Optimal Development Plan Research Articles

Field development optimization in mature oil reservoirs using a hybrid algorithm

Many optimization schemes have been proposed to simultaneously optimize various variables such as well locations, well operation schedules, well types, and the number of wells. However, most of these approaches often focused on fixed well type without considering conversion of existing wells.This paper proposes a new optimization for mature oil field development. Since converting from producers to injectors is a common practice in mature oil field, we have to optimize simultaneously type conversion schedules of all existing producers and infill wells as well as the number of infill wells, their locations, and operation schedules. We propose a new hybrid algorithm, which combines differential evolution (DE) algorithm and mesh adaptive direct search algorithm (MADS) to solve our optimization task.By considering well type conversion, it will increase the complexity of searching space but provide more realistic and optimal development plan. We demonstrate it in 2D synthetic and 3D PUNQ-S3 reservoirs for optimal field development. The proposed optimization considering well type conversion provides higher net present value than the fixed well type optimization in the both cases. The hybrid algorithm also shows better search performances than DE and MADS algorithms. Thus, we conclude that consideration of well conversion schedules is necessary for economical field development scenarios in mature oil fields.

Technology Focus: Heavy Oil (March 2017)

Technology Focus Over a 6-month time frame in 2016, I was able to attend three SPE conferences on heavy oil in different countries spanning three continents (Canada, Peru, and Kuwait). Despite regional differences in the applications, potentials, problems, and technological needs, the common theme in all conferences was “low cost.” Cost optimization in heavy-oil production was discussed from technical and economic perspectives, not only in the technical sessions but also in numerous panel discussions. Such optimization can be achieved through numerical modeling to suggest general optimal strategies and development plans or by using proper real-time data acquisition (production optimization) for prompt decisions while operations are ongoing. This requires continuous monitoring of the processes as seen in many steam-assisted-gravity-drainage operations or other types of steam-injection applications. I selected two papers about advanced monitoring techniques as suggested reading in this issue. Moreover, chemical and nanomaterial additives to water and steam have received a great deal of attention. Low-interfacial-tension (microemulsion) and low-salinity injection in heavy oils in sands and carbonates and wettability alteration in carbonates were common topics at conferences held over the past year. I selected one review paper for additional reading and one experimental work as a summary paper on this subject. Apparently, modeling efforts on advanced (but unconventional) technologies such as electromagnetic heating have continued. You will find a detailed mathematical analysis of the process in one of the papers summarized. Despite the recent economic downturn, we were able to hear the outcome of current field practices at pilot or demonstration scale. Papers detailing small-scale cyclic-steam-injection applications in Kuwait and Oman were worth reading, and one article on this specific subject is included here. Considering these activities in the Middle East, effective transfer of technologies from North America to that part of the world will become highly critical in the near future. Recommended additional reading at OnePetro: www.onepetro.org. SPE 181160 State-of-the-Art Review of the Steam Foam Process by Eric Delamaide, IFP Technologies Canada, et al. SPE 180732 An Integrated Probabilistic Work Flow for Primary and Thermal Performance Prediction of a Large Extraheavy-Oil Field by Raushan Kumar, Chevron, et al. SPE 181431 Horizontal Steam-Injection Flow Profiling Using Fiber Optics by Mahdy Shirdel, Chevron Energy Technology Company, et al. SPE 180726 SAGD Production Observations Using Fiber-Optic Distributed Acoustic and Temperature Sensing: SAGD DAS—Listening to Wells To Improve Understanding of Inflow by Warren MacPhail, Devon, et al.

Oil Reserves Evaluation and Field Development plan of Hakim Oil Field in Libya

The main objectives of this research are to estimate the oil reserves and set a development plan for Hakim Field in Libya, using three methods for calculating OOIP which are Volumetric (Monte Carlo), Decline curve analysis (DCA), Material Balance Equation, and establish the optimum development plan for Hakim field. Results showed that the OOIP of Hakim Field, calculated by volumetric method done through Monte Carlo tool given 90.2 MM STBO for Proven Reserves (1P) , 115.5 MM STBO for Probable reserves (2P) and 147.0 MM STBO for Possible reserves (3P). While OOIP estimated by Decline curve analysis given 82.4MM STBO for Proven Reserves (1P) , 102.8MM STBO for Probable reserves (2P) and 114.9MM STBO for Possible reserves (3P), and 112.18 MM STBO for Probable reserves (2P) by Material Balance. In addition, 14 prediction scenarios have been applied on the Material Balance Model to establish the optimum Field development Plan, results showed that from simulation model the optimal scenario is 8 Producing Wells, 4 Water Injector Wells and 8000 BWPD.

An efficient approach for optimizing full field development plan using Monte-Carlo simulation coupled with Genetic Algorithm and new variable setting method for well placement applied to gas condensate field in Vietnam

This paper presents an efficient technique to optimize a gas condensate field development plan under economic uncertainties. Many studies have been conducted to optimize development plan but mostly limited to oil field under fixed economic environments and required huge number of simulation runs. It is proved that black oil model can be a reasonable alternative of compositional model to complete field development optimization within acceptable period when reservoir pressure is higher enough than dew point pressure. This study implements Monte-Carlo simulation to Genetic Algorithm to assess economic uncertainties while optimization procedure is being performed and to avoid duplicating whole optimization procedure by changing economic assumptions. An idea for setting optimization variables for well placement is also introduced to reduce required number of simulation runs. A real field application confirms that the technique can be applied to optimize a gas condensate field with contractual gas sales obligation, and the idea plays a key role to find the optimized solution with limited resources by reducing the number of simulation runs required during the optimization procedure. The proposed technique can be applied to optimize not only full field development plan but also reservoir management plan and it will be helpful to improve economics of all kinds of E&P projects under lots of uncertainties.

Quantitative estimation of permeability enhancement, production and depletion from microseismic data

It is a known fact that cost efficiency is the number one priority across the industry, perhaps even more so in today’s price environment. Operators are seeking technologies to improve profitability for unconventional field development. Getting a reliable estimate of production within days of completing an unconventional well is every operator’s dream. Armed with this knowledge operators would be able to evaluate the effectiveness of treatment and well spacing strategies without having to wait for months of actual production, allowing for them to arrive at an optimum development plan in a more timely fashion. In this article we demonstrate that microseismic monitoring, taken as an insitu, real time field observation of the completion of a well that integrates all the effects of rock properties, tectonic stresses and treatment parameters enables an estimate of well productivity within reasonable limits. In this method, microseismic data is used to describe a deterministic discrete fracture network model, differentiating between propped and un-propped fractures and further defining a fracture intensity in a given rock volume. This fracture intensity is translated into a measure of permeability enhancement, both magnitude and distribution, achieved through the process of hydraulic fracturing. Through reservoir simulation using this more complete model it is possible to estimate each well’s current and future productivity and the reservoir pressure depletion as a function of time. Current practices rely on unrealistic planar fracture models leading to to inaccurate predictions of unconventional wells’ production and drainage patterns. The approach presented here explicitly honours the microseismic measurements and provides a realistic representation of the induced fracture geometry and thus improved production and drainage estimates. These early production predictions are available within a few days after a well’s treatment, eliminating the typical 6-to-12-month waiting time for production results. The ability to create a model that is consistent with actual production, as shown in the case histories presented here, suggests that uncertainty is sufficiently constrained through the workflow outlined in this article.

Strategic optimization of the oil sands development with SAGD: Drainage area arrangement and development planning

The majority of the oil sand deposits in Alberta Canada can only be extracted using in situ methods, mainly the Steam Assisted Gravity Drainage (SAGD). SAGD project consists of Central Processing Facility (CPF) and Surface Pad (SP) situated surface and Drainage Area (DA) consisting of multiple injector and producer well pairs situated subsurface. DA placement is crucial in ensuring that maximum amount of bitumen is extracted. In this work, an optimization framework is developed to plan the development of DAs. The first step aims to obtain a compact DAs arrangement by maximizing the amount of extractable bitumen. In the second step, a Mixed Integer Linear Optimization (MILP) model is developed to arrange the multiperiod development plan of the DAs. The proposed method is applied to a case study with multiple DAs for arrangement and the results demonstrate that the method can effectively generate a good DA layout and an economically optimal development plan that maximizes the Net Present Value (NPV).

Smart Well Pattern Optimization Using Gradient Algorithm

For a long time, well pattern optimization mainly relies on human experience, numerical simulations are used to test different development plans and then a preferred program is chosen for field implementation. However, this kind of method cannot provide suitable optimal well pattern layout for different geological reservoirs. In recent years, more attentions have been paid to propose well placement theories combining optimization algorithm with reservoir simulation. But these theories are mostly applied in a situation with a small amount of wells. For numerous wells in a large-scale reservoir, it is of great importance to pursue the optimal well pattern in order to obtain maximum economic benefits. The idea in this paper is originated from the idea presented by Onwunalu and Durlofsky (2011, “A New Well-Pattern-Optimization Procedure for Large-Scale Field Development,” SPE J., 16(3), pp. 594-607), which focuses on well pattern optimization, and the innovations are as follows: (1) Combine well pattern variation with production control to get the optimal overall development plan. (2) Rechoose and simplify the optimization variables, deduce the new generation process of well pattern, and use perturbation gradient to solve mathematical model in order to ensure efficiency and accuracy of final results. (3) Constrain optimization variables by log-transformation method. (4) Boundary wells are reserved by shifting into boundary artificially to avoid abrupt change of objective function which leads to a nonoptimal result due to gradient discontinuity at reservoir edge. The method is illustrated by examples of homogeneous and heterogeneous reservoirs. For homogeneous reservoir, perturbation gradient algorithm yields a quite satisfied result. Meanwhile, heterogeneous reservoir tests realize optimization of various well patterns and indicate that gradient algorithm converges faster than particle swarm optimization (PSO).

Концептуальная модель принятия решений по развитию персонала машиностроительного предприятия

The article deals with improving the system of information processing in order to ensure the development of the management staff. On the basis of a systematic approach and the management cycle Deming-Shuhart, held decomposition of the system and proposed a generalized conceptual model. Analysis of the generalized conceptual model allows two main functions of the system of information processing: assessment of the level of readiness of personnel to implement the core business and the formation of an optimum development plan for staff. Consideration of these tasks within the analytical strategic planning reveals the basic of features. Assessing the level of preparedness of personnel is seen as a direct solution to the problem of planning, and odds-mation of the optimal plan staff development within the inverse problem solution planning. This study allows to form the structure of an information processing system.

System of Systems Model for Analysis of Biofuel Development

AbstractThis paper presents a system of systems (SoS) Biofuel model considering the interdependency among the systems involved in biofuel development, including biofuel refinery location, transportation infrastructure, agricultural production and markets, environment, and social communities. The model provides the optimal infrastructure development and land-use allocation for biofuel production in a region considering socio-economic and water quality and quantity effects. The optimal development plan quantifies economic and hydrologic outputs and specifies biofuel refinery locations and capacities, refinery operations, land allocation between biofuel and food crops, optimal shipments of products and feedstock, and transportation infrastructure. The model is formulated as a mixed integer linear program (MILP) and is solved by an algorithm developed specifically to cope with the large size of the optimization problem. In addition to the development of the SoS-Biofuel model, this paper demonstrates the funct...

Biobjective optimization for general oil field development

Abstract The optimization of oil field development and production planning typically requires the consideration of multiple, possibly conflicting, objectives. For example, in a waterflooding project, we might seek to maximize oil recovery and minimize water injection. It is therefore important to devise and test optimization procedures that consider two or more objectives in the determination of optimal development and production plans. In this work we present an approach for field development optimization with two objectives. A single-objective product formulation, which systematically combines the two objectives in a sequence of single-objective optimization problems, is applied. The method, called BiPSOMADS, utilizes at its core our recently developed PSO–MADS (Particle Swarm Optimization–Mesh Adaptive Direct Search) hybrid optimization algorithm. This derivative-free procedure has been shown to be effective for the solution of generalized field development and well control problems that include categorical, discrete and continuous variables along with general (nonlinear) constraints. Four biobjective field development and well control examples are solved using BiPSOMADS. These examples include problems that consider the maximization of both net present value and cumulative oil production, and the maximization of both long-term and short-term reservoir performance. An example that highlights the applicability of biobjective optimization for field development under geological uncertainty is also presented. This usage of BiPSOMADS enables us to maximize expected reservoir performance while reducing the risk associated with the worst-case scenario.

Synthetic Evaluation of Oilfield Development Plans Based on a Cloud Model

AbstractIn the process of evaluating the oilfield development plans, there always exist uncertainties in data, weight assignment, and scheme grading. In this article, an improved evaluation method is introduced to tackle the uncertainties based on a cloud model. The indicators of a development plan are input into this model and a contribution score cloud is obtained for evaluation. The evaluation clouds of all the development plans are sorted by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), with the weighted hamming distance. Then we can get the optimum development plan according to the order. In this model, the randomness and the fuzziness are both taken into consideration, and the feasibility and validity are verified by an example.

Three dimensional modeling for predicting sand production

Abstract In oil industry, the production of sand particles associated with the reservoir hydrocarbons becomes one of the most common problems a well may experience during reservoir lifetime. To prevent this problem, oil companies sometime unnecessarily install sand control equipments without predicting or evaluating sand potential which in turn increases operating cost and decreases well productivity. Therefore, it is essential to predict under what production conditions (wellbore flowing pressure or production rate) sanding will occur and when sand control is needed. This paper presents a new 3D analytical model that can predict sanding onset from openhole wellbores. The model estimates the critical wellbore pressure below which sand production is expected. Mogi–Coulomb failure criterion in conjunction with linear poroelastic constitutive model is utilized to develop the model. For vertical wellbore a closed-form solution is achieved. Another sanding stability model using the classical Mohr–Coulomb failure criterion is developed to point out on the impact of the intermediate principal stress on sand production prediction. For non-vertical wellbore, a computer program in Mathcad is utilized to predict sanding onset pressure. Analytical solution is then derived to obtain the optimal well path where the potential of sand production is minimized. To verify the models, real field cases from published literature and an Omani oil field have been simulated. The model generated results that compare well with the actual field observations. The developed model will allow petroleum engineers to predict sanding onset pressure from openhole wellbores to come up with the optimal field development plan and well completion design. It can also be utilized for cased and perforated wells as an approximation tool.

Modeling and Computational Strategies for Optimal Development Planning of Offshore Oilfields under Complex Fiscal Rules

The main goal of this paper is to extend a simple NPV (net present value) based optimal oilfield development planning model to include complex fiscal rules. In particular, we consider a recently proposed multifield site strategic planning model for offshore oil and gas fields as a basis to include the generic fiscal rules with ringfencing provisions. The reduction of this model to a variety of contracts is explained. The results on the realistic instances show improved investment and operations decisions due to the explicit consideration of the fiscal terms during planning. However, as the model can become computationally very expensive to solve with the extension to sliding scale fiscal rules, we also provide some reformulation/approximation techniques and solution strategies that yield orders of magnitude reduction in the solution time.

Power Development Planning Models in East Africa

Power system planning can be widely viewed as consisting of three main areas: demand forecasting, generation capacity expansion, and transmission expansion planning. Power planning involves the determination of an optimal or least-cost development plan to meet forecast demand. This article examines power development planning and expansion, and planning models used in East Africa. It focuses on the planning process in three countries, Kenya, Uganda, and Tanzania, which historically interrelate in their economic activities across various sectors. The article seeks to give insight into power development planning with regard to a regional perspective, modeling and simulation, and trends and practices. It also seeks to elucidate the challenges and opportunities of integrated generation expansion planning.

Economic Comparison of Intelligent Wells in Simultaneous Production of Oil and Gas Reserves From Single Wellbore

Summary Maximizing oil recovery in thin and ultrathin (less than 30 ft) oil columns is a challenge as a result of coning or cresting of unwanted fluids into the wellbore in both vertical and horizontal wells. There is considerable oil left behind, above the well completion in the reservoir. This may also occur in horizontal wells when bottom- or edgewater encroachment or invasion takes place. The development of the gas resources from these reservoirs is a major challenge because regulators want an optimal development plan for the oil rim before project approval is made. This can delay upstream gas supply to liquefied-natural-gas (LNG) projects and grind down project value. A smart development strategy has been proposed for the development of these challenging reservoirs. This involves the use of intelligent multilateral wells in simultaneous oil and gas development; the first (top) horizontal-lateral-well legs of the multilateral well will be completed at the crest of the reservoir in the gas cap. The second (lower) horizontal-lateral-well leg will be completed just above the gas/oil contact (GOC). Extensive numerical reservoir-flow simulation has been used to demonstrate the ability and possibility of using a single wellbore for simultaneous oil and gas production. This proposed development strategy will provide high impact on the asset of such oil and gas reservoirs by providing a cost-effective-technology solution. The numerical-simulation results show that the intelligent multilateral well will significantly improve the overall cumulative production of gas and oil from a thin oil reservoir with a large gas cap compared with conventional wells and also provide the opportunity for automatic gas lift for low-gravity crude (°API). This paper (1) presents the use of intelligent multilateral wells to produce oil and gas from the same wellbore simultaneously in the thin oil reservoir and (2) provides information on the delay and reduction of excess production of unwanted fluids (water) during oil and gas production from thin oil reservoirs using intelligentwell technology, including cost effectiveness.

Prediction of stratigraphic compartmentalization in marginal marine reservoirs

Abstract Marginal marine depositional systems exhibit stratigraphic reservoir compartmentalization potential at three hierarchical scales. At each of these scales, stratigraphic compartmentalization potential can be related to the dominant depositional processes and accommodation:coarse sediment supply ratio (A/S) that are acting at the time of deposition. All three orders of compartmentalization potential must be considered in order to define optimal field development plans and completion strategies. The lowest order of compartmentalization is usually at the inter-parasequence scale. The parasequence is represented by a conformable succession of strata separated by marine flooding surfaces and as such it generally defines the basic flow unit in marginal marine systems. In systems tracts associated with relatively high A/S ratios, for example late Lowstand, Transgressive and early Highstand (steeply rising shoreline trajectories), vertical compartmentalization potential is relatively high because of the enhanced preservation potential of flooding surface shales under these conditions. In systems tracts associated with relatively low A/S ratios, for example late Highstand, Falling-stage and early Lowstand (flat, slightly rising and falling shoreline trajectories), vertical compartmentalization potential of parasequences is reduced because the potential for erosion of flooding surface shales by overlying deposits is high and hence potential for vertical sand–sand contact between parasequences is enhanced. The second level of compartmentalization hierarchy is the inter sand-body scale. Individual sand bodies are defined within parasequences. The lateral connectivity of these sand bodies is a product of the dominant depositional processes active at the time of their deposition (wave, tidal, fluvial). Wave-dominated systems tend to produce more laterally continuous sand bodies, fluvial-dominated systems more laterally restricted sand bodies and tide-dominated systems both laterally continuous and laterally restricted sand bodies. Vertical compartmentalization potential of these reservoir sand bodies is related to A/S regime. In high A/S regimes, sand bodies are more likely to be disconnected or compartmentalized. In low A/S regimes, erosional amalgamation of sand bodies is more likely thereby leading to lower compartmentalization potential. The third order of potential stratigraphic compartmentalization is the intra sand-body scale. This scale is represented by intra sand-body heterogeneities such as dipping or horizontal shales, carbonaceous-rich beds or laminae, shale abandonment plugs of channels and carbonate concretions. In high A/S regimes the preservation potential of these heterogeneities is relatively high leading to an enhanced potential for intra sand-body compartmentalization. Lower A/S regimes result in a greater likelihood of lateral and vertical erosion of these heterogeneities leading to a higher potential for reservoir connectivity.

System development planning using readiness levels in a cost of development minimization model

AbstractThe purpose of this paper is to describe a methodology that enables systems engineers or program managers to formulate a system‐wide optimal development plan in order to facilitate monitoring and evaluation of the development process in terms of the actual readiness of the system. It proposes the use of the System Readiness Level (SRL) scale to measure the maturity of a system composed of technological elements, which are being developed based on cost‐driven strategies (as opposed to time‐to‐market‐driven strategies). A constrained optimization model is used to identify which critical technology elements and integration links can be matured to which levels at a particular time such that the development costs are minimized while a targeted SRL value is attained on schedule. While the algorithm does not necessarily reduce the total cost of development, it is able to find the minimal amount of expenditures which will achieve the desired maturity level during the earlier part of the development process. Essentially, it shifts the rest of the expenditures towards the latter part of the development during which model‐based integration and testing procedures which have been suggested by others can be applied to reduce costs and time further. This can be a useful option to have when there is substantial uncertainty with the system due to its high novelty and technological content. As a value added approach, the model gives the systems engineer the information needed to understand what a delay may mean to development, so a more informed decision can be made. The paper concludes by discussing the possible use of the optimal development plan to monitor and control the progress of systems under development. © 2009 Wiley Periodicals, Inc. Syst Eng

Investment optimization on port’s development by fuzzy integer programming

In this research, the main purpose is to formulate a model to determine the optimum investment on port development from national investment prospective; on the other hand, costs and benefits are calculated from consumer and investor’s viewpoint. The formulated model is an integer-programming model. The emphasis is on how to formulate an investment optimization problem where cargo operation, investment costs, cargo-handling capacity, cargo transportation network, and the world maritime fleet constraints are included. Fuzzy numbers are used for cargo forecast study results. The output of the model is the type of design ships and design berths which are needed in each sub period, so that the port planner (the government) will find out the optimum development plan of port in each sub period when there is uncertainty in cargo handling forecast (fuzzy numbers).

Optimizing Brownfield Redevelopment With Decision/Risk Assessment: Case Study

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 87047, "Optimizing Brownfield-Redevelopment Options Using Decision/Risk Assessment: Case Study - Bokor Field, Malaysia," by B. Wongnapapisan, SPE, S. Flew, SPE, and F. Boyd, SPE, Schlumberger, and Z. Hassan, Petronas Carigali Sdn. Bhd., prepared for the 2004 SPE Asia Pacific Conference on Integrated Modeling for Asset Management, Kuala Lumpur, 29-30 March. Revitalization of the Bokor field was affected by many surface-facility constraints as well as the subsurface complexity of laminated stacked reservoirs. These complex problems required use of an integrated multidisciplinary team method that used a decision- and risk-assessment (DRA) approach to screen development options. Introduction Field redevelopment requires identification of system bottlenecks and proposals to remove them, but, often, only the facilities level is considered. In proposing a revitalization plan for the Bokor field, the team developed a decision-making process to select an optimal development plan that would solve the constraints while minimizing unit technical operating cost (UTOC) and maximizing production. Often, brownfield redevelopments are limited to maximizing existing facilities (e.g., well slots or the processing plant). In the case of Bokor, essentially no additional oil could be produced because of a lack of gas lift and export compression. Thus, an approach was required that solved the existing bottlenecks and provided sufficient additional capacity to sustain a cost-effective revitalization plan. The process had to be iterative and assess the risks and uncertainties of each approach as well as the economic effects. The solution considered each reservoir target on a discounted-cumulative-oil basis, producing a ranked list of opportunities that could be added together to form any development scenario. Rather than running a reservoir simulation on each development case, multiple facility-development options were evaluated quickly. Each development scenario then was analyzed with a tornado chart, to prepare a decision tree that yielded the most likely outcome. This approach allowed options as diverse as subsea tiebacks or fully integrated platforms with many electrical submersible pumps (ESPs) to be risked and ranked equitably within a reasonable time frame. The full-length paper details the comprehensive multidisciplinary integration process required for brownfield redevelopment by use of a DRA approach for screening, ranking, and evaluating the redevelopment options and eventually selecting the most appropriate option. The existing facilities comprise five main structures: three drilling platforms, a production-station structure where the liquid-production separation and handling process takes place, and a gas-compression structure for gas lift and export. The Bokor field is interlinked with the Betty field for gas import (very high pressure, high pressure, and low pressure), the Baronia field for gas export (gas from Bokor and Betty), and the Bakau field for liquid export.

Development moratoria

Under a strict no-takings rule governments can regulate development timing only after evidence of an externality arises. Regulation remains a threat until (or if) such evidence arises, thereby hastening optimal development plans for all land in the spatial market. On the other hand, the effect on capital density varies systematically following demand growth conditions at different locations. Further, vacant land that does not generate the externality is developed more rapidly than is efficient ex post and its capital density systematically affected. The efficiency gap is greater both for land with a greater risk of being associated with the externality when vacant and the longer the threatened moratorium.