The profitability of a well in an unconventional play is significantly influenced by its completion. It is widely understood that tighter rock needs more stimulation to economically recover hydrocarbons. However, how does one know if a well is being over-stimulated (fracture area created does not justify cost incurred) or under-stimulated (lost potential/profitability in productivity from a well's limited contact to the formation)?
The objective of this paper is to develop and demonstrate an efficient workflow that will help stakeholders make better decisions in the area of completion planning. The workflow utilizes information from fracture modeling, production data analysis, and project economics to quantify the relationship between the key input parameters of the well completion (e.g. pumping rate, proppant and fluid pumped) and expected profitability expressed in net present value (NPV) terms. As a secondary objective, the case study demonstrates that a probabilistic approach (Monte Carlo Simulation) can be used to efficiently arrive at a consistent conclusion to the primary workflow. The output of the probabilistic model includes P90/P50/P10 production and net cash-flow forecasts, from which distributions of NPV can be obtained.
This workflow is intended to help engineers compare profitability among different completion options. A shale gas field example is presented to illustrate the methodology.
A company's performance in a lease sale can have serious implications for future growth and sustained value. Therefore it makes sense to approach each sale armed with the most powerful tools available. Surprisingly few firms go beyond spreadsheet analysis when it comes to such an important event, most likely because it is the most familiar method. Perhaps this is why we see bid levels with a significant amount of spread, representing "money left on the table" or skewed perspectives on the value of the block.
Firms that wish to move to the next level take a different view. They choose to engage their best talent in a
Building a bid strategy capability using simulation as a centerpiece is challenging, complex work, requiring key data sets and a mastery of the underlying technology simultaneously. That does not mean that best in class bid strategy is not attainable – it comes about with a focus on execution.
We will touch on many of the lessons we learned in working side by side with an aggressive lease sale bidder, and their journey from unsatisfactory auction performance to a place among the top tier of bidders: Use the talent you already have, but provide the team with an analytical system to translate knowledge into bidder intelligence. Build a serious blueprint of the bidding system before implementation Use the simulations to "steer" the bid strategy
Use the talent you already have, but provide the team with an analytical system to translate knowledge into bidder intelligence.
Build a serious blueprint of the bidding system before implementation
Use the simulations to "steer" the bid strategy
We will focus on the practical, actionable steps to build a better bid strategy through analytics, sustainable across a range of lease sales, both in the US and abroad. As of this writing, Mexico had recently announced plans to conduct auctions on offshore license blocks starting in 2015, and the US BOEM announced a major lease sale each in the Central and Eastern GoM regions scheduled for March 2014.
Ekweanua, U. Emmanuel (University of Oklahoma) | Sharma, Suresh C. (University of Oklahoma) | Wu, Xingru (University of Oklahoma) | Zhu, Zhen (University of Oklahoma) | Callard, Jeffrey G. (University of Oklahoma)
In the United States, hydrocarbon in unconventional resources such as shale gas has been dramatically changing the fossil energy prospect and transforming the energy consumption structure. Therefore, it is imperative to study how this trend has impacted the U.S. natural gas import, export and the domestic gas price. To understand the relationships, Neural Network would be used to model these variables (gas production, price, import and export) with the ultimate goal of understanding the gas price determination. The key input parameters for the Network are gas production, import and export data and the resulting output of the Network would be the gas price i.e. how well this inputs influence gas price and there magnitude of impact would be ranked in this study. Impact of Weather would be looked into as well but it is not part of the Network inputs. Data from Energy Information Administration (EIA) of the U.S. Department of Energy will be utilized in this study.
This work is motivated by the recent surging interest in converting existing gas import terminals to exporting terminals due to increase in gas production as a result of major technological advancement in getting formerly untapped gas out of the ground. The changes in the gas industry trend have prompted the government to consider policy changes as well. Our study will enable us to draw some policy implications regarding the U.S. energy policy.
Due to the success of shale gas developments observed in the US and the absence of domestic legislation specifically for unconventional gas projects in the countries, an arising question is whether replicating the fiscal terms conceptually conceived for conventional oil and gas exploration would be appropriate for the exploitation of unconventional gas deposits. To assess this issue, this study approached the question with a fiscal policy formulation perspective. It was assumed that a desirable fiscal system, able to balance opposed objectives from the Government and private investors would be a flexible, neutral and stable one, favourable to maximize the present value of the project. To address the question, this article makes a comparison between shale gas projects and conventional gas projects to examine if they have structures similar enough to be covered by the same fiscal regime or if the legislation needs to cover issues that are exclusive to shale gas projetcs. The analysis showed that, first, the basis of comparison would be better segmented between oil projects and gas projects – either from conventional or unconventional sources, since this last category has less margin of rent available to be taxed. Besides that, shale gas projects have particularities that should be considered by policy makers when designing a fiscal system to encourage its development. Furthermore, fiscal instruments can be a powerful tool to guide tax payers behavior and hence address other concerns not necessarily related to revenue-raising, bur, for example, environmental and social issues.
Technical professionals are often asked to estimate "ranges" for uncertain quantities. It is important that they distinguish whether they are being asked for variability ranges or uncertainty ranges. Likewise, it is important for modelers to know if they are building models of variability or uncertainty, and their relationship, if any.
We discuss and clarify the distinction between uncertainty and variability through strict definition, illustrative analogy and numerical examples. Uncertainty means we do not know the value (or outcome) of some quantity, eg the average porosity of a specific reservoir (or the porosity of a core-sized piece of rock at some point within the reservoir). Variability refers to the multiple values a quantity has at different locations, times or instances – eg the average porosities of a collection of different reservoirs (or the range of core-plugs porosities at different locations within a specific reservoir).
Uncertianty is quantified by a probability distribution which depends upon our state of
We show there is no objectively ‘right’ probability distribution for quantifying the uncertainty of an unknown event – it can only be ‘right’ in that it is consistent with the assessor's information. Thus, different people (or teams or companies) can legitimately hold different probabilities for the same event. Only in very restrictive, arguably unrealistic, situations can we choose to use a frequency distribution derived from variability data as a probability distribution to represent our uncertainty in an event's outcome.
Our experience as educators of students and oil & gas industry personnel suggests that significant confusion exists in their understanding of the distinction between variability and uncertainty. This paper thus provides a resource for technical professionals and teachers to clarify the distinction between the two, or to correct it where it has been wrongly taught, and thereby help to improve decision-making.
Declining global economic conditions and increased pressure to find new, affordable sources of energy create a turbulent macro environment for oil and gas companies. Stakeholders present conflicting goals of increased return on investment while simultaneously reducing risk and providing greater transparency into project performance. The traditional models of large scale investment into major capital projects can no longer guarantee success; instead, organizations must focus on capital management throughout a project's life cycle. Significant effort, time, and resources are invested in project delivery. However, poor decisions during the planning phases may result in loss of value during execution. By combining decision analysis tools and techniques with integrated, dynamic planning systems, companies are able to carefully manage their capital across the project life cycle to understand their costs, resources, and schedules. These companies benefit from increased collaboration leading to more informed decision making balancing risk and reward.
This paper presents an innovative method for evaluating and dynamically planning the development of uncertain upstream investments. It centers on a paradigm shift in the way upstream managers assess investments, toward an approach that incorporates decision analysis tools and techniques with integrated dynamic planning systems. Case study examples are provided to illustrate key principles.
The importance of improved guidance for the estimation and classification of "Resources other than Reserves" (abbreviated herein as ROTR) has recently been driven by the evolution of the petroleum industry away from maturing conventional accumulations towards unconventional accumulations such as petroleum in ultra-low permeability reservoirs (including shales) and heavy oil/bitumen resources. Commonly these unconventional opportunities involve newer, capital intensive technologies to exploit areally extensive deposits; accordingly, early-stage estimates of in-place petroleum quantities and potentially recoverable volumes may be very large, creating new and critical challenges to communicating clear and consistent information, including the associated uncertainties, relating to resource opportunities. To date, evaluators involved in estimation and reporting of ROTR have had to rely on only limited guidance.
Under Canadian Securities Administrators National Instrument (NI) 51–101 Standards of Disclosure for Oil and Gas Activities, companies are obligated to disclose Proved and Probable Reserves but have the option to additionally disclose Possible Reserves, Contingent Resources and Prospective Resources. NI 51–101 references technical guidelines contained in the Canadian Oil and Gas Evaluation Handbook (COGEH) maintained by the Canadian Chapter of the Society of Petroleum Evaluation Engineers (SPEE). Disclosure of ROTR estimates in Canada has increased substantially in recent years and based on reviews of many filings, is often unclear, inconsistent or potentially misleading. A SPEE Calgary committee has recently proposed additional guidance to promote and improve consistency in the estimation of ROTR for business operations and public disclosure. It is intended to augment other guidelines in COGEH Volumes 1 to 3. Issues addressed with respect to estimation, classification and reporting of ROTR include the following: Clarification of definitions and principles pertaining to petroleum accumulations, particularly in relation to continuous deposits, Clarification of definitions and principles pertaining to recovery projects and technologies, Exploration and technical and commercial risks, Aggregation of resource estimates. Guidance on reporting the results of ROTR evaluations
Clarification of definitions and principles pertaining to petroleum accumulations, particularly in relation to continuous deposits,
Clarification of definitions and principles pertaining to recovery projects and technologies,
Exploration and technical and commercial risks,
Aggregation of resource estimates.
Guidance on reporting the results of ROTR evaluations
Reporting of the results of a resource evaluation under the recommended revised guidelines should provide information for both internal management and external investors sufficient to make informed investment decisions. The revised definitions and classification guidance may be equally applicable in future updates of the Petroleum Resources Management System (PRMS).
The process of upstream planning for the oil and gas industry has historically been a time consuming and inefficient process. The majority of effort is spent collecting data from multiple functional areas and organizational teams within an organization to form a holistic view of a company. By introducing an integrated solution that combines the opportunity catalog, economic analysis, and optimization into a single workflow, planners are experiencing efficiency gains, reduced time spent planning, and more accurate results. Through an analysis of the implementation of such a system at Chevron's Gulf of Mexico Business Unit (GOMBU), the challenges and benefits of implementing an integrated business planning approach as described will be demonstrated.
This paper will reflect on the systems, processes and workflows involved in the planning process at GOMBU both before and after deploying an integrated planning solution consisting of an opportunity catalog and linear optimization tool. This paper will also describe the challenges faced during the implementation and the benefits gained after the solution was deployed. Define "Vision" and reason for move to linear optimization Discuss state prior to deployment Evaluate technical challenges with current state Review state after deployment Examine results and gained benefits Proposed model for integrated planning framework Improved efficiency of portfolio optimization was significant, optimization time went from several weeks to days Portfolio optimization process was more fluid and responsive to changing business environments Secondary value generated to the entire organization in data integrity, consistency, management visibility into data, and traceability through opportunity maturation. Significant improvement in planning efficiency and accuracy achieved through implementation and execution of proposed architecture Integrated planning saves time, money and leads to significant value realization Learnings are applicable to any mid-to-large sized organization with any aspect of the planning process Combination of opportunity tracking and planning into a single workflow Combination of Opportunity Catalog, Economics Engine, and Linear Optimizer into a single portfolio analysis package Cross-functional visibility and input into the plan and communication of results
Define "Vision" and reason for move to linear optimization
Discuss state prior to deployment
Evaluate technical challenges with current state
Review state after deployment
Examine results and gained benefits
Proposed model for integrated planning framework
Improved efficiency of portfolio optimization was significant, optimization time went from several weeks to days
Portfolio optimization process was more fluid and responsive to changing business environments
Secondary value generated to the entire organization in data integrity, consistency, management visibility into data, and traceability through opportunity maturation.
Significant improvement in planning efficiency and accuracy achieved through implementation and execution of proposed architecture
Integrated planning saves time, money and leads to significant value realization
Learnings are applicable to any mid-to-large sized organization with any aspect of the planning process
Combination of opportunity tracking and planning into a single workflow
Combination of Opportunity Catalog, Economics Engine, and Linear Optimizer into a single portfolio analysis package
Cross-functional visibility and input into the plan and communication of results
Energy, coming in its great majority from oil and gas has become a strategic factor in global geopolitics. It is key to national power and a major requirement for economic growth. Energy consumption has become the most palpable national characteristic that separates rich from poor countries. The United States, the richest nation in the "room" is also the most intense user of energy per capita.
There is a substantial imbalance in the location of energy producers and consumers, an imbalance that has precipitated world conflicts and one that will likely cause future upheavals. There is huge activity by China buying energy resources all around the world. Russia's recent ascendancy in the energy world has been an important counterbalance to the power of OPEC. However, recent events surrounding Russia's energy industry have exposed fissures within the economic and political makeup of the country.
The United States Shale Revolution has, and will, bring market distortions throughout the entire nation and to many others such as the energy-starving, Southeast Asia markets of China and Japan. The recent removal of restrictions on LNG exports by the American government means that new forces will be implemented on both demand and supply of those markets. I believe that the globalization of gas trade will make prices of natural gas to converge and thus we will witness a more "unified" price regime in the not-too-distant future. Predictions of the future supply of petroleum have typically been far less accurate than predictions of demand. Flawed predictions have caused public bewilderment, distrust and, more importantly, government inaction or poorly conceived reactions. The cause of every energy crisis, like oil climbing to $150 per barrel in 2008 before dropping to $40, is above the ground geopolitics and never behind the valve issues.
This paper applies basic economic principles to assess the effects of present-day geopolitical forces on energy markets, particularly those of natural gas, around the globe arriving on a number of interesting conclusions. Topics touched include Chinese urbanization, United States LNG exports, Keystone XL Pipeline, Russian nationalization over its energy industry and its relationship with former Soviet Union countries.
In the oil and gas industry, the term "business planning" brings visions of late nights, additional meetings, and countless hours spent collecting and reconciling large amounts of data. This negative connotation has been reinforced over the years as companies struggle to pull together the information they need to create realistic and achievable plans and to forecast future development to guide the growth of their business.
It is unfortunate that business planning has such a bad reputation as it is critical to the success of any company in any industry. In business planning, the goals are simply to select the best projects from a portfolio of opportunities to maximize the return on investment, while being able to effectively communicate the details of how the different scenarios were created to provide confidence in the decision to invest.
This paper describes a case study in which one of Occidental Oil and Gas Corporation (Oxy BU) business units improved a few key elements in their business planning process which helped them create a more realistic, higher return plan, faster.
The Oxy BU saw the potential rewards that improvements to their planning process could generate by improving their planning efficiency, reducing errors, and breaking out of the same painful cycle they had experienced in previous years. In this paper, we present the results of the improved workflow, focusing on those which were seen to have the largest impact on results including:
Data consistency: Consistent capture and reporting of data across all teams Minimize bias: P50 curves developed, compared, and reviewed across teams Risk analysis: Improved ability to account for granular risk factors across plan Type well scheduling: Increased ability to rapidly build, explore, and turn-around new scenarios Opportunity selection: Increased value of the portfolio Visibility of the plan: Increased communication and buy-in from teams Time to market data: More realistic view of cash flows and activities Resource balancing: Increased confidence in ability to execute the plan
Using this new approach, the Oxy BU planning team was able to turn around three different investment scenarios, numerous development strategies, and create a five-year, long-range plan that the entire management team could present and stand behind.