cases in the last two decades have suggested several mechanisms of oil recovery by LSW, which is still an immature area of research. However, the commercial reservoir simulators have limited capability to model LSW accurately. The principal objective of this paper is to evaluate the potential of IOR using LSW for the Norne Field's E-segment.
There is about 60% oil is still trapped as residual oil especially in the Ile and Tofte formations of the Norne Field's E-Segment even after the completion of primary recovery and seawater-flooding as a secondary recovery technique. LSW simulation is, therefore, run for a period of 18 years from 2005 to 2022 to extract this residual oil adhered to rock wall. LSW simulation studies using original wells indicated that water injection with optimal salt concentration of 1,000 ppm TDS (total dissolved salts) or 1.0 kg/m3 yields substantially higher oil production (34.13 MSCM) compared to seawater-flooding (32.95 MSCM).
With the encouraging finding of LSW, the next stage of the study is involving simulation of different scenarios. Six different cases have been investigated. Case 1 is the base case with seawaterflooding using the existing wells. The other five cases are all LSW, with the following well configurations: (2) using the original wells, (3) using the original wells in addition to a new producing well, (4) using the original wells in addition to a re-completed producing well, (5) using the original wells in addition to a new injection well, and (6) using the original wells in addition to a re-completed injection well. Case 3 indicated the highest oil recovery (50.10 MSCM) compare to other five cases. Thus, it could be concluded that the Norne Field's E-Segment is a good candidate for LSW to extract the residual or trapped oil.
In this study, LSW simulation results have shown the alteration of wettability from neutral-wet to strongly water-wet, which in turn is resulting in a favorable mobility ratio, is the most important IOR mechanism for the Norne Field's E-Segment. LSW in this case is found to give near to piston-like displacement.
Islam, M. S. (Dhofar University) | Kleppe, J. (Norwegian University of Science and Technology) | Abbassi, F. (Dhofar University) | Haque, M. F. (Bangladesh Petroleum Exploration and Production Company Limited)
The endeavor of this study is to evaluate the economic potential of the Norne Field's E-Segment (a Norwegian Offshore Oil Field) under different cost structure for six different field development strategies based on the simulation results of low salinity water-flooding (LSW).
The ultimate oil recovery of the Norne Field's E-Segment is ca. 40% after employing the combination of primary and seawater-flooding as a secondary recovery technique. Therefore, there is about 60% oil is still trapped as a result of high capillary action of water. This trapped oil could be extracted by introducing a novel recovery mechanism. In this case, LSW is considered to extract this residual oil adhered to rock wall.LSW simulation studies using original wells indicated that the water injection with optimal salt concentration of 1,000 ppm TDS (total dissolved salts) or 1.0 kg/m3 yields substantially higher oil production compared to sea water-flooding. Having found that the LSW is an effective Improved Oil Recovery (IOR) technique for the Norne Field's E-Segment, the next tasks are to find the different ways to increase oil recovery using LSW followed by economic feasibility study. Six different well development plans are investigated. For example, case 1 is the base case with seawaterflooding using the existing wells. The other five cases are all LSW, with the following well configurations: (2) using the original wells, (3) using the original wells in addition to a new producing well, (4) using the original wells in addition to a re-completed producing well, (5) using the original wells in addition to a new injection well, and (6) using the original wells in addition to a re-completed injection well. Economic feasibility study has been conducted for all these six cases using Net Present Value (NPV), Profitability Index (PI), and Internal Rate of Return (IRR) methods.
Analyzing the simulation results of the above six field development plans, it has been revealed that the oil production for five LSW cases are higher than the seawater-flooding case which, in turn, result more NPV, more PI, and more IRR for LSW cases. Among the six field development cases, Case-3 has been indicated the highest cumulative oil recovery compare to other five cases and give the highest NPV. Thus, it could be concluded that the Norne Field's E-Segment is a good candidate for LSW to extract the residual or trapped oil.
In this study, LSW simulation results are found to give a favorable mobility ratio, which in turn is resulting the highest oil recovery and the highest revenue.
Gas compressibility factor plays an important role in reservoir engineering applications. A lot of techniques have been proposed to predict Z-factor. Standing-Katz (S-K) Z-factor chart is the most common and popular among them and is being used since 1941. Many correlations have been proposed after S-K chart to regenerate and increase its range in an accurate manner. Some of these models are direct models such as Papp Correlation, Shell Oil Company Correlation, and Beggs and Brill Correlation, others are indirect correlations such as Hall-Yarborough and Dranchuk-Abu-Kassem Correlation.
In this study, five different artificial intelligence techniques are implemented to predict Z-factor. These techniques are neural network, radial basis function network, fuzzy logic, functional network, and support vector machine. To build and test these techniques, Standing-Katz charts data was used in which about 70% of the data was used for training and 30% for testing.
Results from this work show that artificial intelligence techniques can predict Z-factor with low error such as Neural network, Radial basis function, Fuzzy logic, and Support vector machine. Neural network is the best technique among others in predicting Z-factor.
This work will help in selecting the best artificial intelligence technique for predicting Z-factor.
Compressibility factor is the ratio between actual volume to ideal volume. Its value indicates how much the real gas deviates from the ideal gas behavior at a certain pressure and temperature. Z-factor values are mainly used in reservoir engineering (Xiang 2005). Accurate calculation of Z-factor affects determination of other properties for the case of gas condensate and gas reservoirs. The Standing-Katz charts have been used as a standard to calculate Z-factor in petroleum engineering since 1942. These charts were developed using the concept of pseudo-reduced properties, reduced temperature, Tr, and reduced pressure, Pr.
A lot of research have been conducted after Standing-Katz charts trying to fit these charts and to extend them. There are several correlations available to predict Z-factor [Standing and Katz 1942, Papay 1968, Beggs and Brill 1979, Burnett 1979, Papp 1979, Hall and Yarborough 1973, Mahmoud 2013, Lateef 2013, Elechi et. al 2015].
Ensemble-based methods are among the state-of-the-art history matching algorithms. In practice, they often suffer from ensemble collapse, a phenomenon that deteriorates history matching performance. To prevent ensemble collapse, it is customary to equip an ensemble history matching algorithm with a certain localization scheme. Conventional localization methods use distances between physical locations of model variables and observations to modify the degree of observations' influence on model updates. Distance- based localization methods work well in many problems, but they also suffer from some long-standing issues, including, for instance, the dependence on the presence of physical locations of both model variables and observations, the challenges in dealing with nonlocal and time-lapse observations, and the non-adaptivity to handle different types of model variables. To enhance the applicability of localization to various history matching problems, we propose to adopt an adaptive localization scheme that exploits the correlations between model variables and observations for localization. We elaborate how correlation-based adaptive localization can mitigate or overcome the noticed issues arising in conventional distance-based localization.
To demonstrate the efficacy of correlation-based adaptive localization, we apply it to history-match the real production data of the full Norne field model using an iterative ensemble smoother (iES), and compare the history matching results to those obtained by using the same iES but with distance-based localization. Our study indicates that, in comparison to distance-based localization, correlation- based localization not only achieves close or better performance in terms of data mismatch, but also is more convenient to implement and use in practical history matching problems. As a result, the proposed correlation-based localization scheme may serve as a viable alternative to conventional distance-based localization.
In this work we present a systematic geosteering workflow that automatically integrates a priori information and the real-time measurements for updating of geomodel with uncertainties, and uses the latest model predictions in a Decision Support System (DSS). The DSS supports geosteering decisions by evaluating production potential versus drilling and completion risks.
In our workflow, the uncertainty in the geological interpretation around the well is represented via multiple realizations of the geology. The realizations are updated using EnKF (Ensemble Kalman Filter) in real-time when new LWD measurements become available, providing a modified prediction of the geology ahead of the bit. For every geosteering decision, the most recent representation of the geological uncertainty is used as input for the DSS. It suggests steering correction or stopping, considering complete well trajectories ahead-of-the-bit against the always updated representation of key uncertainties. The optimized well trajectories and the uncertainties are presented to the users of the DSS via a GUI. This interface enables interactive adjustment of decision criteria and constraints, which are applied in a matter of seconds using advanced dynamic programming algorithms yielding consistently updated decision suggestions.
To illustrate the benefits of the DSS, we consider synthetic cases for which we demonstrate the model updating and the decision recommendations. The DSS is particularly advantageous for unbiased high-quality decision making when navigating in complex reservoirs with several potential targets and significant interpretation uncertainty. The initial results demonstrate statistically optimal landing and navigating of the well in such a complex reservoir. Furthermore, the capability to adjust and re-weight the objectives provides the geosteering team with the ability to change the selected trade-offs between the objectives as they drill. Under challenging conditions, model-based results as input to a decision process that is traditionally much based on human intuition and judgement is expected to yield superior decisions.
The novel DSS offers a new paradigm for geosteering where the geosteering experts control the input to the DSS by choosing decision criteria. At the same time, the DSS identifies the optimal decisions through multi-objective optimization under uncertainty. It bridges the gap between developments in formation evaluation and reservoir mapping on one side, and automation of the drilling process on the other. Hence, the approach creates value based on the existing instrumentation and technology.
This paper prepared for 2018 OTC Offshore Asia explores the current history of electrically driven functionality for subsea production systems.
It is expected that co-existence of hybrid electrohydraulic and all-electric functionality will dominate the market for subsea tree and manifold control short term. Electric choke and manifold valve actuation offer many advantages as proved successfully during the last 16 years, e.g. related to modularity and flexibility, with zero discharge, with high operational speed and high positioning accuracy, along with CAPEX and OPEX benefits. Performance of systems such as Statoil's Asgard Subsea Gas Compressor is a game changer that will make all-electric valve control base case also for future subsea processing plants.
Reliability & Availability concerns were the major concerns by many operators for not switching to all-electric technology. The excellent reliability of trickle charged batteries in subsea systems, combined with modern safety electronics eliminate the traditional actuator spring as failsafe mechanism power source. All of this has simplified the equipment, reduced the size, and enables continuous equipment status monitoring.
Competitive all-electric systems are expected to be introduced in stages, starting with infill wells. This will eliminate the risk of new technology for the best business cases, being long distance gas fields, water injectors and deep water systems.
Subsea all-electric solutions benefit from general technology developments in other industries. Full utilization is however slow in the subsea market, hampered by current rules and regulations, risk aspects and conservative mindsets. All-electric solutions need Champions and a continued successful staged development initiatives to realize their full potential for significantly reducing subsea field development capital and operational cost.
Agenda Session Details Expand All Collapse All Filter By Date All Dates Tuesday, April 17 Wednesday, April 18 Filter By Session Type All Sessions General Activities Social and Networking Events Technical Sessions Panel, Plenary, and Special Sessions Tuesday, April 17 19:00 - 21:00 Future Leadership Programme: Student Evening Restaurant and Bar Ticketed Event Speaker(s) Darcy Spady, 2018 SPE President As part of the Future Leadership Programme, the SPE Norway One-Day Seminar will host a dedicated Student Evening for both students and Young Professionals* on 17 April. Young Professionals are invited to attend the informal reception. Drinks and canapés will be served. Pre-registration is required for this limited-attendance event. Wednesday, April 18 08:00 - 17:30 Registration 09:00 - 10:30 Opening Panel Session Alexandra Moderator(s) Moderator: Darcy Spady, 2018 SPE President Confirmed Panellists: Tom Huuse, Regional Leader Europe Baker Hughes, a GE company Erik Sverre Jenssen, Field Development Director Lundin Arne Kvamsdal, Director of Business Development Halliburton AS Norge Charlotte Tjølsen, VP Petroleum Technology Statoil 11:00 - 12:30 01T Case Studies - Reservoir I Anitra Session Chairpersons Edel Reiso - Statoil The session includes case studies for three North Sea fields: Smorbukk, Grane and Gullfaks Shetland/Lista.