Integrated Field Development Planning: A Pore-to-Process Perspective

good day everyone thank you for joining the upstream technology leadership webinar my name is Joseph - Lipsky I work in technical marketing for reservoir engineering today's webinar will be presented by Michael Scanlon will discuss integrated field development planning a port to process perspective Mike Scanlon is a chief reservoir engineer with summer j1 subsea who has over 35 years of industry experience working with major and independent operators in field development planning reservoir management and production operations during his time with summer shed he has worked in the Middle East Southeast Asia United States and the United Kingdom working in a predominantly technical management capacity for sis and petroleum engineering software technology IBM with field development projects subsea developments with one subsea please note that throughout the session you can submit questions using the green button on the left side of the screen and with that I'll hand it over to you Mike to proceed with your presentation Thank You Joseph and good morning I'll good afternoon everybody what I was going to spend about 40 minutes talking about is integrated field development planning and but taking a much more of a holistic view so looking at the the entire process from from the poor through to the to the export flange so what I would like to cover is the what the why and the how so in terms of what looking at the the way that a systematic approach has been developed and is is generally adopted now to apply to field development planning in terms of structuring the decision making process I wanted to touch a little bit on the why which is the the complexity of the decisions that are being made the the many different interactions that are required and how these can be these can often be a source of problem and then finally spend time talking about how now I don't propose to spend a lot of time talking about the detail of the technical analysis I don't propose to talk about the application of a fractional flow curve or the specification of the pair requirements for an electrical submersible pump what I want to do is spend a little bit more time talking about the the approach and the type of requirements in the approach and specifically on the requirements of the enabling technology that needs to be is so in terms of the the overall the overarching approach there very much has been an adoption of this gated decision making process to field development planning this is now fairly common within within the industry and essentially what it does is breaks the development planning process down into discrete phases each one of these phases is bounded by a gate a decision gate and in order to pass through that decision gates and incur the increased expenditure the increased commitment to the project there needs to be certain sanctioned criteria that need to be met so a lot of what well all of what we're going to talk about is around the application of this gated decision process but within the application of that process there are a number of key facets that need to be to be considered and what I want to do is spend some time talking about the requirement for integration an integration across the the expert disciplines and also an integration in in time talk about the scalability of the analysis that can be done and how it can be geared towards matching the objectives of each phase of the decision making process and talk also about the increasing importance of quantifying the the associated uncertainty and the ability to translate that into some sort of a quantification of the risk and associated contingency and mitigation strategies and if this can be effectively undertaken with these three key facets then there's the opportunity to try and fast-track this whole process and make it much more quick and and flexible so moving on to the the why why is why is this important well the first thing to consider is that in field development planning there is there's no one particular goal that is being sought and there's no one particular person that this is this problem is being addressed too so there's the recognition that there are a number of key stakeholders in this development planning process there's obviously the operator and they have to make the investments and the commitments to the to the operation there's the partners there's the legislators there's the local government importantly there's the finance here's who will have certain criteria that they need to have met and obviously there's there's a market that needs to be considered so each one of these stakeholders will require slightly different emphasis on their objectives on what they're looking for out of this planning process so it's not just implicit that it's a complex technical process that that has to be undertaken it's also that the output and the decision support needs to be in terms of the different objectives but it required B that economic in terms of net present value or cash flow generation or the phasing of that cash flow generation but it could also be the maximization of recovery it could be the local content it could be the licensing requirements so it's it's as well to keep that in mind so the other is that the the industry has faced a number of challenges in recent field development performance there are a number of reasons for this but these can be summarized as the the problem that projects are becoming generally much more complex there's there's an increasing diversity in the type of development that's undertaken and in many cases the the associated costs and liabilities in many cases are actually becoming much more much larger in recent years with the with the drop in the the oil price there is there is a much lower margin so there the the efficiency of these developments needs to be be there but also as the market is changing so quick there's often a requirement for flexibility and efficiency to you know be able to accelerate where where the opportunity arises so there are a number of challenges that face the the execution of field development planning so looking at some of the key examples of this this is a this is a presentation that's actually made by by a major oil company Eni just looking to the future and really reflecting the type of projects that they are likely to be engaged with moving forward and they're sourcing their data from the from the EIA but the the point that they're highlighting is that the type of project that they're going to be undertaking is going to become much more diverse they are going to be dealing with certainly a lot of declining production and within those those declining fields there's going to be the requirements who apply a lot more technology to to improve recoveries so you are and IOR type processes there will be a move to Ward's in some cases much more complex environments are big or deep water or fast track onshore developments and all of these will take a slightly different skills slightly different emphasis and and a different focus and yet they're all contained within the broad spectrum of a portfolio that a major oil company is is going to have to deal with so looking back and this is really looking at a retrospective from a number of multiple sources over the past five two to eight years and obvi to hundreds developments 99% of them did not meet the forecasts that were originally estimated for them and on which they were originally sanctioned there was on average a two-year delay and and this could be summarized through a resultant loss or in terms of cost overruns or non-performance equivalent to about 30 billion dollars a year so there is a huge opportunity here to try and improve the the effectiveness and the efficiency of this this process and the cartoon on the right is is really just a generic perspective of where a lot of the value erosion can occur between the full potential value of a resource represented on the left and the actual value that's achieved and there's some some generic areas where where there is an erosion of this value be it in terms of the reservoir and a poor understanding of the the reservoir and its sides its performance there there's also problems within the the gathering system where it can be under sized or oversized or there's unforeseen shutdowns or equipment failures so all of these are recognized issues that are dealt with but there's there's another area which is the which is classified here is the integration law and by integration really what we're referring to is the recognition of the interdependence between all of the components of this value chain how they interact and how they need to be able the interaction and the interdependence II really needs to be communicated much more efficiently and effectively so really that's why this this focus on on integration is is so important and really to emphasize that at this point this is this is an output from an internal study that that she'll presented looking at their development planning processes and really trying to identify the core challenges and opportunities now this is is quite a dated slide so this is not something that's particularly new but it is a challenge that's being faced so on the top they outline the you know the challenges and essentially the opportunities and on the bottom they sort of address some of the the causes and one of the key ones that they point out is the poor integration of experience and knowledge and particularly an environment that encourages a technical environment that encourages people and experts or probably different disciplines to be able to work together and this can be either in terms of organization or in terms of tools so this is sort of a challenge that was put out there I mean you know this is of the order of about ten years ago there's another perspective here from from another major oil company study and this is this is some output that was this is a paper that was published by Chevron and it really makes a very obvious point but something that is there's often misunderstood there's there's a tremendous focus on project execution in terms of managing the the cost of execution in terms of managing the you know the performance of bills the performance of drilling but this retrospective analysis points out the importance of good planning because what they what they were what they're illustrating here is that if you if you plan if you if you if you have poor project definition so you follow the lower curve on that that net plot no matter how well you execute no matter how well you drilled your wells no matter how well you control your course if you put the wells in the wrong place if you put the wells if you don't complete them in the right way then you'll hear you can have excellent execution that'll get you to Point C but you still won't have a good project so in order to get a good project you really need to get the planning right so the planning is absolutely key and hence this focus on on coming up with a systematic way of being able to to move through this planning process to ensure that it's consistent its comparable with other opportunities and it captures all the the opportunity so what we'll talk about now is is maybe how we can we can address the requirements of this planning process and what I want to do is is start with looking at some of the implications so as I work in in subsea environments what I what I'd like to do is maybe take an example from that world which is looking at the the concept and the design requirements or the subsidy development now as a reservoir engineer I'm particularly focused on the performance of the reservoir and the recovery but there is a recognition that the equipment that is required in order to exploit and develop this asset has an extremely important role to play in terms of the the lift requirements those that is required in order to get the hydrocarbon to the the export vessel in terms of the flow assurance due to thermal losses in the line and potential for for waxing and and also the operability in terms of the type of flow regime that that's likely to be experienced within the gathering system if there's going to be slugs or if there's going to be problems with with with liquid holdup and all these are related to the delivery pressure and the delivery rates and the nature of the hydrocarbon that's coming into the system so the inter dependency in the subsea world between the reservoir and the gathering system is is very evident there's another aspect to the the offshore environment which is particularly pertinent which is the ability to to match the the uncertainty and therefore the phasing of the project to the to the capital commitments that are being made so in an offshore environment there is the choice of going with dry trees which is either building out a platform or you know coming up with some sort of a structure that the wellhead can be above the surface of the water and going subsea putting the the well heads on the seafloor and the real decision that's being made here is is taken very early on in the development planning process and it's absolutely critical because it's a trade-off between essentially the capital commitments that needs to be made to the project very early in the project life in order to build the platform that's required to drill the wells from so with a limited amounts of reservoir understanding in order to be efficient a decision has to be made to spend hundreds of millions of dollars of capital cost to build out a platform the alternative is to go subsea and with a subsea approach the project can be phased there isn't the requirement to make a big capital commitment to a major major structure because you just have to buy the well heads and the subsea well heads and the flow lines which means that the project can be progressively phased as more is understood about the the reservoir so this has a tremendous appeal the downside of a subsea approaches that access to the wells becomes extremely difficult and become and can become prohibitively expensive so this decision that needs to be made very early on between dry trees and wet trees is really a difference between capital cost and operating costs operating risk later on so the the understanding of balancing the what is known or the implication of what is not known about the reservoir against the the planning requirements for for infrastructure and equipment needs to be made very early on so the gated development process is a structured approach that stopped saying early on under underpins this whole this whole integrated approach and what it does is breaks the the decision-making and the technical analysis and the understanding of the asset into discrete phases and each phase progressively increases the level of detail that is required about the project in order to to make the next investment or operating commitments to the project so generally these phases are referred to as either an appraisal or moving from appraisal into concept concept conceptual engineering and once a and a concept has been involved there is then the move into detailed design or front-end engineering where the specification of the equipment is made and then finally into the execution phase where the the capital expenditure is actually made in each one of these phases there will be more information that will be coming out about the about the reservoir about the the project about the the opportunity so the stage gates are designed in order to allow the decision to be progressed but in the context of the information that's available and the commitment that's being made and this really is the the foundation of of this process but what's important to understand is that within each one of these phases there is a requirement to consider the entire project scope one of the key requirements of this is to understand that within each one of these phases there is a different understanding of the project as a whole there is a different understanding of the uncertainties that are inherent because as more information is acquired about the asset in terms of appraisal drilling or in terms of additional reprocessing as further commitment is made to the project moving into concept selection as more experiments are run on the the data that is available there is there is a reduction in the the level of uncertainty there will never be an opportunity to completely reduce or to engineer out all the uncertainty the the idea that you can engineer out all the uncertainties is just not feasible because the amount of analysis and data acquisition that you would have to undertake would be way too expensive so there there has to be a recognition that moving through each one of these phases there will be some inherent risk and the requirement is to be able to understand the impact of what is not known to be able to prioritize that and to be able to to build effective risk mitigation strategies or prioritized data acquisition as the process moves forward and implicitly in the sanctioned decision that that is is likely to be made the the sanction criteria there will certainly be a requirement to recognize the opportunity but there will also be requirement to quantify the risks that are being carried and how those risks are going to be mitigated so if this gated process can be can be executed in an efficient way then it can be it can address the requirements of flexibility so the idea is that if we can deal with the the integration requirement if we can look at how to scale the analysis to the objectives of each of those phases and to the available information so that it can be done efficiently if we can quantify the the impact of the uncertainty then we can start to manage that risk and be able to move through this process in a much more effective and efficient way so what I want to do is take a little bit of time to talk about those key elements or key attributes that are required to make this system efficient and to start with look at the the integration requirements so there is inevitably a lot of need for technical analysis within the development planning process the there is a requirement to be able to refine you know to define the the recovery strategy how is this reservoir going to be depleted how many wells are required where are those wells going to be placed what type of completion is required what type of surface facilities and what size is required to be able to handle the resultant production and what makes economic sense in terms of what actually will achieve some some positive outcome from this development and finally the it needs to be remembered that that these development plans generally have to be approved both by the by the investors but also by the the legislative oversight to ensure that those two divisions and reference to safety and the environment and and operation so the types of technical evaluation that are undertaken are things like reservoir characterization how much hydrocarbon is there where is it what pipe is it and this is a whole world in itself taken up by a number of experts with different expertise and with different discipline skills as a reservoir engineer I mean I'm being very focused on having got that reservoir characterization having understood something about the fluids how can this reservoir effectively be drained what are the drive mechanisms how fast can it be drained what are the well locations but it's not just a question of how fast and ultimately how much recovery you can get is what's the economic viability what's the optimal that can be achieved to balance the requirements of all the stakeholders and of the different objectives that are required there's also the the requirement to identify the impact of what isn't known what is not known about the reservoir what influence is that going to have what potential outcome could occur what is the what is the the operating efficiency of some of the equipment now what's its design life if you know is it is it designed to to function for the life of the asset so all these things have to be understood and have to be undertaken through through a technical evaluation but in order to achieve this this development there is this recognition that there are a number of different disciplines that are working to a great level of detail within their particular domains so that petrol physicists may be very exercised in terms of really understanding what the saturations are within the within the pore space there's the geomechanics as the geophysics for the structure there's the geochemistry in terms of the interactions there's the drilling requirements there's all of these things but but if if these experts work in isolation and they focus on coming up with absolutely the best analysis of the information that's available for their their asset it's extremely useful but it isn't necessarily relevant to the decision objective that's being made so while there is the the possibility of spending many years building an extremely high-resolution representation of the geology if if the decision that's being made is is about sort of gross displacements efficiency then maybe that that high high resolution model is is not what's needed so the idea is that all of the experts working on this planning process need to be working to a common objective and they need to be working at a scale that is relevant to the decision or to the objective objective that's being made because if they don't the problem is is that there's a breakdown of communication between the subsurface in many cases and the specification of the service equipment so an example is what is the impact of of a reservoir engineer for instance saying there's a 25% chance of an aquifer what does that actually mean to a process engineer trying to design the the operating tolerances of a separator vessel well it has it has a very significant impact but it may not be communicated very effectively so if there is a breakdown in the understanding of the interdependencies of these these uncertainties and of these requirements then they were there is inevitably unnecessary drilling either there are the wells are too many wells are drilled or more than likely not enough wells are drilled there's an over sizing of the facilities with the Associated cost overruns there are bottlenecks in the systems when there's been potentially under investment or there's there's the the the requirement for some sort of contingency is misunderstood and ultimately the project will will not will be suboptimal and there's the risk of failed contracts so in order to address this integration of all these different disciplines there are a number of things that have occurred over the years it used to be that these experts were focused into expert discipline departments so they would discipline silos where you know you were assigned to work within a reservoir engineering group for instance and there was a chief reservoir engineer and you focus very much on the discipline and the expertise and the skill of reservoir engineering there was a recognition that sometimes the studies that were undertaken were undertaken and it took too long went to a level of detail which was not appropriate to the decision that was trying to be made so there was a move towards asset themes to try and get all the different disciplines to be focused on the asset objectives rather than on the discipline objectives and this had some associated problems with it in terms of the the experts not having a peer group not being able to refer to colleagues with the same expertise and tending to work somewhat in isolation so there's been very much a move towards a hybrid system where there is a focus on asset teams but there is a matrix with with a discipline experts being reporting into a functional lead and this is pretty much where the industry is today so this organizational integration has been effective in starting to focus the disciplines on on the asset objectives the other aspect of integration that is is is important to this development planning processes a recognition recognition that there needs to be an integration over time so they're sometimes a tendency to design for the peak rates so equipment is designed to handle the maximum capacity but it tends to be suboptimal later in the field life so it's it's important to look at the field development plan not just as the requirements for the initial design base but for the phasing and look of the equipment over the entire life of the asset and that may well mean a reconfiguration of the equipment but if this is planned upfront and can be accounted for in the in the project economics there's there's much more opportunity to optimize the development so this integration over time is particularly important and finally there's the technical integration the integration of the technologies that are used in order to to under undertake the the analysis within the lead discipline silos so one of the most effective models and and one that's fairly universally adopted is is the application of a model an analytical or a numerical model that is used to be able to predict how things are going to perform so traditionally there's geological models which converted into reservoir simulation models to be able to have some predictive capability over time and and of importance the ability to run different experiments with those with those reservoir models in the predictive case there's also well models models of the the wellbore to be able to understand the lift and flow dynamics both within the wellbore and within the network models to be looking at the gathering system and the interactions between the different pipelines and and equipment there's the the process model to be able to look at the the processing of the facilities and ultimately there's the petroleum economic models traditionally all these have been undertaken by the discipline experts working pretty much in isolation and the technology generally has not been designed in a way that is easy to to pass the the output of one analysis into the input of another this tends to be done or tend to be tended to be done by the by the passing of things like profiles and spreadsheets so the requirement of the enabling technology that makes this this integrated approach that enables it is really having an integrated asset model an asset model that looks at the entire value chain of this project enables those predictive simulations to be made enables those realizations to be run so the the different outcomes can be evaluated the different risks can be understood but of critical importance the interdependencies between these difference domains can be fully explored and understood and accounted for so the integrated asset model needs to be able to accept models or simulations from the underlying experts to be able to work with the existing tools that they currently use to be able to aggregate those into some sort of a a process management system where the interactions between these models can be effectively and efficiently managed and if this can can happen if this can if this is done in a way that that the different resolutions and the different data frequencies can be incorporated then there is the opportunity to be able to to scale the analysis to the objectives and to be able to look across the full spectrum so that's really the requirement for for integration across the disciplines over time and really the requirement of the enabling technology so let's talk a little bit about the scalability of the of the analysis scaling it to match the objectives so within this gated development process there is move through the system to each stage gate and each one will have different requirements in the initial stages in the appraisal stage there is not an awful lot of information about the asset there's not an awful lot of information about the reservoir so there's a relatively low level of or low resolution that is required to address the type of questions that are going to be asked to meet the sanction criteria to move from appraisal to concept things like how much resource is in place what are the predominating structures where do we need to acquire more information what are the key uncertainties how do we mitigate those uncertainties as we move forward so the level of resolution that is required of that analysis is sufficient to be able to address the the decision gate criteria there is no point in taking a reservoir building a reservoir simulation model with 300 million cells in it because you can generate a numerical geological model based on the the 2d seismic so the technology will allow you to do it but it makes no sense to do it because it's not actually going to give you any more insight it's just going to take more time and time is really what you want to be working efficiently with so talking about the the application of the right tool let's take an analogy from from the medical world on the left hand side you've got an x-ray and you go to your doctor and you've had a fall and he suspects that you've got a cracked skull then maybe an x-ray is sufficient to determine whether you've got a cracked skull because the x-ray will allow you to to see the hard bone structure and based on that it's probably sufficient to be able to make a diagnosis however if you're getting continual headaches and it looks like you might have some sort of damage inside your head then there is the recourse to a CT scan now CT scan is a much more expensive much more involved applica assimilation of data so the doctor has to make a decision as to what is the appropriate tool for the symptom that you're that you have and you know that they have to balance the the time to make that diagnosis and the availability of funds to be able to make the diagnosis and the same is true in the in the petro technical world so again within the world of reservoir engineering and specifically in in with a view to the models that are available to the reservoir engineer if you move from the the x-ray equivalents of trying to define the the dynamic performance of a reservoir you have a material balance study which is a single dimensional very simple calculation of the the pressure response to the removal of fluid from from a closed system but it gives you no indication of the the dynamics of that fluid within the reservoir where it's going to flow how it's going to flow at what rate it's going to flow particularly so if you need to know that then you need to move up the resolution spectrum so you move up towards a numerical simulation which can be streamlined or into a black oil or then you may have to add more and more complexity more and more physics to be able to look at the Geo mechanics to be able to look at at and compositional and ultimately you may have to go to a very very high resolution because the mobility modification is is what's important and how that's distributed around the field is is key so the point is to be able to choose the right tool for the job realizing that more resolution is going to cost more and it's going to take more time so there is the opportunity to be able to work at multi scales so if you have a reservoir simulation the full field and you need to do a detailed design or the placements of some inflow control devices in a horizontal well you don't want to use your course scale full field model to do your high-resolution near wellbore design what you want to be able to do is take the full field model realize what the boundary conditions are in your area of interest pull that area of interest out refine your understanding increase the resolution be able to get more insight into the specifics of the fluid dynamics in that area rather than the gross dynamics of the of the reservoir use that to be able to design your completion and then be able to plug that back in in some sort of representative way back into the full field model so that the the simulation time is not compromised but you have increased insight into the into the process so the key here is to adopt more of a decision driven approach to to the analysis and one of the key things here is is to make this objective driven the importance of this is are the important that the key points or the most important aspect of starting a decision driven workflow is to make sure that everybody working on this problem understands what that objective actually is so to start out with a framing session where everybody gets together and understands what the criteria for the decision actually is and then work at a coarse scale to understand what the sensitivities to this analysis is likely to be understand what the key parameters are going to be so that the time can be focused on analyzing those rather than analyzing some other detail that may not have any impact on the decision may be scientifically interesting but it's it doesn't impact the decision so once the the key and the key parameters are stood that influenced the decision more focus can be made on those to understand their impact and and the the sensitivity around those and so a move to a finer scale to really understand those key parameters can happen once those are understood they can be they can be approximated into an appropriate scale full-field so the idea is that you can work through multi scales but but work towards the objective focus on what the objective is as opposed to the capability of the technology or the availability of data and this is a key point because certainly within reservoir simulation there has been a tendency to make the reservoir simulation model the repository of all information that is available about this field so it's all crammed into this reservoir simulation model which becomes very large very unwieldy and very slow to run and is therefore not appropriate for running multiple realizations to understand what the difference risk impacts are likely to be so just addressing the the scalability and moving on now to talk about risk because if we are working in an integrated fashion if we got some sort of an idea of the full spectrum and we want some idea of the interdependencies and we can work at an efficient rate in a scalable fashion we can identify the key uncertainties and what those uncertainties are likely to be in terms of the the project risks so there are a number of different types of risks and it's worth realizing that it's not just the in the Petra technical world it's not just the reservoir risk it's the impact of those risks across the spectrum be they economic risks be they political risks be they whatever but the focus very much here is on is on the the reservoir risks because these are in many ways some of the most undefined risks so reservoir risk essentially refers to the impact of the uncertainty in the interpretation of the reservoir and this is always going to be there because the decision to develop is going to happen very early on with a limited amount of reservoir data what confidence there is will be at the well the rest of it is interpretation its interpretation between the wells and its interpretation guided by things like seismic remote remote measurements and and an analysis so there is a high possibility that is equally probable that there are many different realizations of that reservoir which are which are possible particularly if you consider the example of a channel sand where the the high energy and the channels will have a very high influence on the the recovery and on the rate that's achievable from this field but the distribution of those channel sands is interpolated between wells guided by seismic so there is uncertainty in the the distribution the width and the makeup and continuity of those channel sands so that's an example of reservoir risk what what you want to be able to do is take that uncertainty be able to run multiple realizations of the predictive model accounting for the the probable distributions and understand what the range of possibility is going to be so if you can do that you can produce something as is illustrated on the right here which is a tornado plot which indicates what the most influential parameters on your objective are so in this case we're looking at oil in place and the most influential parameter is likely to be the distribution of porosity so the key point is that by understanding the impact of these parameters and by being able to prioritize them then we can focus on what is important to be able to analyze further to be able to understand and to be able to come up with a mitigation strategy around so the other aspect of this is that taking the as equiprobable reservoir realizations we want to be able to run different development scenarios against them to see which development scenario has the widest operating tolerance for the minimal cost in other words which design which configuration of production equipment and layout will give us the most flexibility to be able to deal with the inherent uncertainty and the range of uncertainty that were we're working with within the reservoir world so a very crude example of this is looking at the requirements of artificial lives and comparing that against some assumes distribution of of aquifer so the idea that there is an aquifer or there isn't an aquifer and compartmentalization so just a very simple example at looking at the operating range of different artificial lift mechanisms and how that range can be extended you know by the use of multiple lift systems or dual lift systems to be able to cover a wider range of uncertainty in other words to have more contingency and to be able to handle the the uncertainty so this is why the integration becomes really important finally the technology has to be able to present this data in a way that is meaningful to the decision-maker so it has to be able to communicate what the key influences are what the impact of those influences are and be able to visualize what the alternatives are so really that's just a requirement to make this feasible process so we sort of addressed the risk component so if each one of these can be can be undertaken in an efficient way there is the opportunity to to move this process into a more fast-track and more flexible approach because if we don't have to engineer out all of the uncertainty we don't have to spend some months and months going into high resolution reservoir simulations if we can actually work at an appropriate scale we can identify the risks we can we can prioritize what needs to be dealt with and what the mitigation plan is we can move through those stage gates much more efficiently and much more effectively and and this is really a key requirement so in terms of being able to fast-track this we need to be able to have effective ways of integrating and communicating between the disciplines so we need to have an environment that enables this integration we need to be able to choose appropriate techniques and tools to be able to to get insight into the prevailing physics and the prevailing reservoir conditions at the appropriate scale to be able to make the decisions if we can do it at the appropriate scale we can run multiple realizations and we can generate statistical approaches we can generate distributions of possibility and we can use these distributions of probability and possibility as a way to guide the management and the mitigation as we move forward into the the equipment selection and and the the phasing of the project and finally we need to be able to integrate all the information that this learned as we start building this out and update the the understanding as we start to go on to production so in terms of the technology requirements one of the key things is the continuity of knowledge one of the criticisms that's often made is that the exploration group will will be able to generate prospects relatively quickly but excuse me but the the handover to development is slows the process down and what tends to happen is is all the analysis that's undertaken in the exploration phase of understanding the regional charge mechanism the regional migration mechanism be the trapping structure and the sealing structure tends to be lost when it's handed over to the development group because they start again with building new models so this continuity of understanding is knowledge is key so as well as being able to to integrate in these models having scalable models allows us to continually update and rescale the model to the resolution that's required right the way from the exploration phase through to be the final investment decision and the ongoing management of the asset so again going back to an example from from Eni this is something that they are looking to do actively because they recognize that while they've adopted this structured decision-making process that gives them the the consistency and and the rigor that they need they're they're running into issues of what they would like to be able to do is they'd like to be able to fast track these projects bring the the first oil forward have more flexibility to be able to respond to market opportunity as it presents itself I want to be what they're exploring here is how they can start to concatenate how they can start to move some of these phases under each other so while there is still going to be a stage gate decision some of the pre-work can start to happen so that those decisions can be made earlier on and more efficiently with a better understanding particularly of the risk the risk quantification and the associated mitigation strategies which will enable these projects to move forward so just trying to summarize those technology requirements what we're looking for from the the technology to be able to to enable this process in an effective way is to have the the physics that's available to represent what's happening in the field to be able to run those at a scale that is appropriate for the decision and for the time that's available to to do the analysis Bo because we're efficient in running that to be able to run scenarios and and result and realizations to understand the in act of the uncertainty and to be able to effectively communicate the the interactions and the interdependencies between the different disciplines to be able to integrate this into the gated decision process at the appropriate scale and ultimately lead to an integrated development plan with a port process perspective so all these things need to be pulled together both in terms of organization and in terms of enabling technology so just to summarize the adoption of the the gated decision-making process is being commonly applied now but what is key to make that effective is an integration of all the experts and the expertise within each one of those phases so that the interdependencies are fully understood to be able to scale the analysis to the particular objective that is being asked so to run analysis at the resolution that is required to make the decision but is being asked to be able to work efficiently so that different realizations a number of multiple realizations can be run in an effective time so that the uncertainty and the impact of that uncertainty can be quantified and prioritized into a mitigation a risk mitigation strategy and ultimately with an understanding of the impact of that uncertainty and and of the end of the opportunity this process can be progressively fast-tracked and made more flexible and more efficient so with that I'll hand over to to Joseph to take any questions that that you may have thank you no thank you Mike for the very insightful presentation I'd like to remind the audience if you have any questions use the green button on the left side of your screen and submit your questions in that way and we'll read them out in an orderly fashion the first question we have here is around the hybrid organization so you discuss the benefits around the hybrid organization how do you work to build an environment that can work in this way okay well I mean this is this is really a organizational undertaking but I guess the the first the first recognition is the importance of of the integration of of the different disciplines and I think there's a recognition there certainly it can be achieved with the with the work processes but it is it's facilitated by an organization where people are working together in in a common theme but still have access to the expert peers that they may need to be able to get clarification or bounce ideas off of their particular discipline requirements their particular expertise thanks Mike next question here is around the design for surface facilities can you expand on more on the need to design surface facilities where the field life as against the peak rate production especially in projects where cost recovery is critical sure okay that's a good question and it's it's certainly a challenge because one of the the requirements is to be able to to look at what the what the most effective process facility is or service facility is but but but look at it over the over the life of the asset so if there is a recourse to a predictive simulator an integrated asset model then it can be can be run with the difference equipment sizing to look at what impact that has both in terms of Canada except P traits this P trait need to be turned down and the plateau extended how does that I cannot how does that impact the economics so again it's it's taking recourse to to an integrated asset model as the basis our design rather than just being handed a peak rates by by the sub service department and and being told that that's the the required handling capacity so again this communication and a perspective right the way across the value chain and over the life of the asset is is is particularly key and and this an integrated asset model really is the enabler for that next mic so if there's any other questions please please submit them through the chat window I was curious Mike just going from from a design to to operation and handling the frequency of data and that type of thing it seems like you're able to design a lot of a lot of this this process and an organized integration in the design phase but then taking its operation the frequency of data seems to it could be a complicating factor so how do you take that into the count with the the skin decision process and operating a field well I think again it comes down to being able to set up the the production management system at a resolution that's appropriate for the for the particular challenges that are being faced and again you know the approach needs to be what is the most crucial data what's the most influential data not you know I can acquire all this data how do I use it all so the again this this idea that you focus the requirement for the analysis for the management's and and you drive you use that to drive what data is requirement what frequency it's required there is also the the idea that you're going to be able to work at multi scales so an operational decision certainly has more immediacy in terms of how it needs to be made at it it's much more localized in many cases but what you need to be able to do is have some sort of a contingency plan so for instance if you get an unforeseen shutdown in some part of the the gathering system that at least you've run scenarios with your your integrated model that you can stand what your best option is in terms of what remedial action you need to take in terms of switching production to to a different source what impact that's going to have because you've had the opportunity to to simulate that before so being able to switch between the scales of the operational scale under the of the strategic scale thanks Mike our next question here is around water injection so what are some of the design factors considered for water injection in terms of the reservoir or in terms of the production equipment so in terms of the reservoir obviously it's going to be you know the amount of water that needs to be injected to affect the displacements or to achieve the level of voidage to maintain pressure that that's required in terms of the selection of the production equipment it's the the the filtration and the the type of treatments of the water that's being injected to ensure that there's not there's not subsequent production problems with with fines you know or precipitation or sulfate reducing bacteria creating h2s so again with recourse to an integrated asset model these type of things can can be evaluated you know what's the impact of you know having one hundred and twenty percent voidage requirements on the sizing of of injection lines and the injectivity that's required of the wells and how many injection wells are there again the the use of a an integrated asset model will we'll give a lot of insight into that thank you Mike yeah I think it's quite a broad topic that can be explored quite deeply from combustible surface and surface absolutely there's another question here around high resolution data and the question is please stress the need to gather a very detailed high-resolution data on the distribution of reservoir phases potential baffles and barriers in the first exploration wells it may be years before you have a well capable of getting measurements later so I think this has to do with the amount of data you have an exploration exploration phase short no drama yeah again that's that's a key point but obviously there's there's this trade-off between the the exploration budget that's available and the amount of data that can be acquired but but certainly as somebody works in the petro technical world this is the more information that's available the more can be you know the more you can select to understand what's what's appropriate and again you may spend an awful lot of time at wig time understanding sort of interference effects and determined that actually the the baffles are not the key driving mechanism that the distribution of will ethology is not actually influencing the flow dynamics that much so I know it's something that needs to be balanced so again as you move through that appraisal stage if it becomes evident that that there is a lot of heterogeneity in the reservoir in it and and you look at scenarios with you know with the core scale model that indicate that actually the liver logical distribution is going to be important then you can prioritize that as something that needs to be invested in moving into the next stage so thank you Mike we'll take just one more question before we close out the session if there are any other questions please don't hesitate to submit them and we can answer those offline separately but the last question here that we'll take for Mike what happened here is around bottleneck in in in OCS so I guess you can we can run your experience or your opinion on the matter but what is it currently a bottleneck and most NoCs organization or technology stack software hardware or deployment of integrated workflows as a subject around what is the major bottleneck that you've seen in in OCS you mean national well commercial oil company it's an organizational challenge or a technology challenge to implement something like this I guess in my experience it's there's there's an organizational change that needs to happen I mean a lot of the national oil companies have a great sort of depth of expertise but it's very much organized into into expert departments and and certainly moving towards the asset type approaches is something that that is starting to happen but maybe it's not happening it happening as as fast as it is in some of the independence but I mean it's it's certainly an opportunity that bit is out there so great well thank you Mike thank you for the great presentation we've just about run out of time for today's webinar we'll address any of the questions that weren't addressed in the session today separately and I'd like to advertise that we'll have a recording of this presentation put on the upstream technology leadership webinar webpage following this broadcast so please if you're interested in getting recording goes there we'll also have other series around enhanced oil recovery in October and one about high resolution simulation in November so stay tuned for those thank you again Mike for the time and a very great presentation and thank you all for participating in today's upstream technology leadership webinar okay thank you

Channel: Schlumberger Software

Views: 10,444

Rating: 4.8805971 out of 5

Keywords: Gated Decision Process, Oilfield Development, Scalability, Risk, Field Development Planning, Reservoir Engineering, Oilfield Life Cycle, Asset Model, Pore-to-Process, Technical Integration, Integration

Id: ApHn02iUQKI

Length: 65min 12sec (3912 seconds)

Published: Wed Oct 05 2016