As an evolution of well recognized standards for projects assessment, planning and optimization; such as the FEL (Front End Loading) methodology proposed by IPA and the LCCA (Life Cycle Cost Analysis) powered by ISO; and also as a customization for E&P projects applications; R2M has developed its own approach, of stochastic nature, based upon Probabilistic Risk Analysis, Uncertainty Management and Reliability Engineering, named E&P ISAVAM® (E&P Integral Stochastic Asset Value Assessment Methodology).
E&P ISAVAM® allows to:
All this with the objective of generating plans aimed at ensuring the robustness of the business, emphasizing the reduction of production losses, optimizing the reliability of processes and maximizing the integrity of employees, production facilities and the environment.
The differentiating elements of E&P ISAVAM®:
ISMWells® is a E&P ISAVAM® branch that specializes in the assessment, planning and optimization of Well Projects; which are the basis for E&P projects.
ISMWells® is an evolution of internationally recognized standards for assessment, planning and optimization of projects; such as FEL (Front End Loading) proposed by IPA and LCCA (Life Cycle Cost Analysis) powered by ISO. It has been designed by R2M, integrating Probabilistic Risk Analysis, Uncertainty Management and Reliability Engineering techniques; into a methodology customized to the particular difficulties and challenges of Wells Projects.
The methodology; with stochastic basis, requires the selection of representative statistical samples based upon the right choice of homologous or representative wells; which must take into account concepts such as "geologically equivalent location" "equivalent program", "equivalent technology" and "equivalent completion". It also incorporates Bayesian techniques for the treatment of "Expert Opinion".
The distinguishing features of MEIPO® are:
Given an operational program of well interventions associated to an E&P project: MEOSIP® allows you to find the best combination and the optimal sequence for such activities, (Drilling, Major Repairs and Minor Repairs), aiming to maximize returns with a tolerable level of risk; to meet legal obligations and budgetary constraints and to achieve compliance with production goals and incorporation of reserves.
The differentiating elements of MEOSIP® are:
The most important benefits associated to MEOSIP® are:
SPAVAM® generates a tailored made plan to develop a production asset; suited with technically feasible, economically profitable and budget wise affordable actions; aiming to ensure
SPAVAM® is an evolution of recognized standards for projects assessment, planning and optimization; such as FEL (Front End Loading) proposed by IPA and LCCA (Life Cycle Cost Analysis) powered by ISO. It has been developed by R2M taking into account the particular difficulties and challenges of Exploitation Projects.
The key differentiators of SPAVAM® are:
SEAVAM® is the E&P ISAVAM® branch specialized in exploration assets. It is a fully stochastic approach developed to assess and to optimize exploration projects integrated by multiple exploration opportunities, considering geological dependence among them.
SEAVAM® integrates Probabilistic Risk Analysis, Uncertainty Management and Reliability Engineering techniques in a unique approach that allows:
SEAVAM® generates tailored made strategies to develop an exploration asset; suited with technically feasible, economically profitable and budget wise affordable actions; pointing to
The key differentiators of the proposed methodology are:
O&G Companies, all over the world are facing:
This implies business more complex and with less margin that require strategies to maximize profitability and value added in a context of creativity, innovation and high-tech.
This situation requires a rigorous strategic planning process, driven by a flexible process of optimization, that not only must be able to synchronize its performance with the dynamics of E&P business; but also it must be a standardized, traceable and auditable decision making process.
To address the above mentioned challenges; R2M has developed MSMOIP®E&P, which distinguishing features are:
PFSOM® emerges with the need of optimizing production facilities; as part of an integral optimization of a project. The heart of PFSOM® is an analysis technique known as RAMP Analysis.
RAMP Analysis (Reliability, Availability, Maintainability and Process Analysis), combines techniques coming from Reliability Engineering and Process Engineering in order to predict production losses and the unavailability of a productive process, according to particular characteristics of the process involved, to the system configuration, to the reliability of its components, to maintenance policies and to the existent operational philosophy.
This analysis is based upon a powerful simulation process, which must take into account the following effects:
The main objectives of a RAMP Analysis are:
A RAMP analysis begins with the estimation of the failure and repair rate of each one of the components or equipment that conform the installation. The sources and types of information for this estimation can be of varied nature; from own data (evidence); to analog data, up to generic data.
As evidence; the own failure and repair data coming from the system under analysis should be considered; as analog data, information coming from similar systems may be included, and as sources for generic data some data banks can be
The tool to structure and mathematically support the combination of these sources of information is the Bayes Theorem. The information coming from external sources, known as “prior knowledge” and the own data, called “evidence”, are combined to obtain failure rates more representative of the operational reality of the process under analysis (updated or improved knowledge).
This improved information of the failure rates feeds an Availability Bock Diagrams model (ABD) that represents the system architecture and the field operation philosophy.
Once the RAMP Model of the Production Process is built, it works as a simulator (“what if…”), that allows inferring the impact of new maintenance policies, the application of new technologies and the changes of equipment maintainability, modification in the production process configuration, changes in the inventory policy and the introduction of new production method in system availability and deferred production.
The main products that result from a RAMP analysis are the following:
AIC® is a methodology to design and to optimize maintenance plans for productive assets and processes. These plans must contain specific tasks to minimize the recurrence of failure modes and/or to mitigate their consequences, within its operational context; everything in order to make productive systems be able to reach profitability goals and performance targets, and also to respect budget constraints and reach compliance with legal and environmental requirements.
AIC® is an evolution of the classic methodologies to develop reliability based maintenance plans such as Reliability Centered Maintenance (RCM); which is an analytical and systemic process based on the understanding of the function of the systems, its functional failures and the component failures. The heart of RCM is a systematic analysis methodology of the failure modes and effects (FMEA) that could occur in specific equipment, within its operational context. From the analysis it is possible to identify the possible causes and failure mechanisms associated to each failure mode and therefore can be inferred the preventive, predictive, detective and/or corrective tasks required to avoid the failures and/or mitigate their consequences.
AIC® allows completing optimum maintenance plans in “reasonably shorter periods of time”, using less resources (50% less time and 60% less resources than traditional RCM); i.e AIC® is an optimization of classic RCM. The following diagram shows how AIC® not only covers the traditional RCM requirements but also includes additional steps to enhance its scope.
The fundamental similarities between AIC® and RCM are:
The main improvements that AIC® has with respect to RCM are:
IPDOIM® (Inspection Plans Design and Optimization Integral Methodology) is an evolution of traditional methodologies for the design of inspection plans for static equipment and is based on the integration of methodologies Based Risk Inspection (IBR), Corrosion Risk Assessment (CRA), Mechanical Integrity (MI) and probabilistic modeling of the deterioration, which can extend the range of coverage damage mechanisms considered in the classical approach to RBI; considering among other main aspects:
However, the main basis of IPDOIMI® is Risk Based Inspection (RBI) Technology; systematic methodology based on best practices API RP 580, RP 581 and API 571 (deterioration), which aims to define inspection plans for fixed equipment, based on the probabilistic modeling of damage (probability of failure) and the consequence of failure (loss of containment function of the fluid or leakage product to the environment), to establish the scope and the date of the next inspection based on the level of tolerable risk for equipment evaluated.
The RBI Technology is based on the assessment of generic frequency of failure (historical), damage mechanisms, design features, operating conditions; maintenance, inspection and management policies, in conjunction with the quality and effectiveness of the inspection, and the consequences associated with potential failures, as shown in Figure No.1. The main deliverable of the technology, is the optimization of inspection plans. Also is very effective to optimize the Corrosion Monitoring Locations, according to the mechanisms of deterioration, risk levels and deterioration rates.
Meanwhile, Corrosion Risk Assessment (CRA), allows to establish control limits to avoid failures, in order to accomplish the "Zero Leak Policy". Main strategy is the "integrity thickness" monitoring for the static components of the system under study, based on the criteria of Corrosion Loops (similar construction materials, fluid characteristics, operating conditions and damage mechanisms). While the Mechanical Integrity (MI) aims to ensure that all process equipment are designed, procured, manufactured, built, installed, operated, inspected, maintained, and / or replaced promptly to prevent failures, accidents or potential risks to people, facilities and the environment; establishing criteria based on historical data, rules and regulations (ASME, ANSI, API, NACE, among others).
Figure No. 2 shown the sequence of steps followed for the development of MIDOPI® and based on which we can identify that the main products are:
The Cost-Risk Optimization Model (CRO Model) allows to compare the associated cost to a risk mitigation activity (preventive maintenance, predictive maintenance, substitution, re-conditioning, redesign, rehabilitation, technological upgrade, etc), against the risk reduction level or performance improvement gained by this activity. In others words, the model allows to know “how much I obtain with what I spend or invest”.
It is particularly useful to decide in scenarios with interests in conflict. A good example of this kind of scenario is the scenario “operation-maintenance”, in which the operator requires that the equipment or process operates in continuous form to guarantee maximum production, and simultaneously, the maintenance personnel requires the process shutdown with certain frequency to be able to perform proactive maintenance tasks and to win reliability in the same one.
The Cost-Risk Model allows determining the risk optimal level and appropriate maintenance amount, to obtain the maximum profit or the business minimum impact.
The figure below shows the model previously mentioned, in this case used to determine an optimum frequency for a maintenance task or proactive action. Three (3) curves plotted against time can be observed:
The "minimum" of this curve, (point on the lower level of it), represents the "minimum possible impact on the business". This point is located just over the value of time interval that represents an optimum frequency for performing the mitigation activity, a shift to the right of this point mean "taking a lot of risk" and a shift to the left of it would involve "spending too much money".
The figure below shows a CRO application on spare parts inventory optimization.
Root Cause Analysis is a deductive methodology that centers its attention on recurrent or chronic failure events or problems.
The solution to these problems will end in an risk reduction from “Major Events” or “Catastrophic Events” because they very often have their origin in common causes of chronic problems. Root Cause Analysis applies to any type of failure (Sporadic or Chronic Events).
RCA is backed by several international standards; among them, one of the most widely used standards or guidelines to support this type of analysis is in the DOE- NE- STD- 1004-92 - Root Cause Analysis Guidance Document, issued by the Department of Energy of the Government of USA.
The heart of the ACR is a logical tree called "Cause and Effect Diagram", such as that shown in Figure below.
RCA is a simple but very effective way to find the physical and latent root causes of a problem, and consequently, to identify actions or solutions to attack, minimize and / or eliminate these root causes.
To justify the solutions to a problem the RCA counts with a quick method for risk and benefit analysis for the solution or not solution of a root cause.
Finally, as a warranty of the continuity of the problem solving process the methodology states the application of a follow up and change controls system, a managerial system and a communication system as a guaranty of a continued solution of the chronic problems.
R2M International, offers a multidisciplinary approach, called Integral Reliability®, designed to optimize asset life cycle value, based upon high resolution stochastic methodologies and developments. It generates tailored made strategies suited with technically feasible, economically profitable and budget wise affordable actions.
Our approach help companies to:
It aims to ensure business robustness, emphasizing the reduction of production losses, optimizing the reliability of the processes and maximizing workers, facilities and environmental integrity.
Reservoir, Wells & Production Facilities Models Integration
Our approach for O&G is designed to link the uncertainties associated to exploration; perforation, exploitation and management of reservoirs (Subsurface); with reliability, availability maintainability and process (RAMP) issues of wells and production facilities (Surface).
All this effects are then transferred to the Economic and Decision Models to quantify and rank the risks associated to said uncertainties; in order to select proper contingency and/or mitigation action to integrate optimal strategies to drive business.