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Reservoir connectivity over production timescales is a key uncertainty impacting estimated ultimate recover (EUR) per well, and ultimately the economics of a development, but is difficult to address without production data (particularly where the reservoir is poorly defined by seismic). While appraisal well tests can be designed to help predict the performance of future development wells, high rig costs in deepwater means the test duration is often insufficient to investigate the volume that would be accessed under production conditions. Recoverable resources from a recent deepwater gas discovery were dependent on demonstrating significant reservoir connectivity and net reservoir volume; however, this was complicated by a lower delta plain interval that was dominated by sub-seismic reservoir elements.
This paper describes the acquisition and interpretation of long-term pressure build-up data in a plugged and abandoned deepwater appraisal well. To accomplish the test objectives at an acceptable cost, we turned to a novel combination of well testing, wireless gauge technology and material balance techniques to allow the collection and interpretation of reservoir pressure data over a planned period of 6 to 15 months following the well test. The final build-up duration was 428 days (14 months).
Three interpretation methods of increasing complexity were used to provide insights into the reservoir. Firstly, material balance was used to produce an estimate of the minimum connected reservoir volume. The advantage of material balance is that it requires very few input assumptions and produces a high confidence result. Secondly, we used analytical models in commercial pressure transient analysis software to investigate near wellbore properties and distances to boundaries. Finally, we used finite difference simulation models to investigate reservoir properties and heterogeneity throughout the entire tested volume. With increasing model complexity came additional insights into the reservoir properties and architecture but reduced solution uniqueness.
A key complication for the interpretation of the recorded pressure data was the potential for gauge drift to occur – this was incorporated into the uncertainty range used in all three interpretation methods. The observed relative performance for the various gauges used during the well test is also reported in this paper.
Commencement of initial field production is a unique opportunity to acquire reservoir surveillance information that can inform future reservoir performance. When a field is perturbed from original conditions with first production, there is potential for reservoir property uncertainty reduction by observing pressure measurements at non-producing wells with downhole pressure gauges and comparing the observed signal to a range of simulation model results.
The Wheatstone field, located offshore northwest Australia, has recently commenced production start-up to supply gas to the Wheatstone LNG facility. The operational guidelines required each development well to commence with a single well cleanup flow to the Wheatstone platform. The initial single well cleanup flows of the Wheatstone field allowed scope for the selection of a well flow sequence with observation at non-producing wells.
The recommended sequence of initial cleanup flows was designed with a focus on reducing reservoir uncertainties via the use of Ensemble Variance Analysis (EVA). EVA is a statistical correlation technique which compares the co-variance between two sets of output data with the same set of inputs. For the Wheatstone field well cleanup flow sequence selection, the EVA workflow compared the full field Design of Experiments (DoE) study of field depletion and a series of short early production reservoir simulation DoE studies of the gas field. The co-variance between the two DoE studies was evaluated. The objective of the EVA approach was to determine the startup sequence that would allow for the best opportunity for subsurface uncertainty reduction. This objective was met by ranking multiple cleanup flow sequence scenarios. The key factors considered for sequence selection ranking were the impact on business objectives such as future drilling campaign timing and location of infill wells, as well as insights on reservoir connectivity, gas initially in place and permeability.
The recommended sequence of well cleanup flows uses super-positioning of pressure signal to boost response at observation wells, which improves measurement resolvability. The selected sequence preserves key observation wells for each manifold and reservoir section for as long as possible before those wells were required to be flowed to meet operational requirements. Operational constraints and variations of the startup plan were considered as part of the evaluation.
In this short technical note we lay out an analytical framework to assess the impact of transient temperature changes in the wellbore on pressure transient response of cold water injection wells. We focus attention on the falloff period of an injector following injection. Historically, these pressure data have been used to calculate reservoir properties concerning flood efficiency and completion properties, e.g.: formation permeability-thickness, mechanical skin and fluid bank mobilities. One key question addressed in this paper is whether the effects of thermal heating of wellbore fluids during a falloff survey can mask the pressure signature of a two-zone composite reservoir. The pressure deflections required to detect mobility changes may be relatively small compared to pressure changes induced by temperature effects in the well. The framework proposed in this paper allows for the numerical evaluation of the contribution of each.
Previously, researchers have studied multiple bank transient injection problems extensively for the case of reservoir flow and pressure drop, even for non-isothermal problems. The effect of temperature changes in the wellbore and overburden are seldom discussed, however. It is demonstrated in this paper that these effects can, in some cases, be substantial and it is worthwhile to incorporate them into an interpretation model.
The results of this paper are useful for planning and designing a pressure falloff survey to minimise the adverse effect that heating of wellbore fluid by overburden rock may have on the pressure transient signature. The theory can also be used to analyse existing data affected by the phenomenon.
Appraisal adds value to potential developments by changing key development decisions (well count, subsea infrastructure requirements, development sequence, etc.), and this value can be quantified using value of information (VOI). The value of perfect information is readily evaluated but, unfortunately, all real world data is imperfect. Quantifying the value of this imperfect information requires assessment of either (i) the likelihood of the appraisal activity correctly resolving the value of an uncertainty, or (ii) the impact of the activity on the post-appraisal uncertainty range, both of which can be problematic. Traditional value of imperfect information analyses tend to focus on resolving only a single uncertainty and becomes difficult to apply as the number of uncertainties addressed by a single appraisal activity increases.
This paper describes a fit-for-purpose probabilistic approach to enable the rapid evaluation of perfect and imperfect value of information for a range of appraisal alternatives. The workflow is demonstrated through its application to a recent deepwater appraisal well which included an extended well test selected as the preferred activity from amongst a range of alternatives (including conducting no further appraisal).
The workflow uses a Monte Carlo spreadsheet tool to generate gas in place (GIIP) and estimated ultimate recovery (EUR) estimates for individual reservoir elements, which are then aggregated to field level estimates. A large number of individual trial values are captured and interrogated in conjunction with a set of heuristics to allow the rapid generation of probabilistic development plans (without needing to rely on a small set of deterministic realisations). Distributions and dependencies defined in the spreadsheet can be readily altered, enabling robust evaluation of the impact on EUR and preferred development plan for each appraisal alternative and outcome (low/mid/high). The EUR and development plan are then used in an economic model to quantify the value added by each appraisal activity. The highest value appraisal activity, in this case the appraisal well with an extended well test, was executed and a post-appraisal lookback was completed to review the value of information analysis once the appraisal results were available.
The Wheatstone and Iago gas fields, located approximately 110 km northwest of Barrow Island in the Carnarvon Basin, are developed through a common subsea and offshore platform infrastructure. The production forecasts for the Wheatstone Project are generated using reservoir simulation models for both fields coupled to a shared production network model. This ensures the appropriate representation of boundary conditions on the production system, such as well back-pressures. Typical forecasting workflows in a greenfield environment include running experimental design (design of experiments) to generate probabilistic forecasts of field responses. However, conventional experimental design workflows are based on simulations of a single field and are often completed without coupling the reservoir model to a production network model.
This paper will discuss the improvements to conventional simulation workflows made by the Wheatstone Reservoir Engineering Team. These refinements, which enabled running experimental design with both reservoir models coupled to a production network model, allowed responses to be generated and reviewed at the project level. This approach accounted for field interference through the production network and afforded the opportunity to understand the production interactions and relationships more accurately and thereby establish a vantage point for improved optimisation. The improvements were necessary to overcome some of the commercial and in-house software limitations constraining the workflow and results.
This type of simulation workflow had not been achieved to this extent previously within Chevron Corporation. The approach described here allowed the direct generation of project level responses, such as timing of future drilling campaigns, which would not have been practical or reliable otherwise. Future improvements of this modelling workflow will consist of standardising the workflow within the Corporation, using it for history matching later in life as well as decreasing cycle time on more routine simulation work.
Haghighi, M (The University of Adelaide) | O'Reilly, DI (Chevron Australia Pty Ltd, The University of Adelaide) | Hunt, AJ (Chevron Australia Pty Ltd) | Sze, ES (Chevron Australia Pty Ltd) | Hopcroft, BS (Chevron Australia Pty Ltd) | Goff, BH (Chevron Australia Pty Ltd)
This paper demonstrates how good technical evaluations and focused operational application can enhance the value of a mature asset. The Windalia reservoir underlies Barrow Island (BWI), situated 56 km from the coast of Western Australia, and has produced oil since 1965. Waterflooding commenced shortly after initial production, in 1967, and remains the main drive mechanism in the field today. Throughout the life of this onshore field, water injection and oil production have varied according to asset strategy and economic conditions. In this case study, we share how recent improvements made in the areas of Reservoir Surveillance and Operations activities have increased water injection efficiency and total oil recovery.
Through the use of new methods and workflows, the BWI Sub-Surface team was able to target specific areas of the field to distribute water to in order to increase injection and maximise oil production. For example, new workflows were built with the real-time PI monitoring system to analyse Pressure Fall Off (PFO) tests from each of the 147 waterflood patterns in detail. Capacitance-Resistance-Modeling was also leveraged to guide individual well target injection-rates. Operationally, several projects were also initiated to increase water injection into the right areas of the field.
The new Reservoir Management approach has significantly increased the volume of water being injected into the areas of need, supporting improved levels of oil production. For the first time in almost 10 years, the stream-day water injection rate has exceeded 90,000 bwipd. The results from PFO transient interpretation and pattern balancing proved effective in directing water to low-pressure, high-GOR areas of the field. They also provided valuable information about formation perm-thickness and skin. The phenomenon of water-cycling was also largely avoided, owing to close monitoring of production well tests and water injector transient surveys.
The present work addresses reservoir and operational aspects of Australia's largest active waterflood. The lessons shared are highly applicable to a low oil price environment, as they show how fit-for-purpose and low-cost acquisition of reservoir data can lead to improved field performance.
Reliable reservoir and well performance predictions are essential to successful production, investment planning and capital stewardship for large liquefied natural gas (LNG) projects located offshore Western Australia. Successfully achieving this enables maximisation of revenues without eroding project net present value.
In order to make informed decisions about the timing of future gas supply for LNG plants, the values and trade-offs of different timings for future wells need to be assessed. To achieve this, excellent reservoir characterisation is desirable, as well as reliable modelling of the field management rules, production system and well constraints. This paper will discuss the improved modelling aspect of the field management rules, production system and well constraints that will be used as a basis for future investment timing decisions for the Wheatstone project.
Steps to improve the gas supply forecast included incorporating known production network constraints and downtime associated with well failure, in an effort to more accurately reflect production capability and operating envelopes. The adoption of a new software technology has supported the implementation of detailed and accurate field management logic into coupled production system – reservoir simulation models through a rule-based model controller. This enabled a more accurate representation of operational limitations, as well as more stable and reproducible simulation runs, modifiable well rate allocation schemes and well routing between production corridors.
Improving the simulation models with those functionalities required close integration with flow assurance and subsea engineers, as well as operations, which resulted in a better cross-functional understanding of how certain constraints can affect ultimate field recovery and future field development decisions. Enhancing the representation of the production profiles has also resulted in higher confidence in making more informed decisions for future drilling campaigns timing, scope and well locations.
Future model improvements will consist of incorporating revised operational constraints and updating the model's Field Management Controller as the production networks constraints and limitation are better characterised once the Project is in production phase. Evergreen updates of the reservoir models and the field management model are expected to be performed as new surveillance and production data become available, which will support an improved decision process for future gas supply investment.
The initial well proving and early production period of a hydrocarbon field is a valuable and unique period of field surveillance where there is the opportunity to narrow the range of uncertainty for key reservoir properties through the use of inter-well interference testing. The Wheatstone gas field, currently being developed as part of the Wheatstone liquefied natural gas (LNG) project, is located offshore north-western Australia. The start-up of the Wheatstone field, due to the nature of constrained ramp-up for LNG supply and location of development wells provides a unique opportunity for early field life interference testing. This is due to periods of individual well and well combination flows that are ideal for pulse generation and detection, with many development wells observing potential pressure responses while nearby wells are flowing. This paper will focus on the potential of initial well proving flows for pulse testing at the Wheatstone field to capture reservoir information.
Pulse testing can potentially be an important reservoir diagnostic tool, particularly during early production when the field is at initial state. Through considered test design strategy, detection of a pressure pulse in an observed well can be used to infer inter-well reservoir connectivity, connected pore volume and transmissibility. This paper provides a method to refine reservoir pore volume ranges and transmissibility. This will be accomplished through the use of dynamic model derived pulse testing type curves using homogeneous reservoir properties to match observed signals for selected active and observation well pairs within the Wheatstone field.
A suite of dynamic models exist for the Wheatstone field. These models cover a wide range of possible realisations for reservoir outcomes that affect initial static volumes and dynamic responses including structure, reservoir net to gross ratio and petrophysics (porosity, permeability and saturation). Selected dynamic models that reflect the uncertainty in inter-well connectivity, driven by variations in net to gross ratio and petrophysics, were run to develop well proving profiles for selected development wells, with non-active wells observing for a pressure pulse from this activity. Following the reservoir simulation uncertainty study of well proving flows, a homogeneous reservoir property simulation model was developed based on the reference mid case dynamic model, with constant porosity and permeability applied to active reservoir cells in the mid model. A variety of type curve pulse responses were developed for a range of porosity and permeability ranges for well pairs. These homogeneous type curves are then used to match reservoir model responses for the well proving uncertainty study, leading to estimates of potential average pore volume and permeability between well pairs. Thus the use of homogeneous reservoir model matching of interference signals during initial field conditions can be employed to appraise inter-well reservoir property ranges.
Affinito, Ralph (Chevron Australia Pty Ltd) | Boxall, John (Chevron Australia Pty Ltd) | Clough, Jonathan (Chevron Australia Pty Ltd) | Coletta, Angelina (Chevron Australia Pty Ltd) | Frontczak, John (Chevron Australia Pty Ltd) | Morrison, Alan (Chevron Australia Pty Ltd) | Pradhan, Vijay (Chevron Australia Pty Ltd) | Robinson, William (Chevron Australia Pty Ltd)
Integrated subsurface and facilities management, along with asset integrity and reliability, is a "must win" for flawless start-up and early operations. This consists of understanding and closing the value loop around the subsurface and facilities of an asset or connected set of assets. One of the tools Chevron Australia (Chevron) used to successfully start-up the Jansz field under the Gorgon project was an upstream integrated planning process.
An upstream integrated tabletop process evaluates and tests all plans and procedures that are in place for start-up and the early operating life of the asset, from the sand-face of the reservoir to the inlet facilities (for an upstream focus). This process aims to eliminate the gap between a flawless start-up, defined as reaching target performance as early and safely as possible, and what could be a troubled start-up. Start-up plans are presented based on the underpinning objectives, challenges and strategies from each of the key stakeholder groups. A suitably wide range of credible scenarios, targeting those with the greatest potential to cause significant upsets, are considered and tested to ensure that procedures and mitigation measures are both suitably understood by the relevant stakeholders and are in place. The process also helps define roles/responsibilities and build relationships between the subsurface, subsea, facilities and operation teams starting up the project.
The integrated tabletop process has a significant focus on reservoir management. Early production, staggered well start-ups and well planned production ramp-up activities can provide insight into completion efficiency, performance prediction, reservoir connectivity and reserves assessment. Operation’s objectives, especially for a liquefied natural gas (LNG) plant (successive start-ups, minimum intervention) are often at odds with reservoir management. The tabletop process enables alternatives to be evaluated striving for a balanced, value added start-up plan.
This paper goes through an overview of some of the key concepts required for a successful integrated tabletop process and results of the Jansz field and upstream system start-up. Integrated planning involving subsurface, subsea, flow assurance and facilities resulted in a flawless start-up of the field. Highlights of the results for each of these areas will help support future start-up efforts.
DI, O'Reilly (Chevron Australia Pty Ltd, The University of Adelaide) | BS, Hopcroft (Chevron Australia Pty Ltd) | KA, Nelligan (Chevron Australia Pty Ltd) | GK, Ng (Chevron Australia Pty Ltd) | BH, Goff (Chevron Australia Pty Ltd) | M, Haghighi (The University of Adelaide)
Barrow Island (BWI), 56 km from the coast of Western Australia, is home to several mature reservoirs that have produced oil since 1965. The main reservoir is the Windalia sandstone, and it has been waterflooded since 1967, while all the other reservoirs are under primary depletion. Due to the maturity of the asset, it is economically critical to continue to maximise oil production rates from the 430 online, artificially lifted wells. It is not an easy task to rank well stimulation opportunities and streamline their execution. To this end, the BWI Subsurface Team applied Lean Six Sigma processes to identify opportunities, increase efficiency and reduce waste relating to well stimulation and well performance improvement.
The Lean Sigma methodology is a combination of "Lean Production" and "Six Sigma" these are methods used to minimise waste and reduce variability respectively. The methods are used globally in many industries, especially those involved in manufacturing. In this asset, we applied the processes specifically to well performance improvement through stimulation and other means. The team broadly focused on categorising opportunities in both production and injection wells and ranking them, specifically: descaling wells, matrix acidising, sucker rod optimisation, reperforating and proactive workovers. The process for performing each type of job was mapped and bottlenecks in each process isolated.
Upon entering "Control" phase, several opportunities had been identified and put in place. Substantial improvements were made to the procurement, logistics and storage of hydrochloric acid (HCl) and associated additives, enabling quicker execution of stimulation work. A new programme was also developed to stimulate wells that had recently failed and were already awaiting workover, which reduced costs. A database containing the stimulation opportunities available at each individual well assisted with this process. The project resulted in the stimulation of several wells in the asset with sizable oil rate increases in each.
This case study will extend the information available within the oil-industry literature regarding the application of Lean Sigma to producing assets. It will assist other Operators when evaluating well stimulation opportunities in their fields. Technical information will be shared regarding feasibility studies (laboratory compatibility work and well transient testing results) for acid stimulation and steps that can be taken to streamline the execution of such work. Some insights will also be shared regarding the most efficient manner to plan rig-work regarding stimulation workovers.