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Production forecasting in the financial markets

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Onshore, tight resource development continues to attract an increasing share of investment capital. The page shows how investors use production forecasting to mitigate downside risks and create investible opportunities in this market.


Investing is competitive. Because capital flows freely, markets quickly incorporate all publically available information about a company’s profitability and growth potential. How can E&P investors earn outsized returns in the face of a market that responds so completely and efficiently?

The trivial answer is that investors earn above-average returns by predicting a company’s cash flow both better than and before the market consensus. In order to predict cash flow, an investor with sufficient analytical expertise will start with the bedrock of an E&P company: production performance. In this context, high-quality, independent production forecasts generate a realistic expectation of performance, which may provide investors a competitive informational advantage, which might yield above-average returns. However, investors will generally only have access to publically available data.

Public domain information is sparse compared to that available to operators internally. In increasing order of objectivity, investors can generally examine:

Corporate Disclosures
This includes marketing presentations, press releases, and conference calls. This information is current and updated as new information evolves. However, it biased: even with the best intentions, management teams tend to be optimistic about asset performance.
Reserve Reports
Reserve reports and competent person’s reports provide a technically sound, but high-level summary of a company’s reserves and value at a point in time. They are usually incomplete evaluations for investors because they often don’t include asset by asset detail or sensitivities to commodity prices, whereas equities continuously price in new information. Reserve booking rules may also prevent a reserve report from including economically important resources based on arbitrary cutoffs such as drill spacing units from existing production or commodity pricing rules. If the reserves reports are produced by independent 3rd party consultants, as they often are, they will be less biased than corporate disclosures.
Geological Models
SPE papers, publically available core and log data, rock property data can be used to characterize resources in early days of development, before public production data is available. These data sources are the most difficult to collect, characterize, and evaluate. Relying on geological models exclusively will result in significant economic uncertainty, while tying a geologic model to properly evaluated production data will increase confidence in a model and forecast.
Public Production Data
Collected for royalty, severance tax and regulatory purposes, data in this category is unbiased and relatively current, but of varying quality and quantity depending on the jurisdiction.

Public production data is the backbone of independent analysis but requires resources to aggregate and expertise to analyze. Institutional investors - pension funds, hedge funds, etc, have the resources to dedicate to more detailed analysis, and these are the investors that drive the market. Sophisticated investors look for areas where analysis of public production data conflicts with corporate disclosures or reserve reports: these may be clues to market misperceptions, leading to mispriced investments and opportunities for above-average returns.

In many cases production forecasts created by analysts and engineers working on behalf of institutional money managers are at odds with an E&P company’s publically disclosed expectations. Discrepancies arise because:

Methodologies differ

The financial community primarily uses Arps or modified-Arps decline analysis to forecast production. Differences in reserve estimates compared to company disclosures can arise because of differing methodologies. Specifically, E&P companies have access to data and software that outside analysts do not. In addition, reserve estimates disclosed by companies are not always aligned with production forecasts.

The first five years have paramount importance

Investors project near-term production to the extent that it drives cash flow and NPV. Though analysts always compare their EUR estimates to company disclosures (when available), it’s near-term well performance drives the lion’s share of per-well NPV. It is less important to calculate the EUR than it is to nail down the first five years.

Fig 1 below highlights cumulative recoveries and present values by month for the same type well, with 10% vs. 0% terminal decline rate. EURs differ significantly, with a 575 Mboe modeled EUR in the 0% tlim case and 525 Mboe for the 10% tlim case. Figure 1 below highlights that while recoveries differ in these two scenarios, NPV of cash flows do not. The pink solid line represents cumulative cash flow recovery in the 10% tlim case and dotted line is the 0% tlim case, both recovering ~80% of cash flow within the first 5 years. In the 0% terminal decline case, the same type well recovers only 55% of its EUR over the same time period (orange dotted line).

INSERT Figure 1 (Pending permission approval)

Type Well Based off of a Select Sample Set

Inappropriate removal of wells from the sample

Companies remove wells from the type curve sample for a variety of reasons, including poor locations (determined in hindsight), mechanical failure, stimulation failure and so on which biases the data. These unsuccessful wells still cost money and add to a company’s cost structure.

Blue-sky scenarios are risky

Company disclosed production forecasts and type curves are sometimes reflective of a select subset of optimized wells. While trends in optimization matter, base case production forecasts used by analysts reflect current reality, leaving future optimized well results valued as options. Upside scenarios generally won’t be entirely priced into equity values.

Fig 2, Fig 3, and Fig 4 below highlights a company’s disclosed type curve from its corporate investor presentation, which we compare and plot alongside public production data. The company curve shows a significantly shallower early-time decline. Perhaps the company disclosed an aspirational curve, or maybe the company had private data to suggest that a shallower decline is appropriate. In any event, evaluating the reasons for this discrepancy can lead to investable opportunities.

INSERT Figure 2 Type well oil production profile (Pending permission approval)

INSERT Figure 3 Gross EUR  (Pending permission approval)

INSERT Figure 4 Company disclosed type curve erses public data (Pending permission approval)

Only the change in downtime matters

At the core of any analysis, the type curve used as a basis for go-forward modeling has to be reflective of the actual cash flow stream. This means modeling downtime. While this has little to no impact on expected recoveries, cash flows differ in near term by the percentage of time a well is not producing. If downtime assumptions are consistent through time, then using downtime-adjusted producing-day models will predict cash flows accurately.

Consequences of upside and downside risks are asymmetric

For long investors, missed guidance, negative reserve revisions and dashed expectations get investment managers fired, while an unexpected improvement earns a pat on the back and a bonus. The asymmetry of risks makes investors especially sensitive to downside scenarios, and once trust in a management team is lost, it is difficult to regain.

Fig 5 highlights production per day guidance ranges, actuals and share price impact for an NYSE listed upstream producer. The blue boxes below represent quarterly guidance and dots within each are actual production per day realized in that quarter. Red dots indicate median guidance misses and green dots indicate where median guidance was exceeded. The grey line represents share price performance over the same period. You can see that, generally (and all else equal in the commodity cycle), production misses have a negative impact on share price and exceeding guidance has a positive impact on share price. This is highlighted as “price impact (%)” in the bar chat at the below.

INSERT Figure 5 Company xyz stock price verses production guidance and actuals (Pending permission approval)

Recent results carry higher weight

Investors struggle with the question of how much the future will look like the past, a question with the highest risks and payoffs at the early stage of a play’s development. It’s common for different investors and managements to have widely divergent views in the early days of a play, based on the same data set but with different views on the relevance of particular data points.

Type curves used during the geologic de-risking phase are typically based on the closest geologic analog. Beyond 20 wells with at least one to two years of history, data can typically be used to derive appropriate initial type curves. In a success scenario, development typically follows an accelerated pace through geological de-risking, commercial de-risking and commercial development as highlighted in the figure below. An economic or technical failure scenario typically sees peak operator count within the first two years with a steady decline as the play proves to be uneconomic Fig 6.

INSERT Figure 6 Permian Midland: Success (Pending permission approval)

Fig 6 highlights the success phases in the Permian Midland through the following phases:

Geologic de-risking

Typically takes 1-2 years and ~20 wells from a limited number of operators. This phase gives “proof of concept,” and will be the biggest investor payoff in a success scenario, but carries the highest risk of uncertainty around type curve modeling and economics.

Commercial de-risking

1-2 more years to a well count of 200-400 wells, with a rapidly increasing operator count. This phase proves up the core and identifies economic boundaries. This is the greatest opportunity for investors to analyze production and completions data/trends to predict the evolution of performance and type curves, make calls ahead of the market consensus and position investments

Commercial development

Accelerated development pace for existing operators and potentially new play entrants. Development is focused on the most economic areas of the play, with performance of core/non-core areas typically well-defined and understood by the broader market. The market focus here is on commercial development economies of scale and the change of type curves as a result of completion and stimulation experimentation and optimization.

In a failure scenario, operator count typically peaks within the first two years (~10-20 wells) with activity dropping off thereafter. The play will see consistent decline in operators over subsequent years as drilling fails to become economic.

INSERT Figure 7 Alberta Bakken: Marginal technical success with economic failure (Pending permission approval)


Noteworthy papers in OnePetro

Noteworthy books

Society of Petroleum Engineers (U.S.). 2011. Production forecasting. Richardson, Tex: Society of Petroleum Engineers. WorldCat or SPE Bookstore

External links

Production forecasts and reserves estimates in unconventional resources. Society of Petroleum Engineers.

Production Forecasts and Reserves Estimates in Unconventional Resources. Society of Petroleum Engineers.

See also

Production forecasting glossary

Aggregation of forecasts

Challenging the current barriers to forecast improvement

Commercial and economic assumptions in production forecasting

Controllable verses non controllable forecast factors

Discounting and risking in production forecasting

Documentation and reporting in production forecasting

Empirical methods in production forecasting

Establishing input for production forecasting

Integrated asset modelling in production forecasting

Long term verses short term production forecast

Look backs and forecast verification

Material balance models in production forecasting

Probabilistic verses deterministic in production forecasting

Production forecasting activity scheduling

Production forecasting analog methods

Production forecasting building blocks

Production forecasting decline curve analysis

Production forecasting expectations

Production forecasting flowchart

Production forecasting frequently asked questions and examples

Production forecasting in the financial markets

Production forecasting principles and definition

Production forecasting purpose

Production forecasting system constraints

Quality assurance in forecast

Reservoir simulation models in production forecasting

Types of decline analysis in production forecasting

Uncertainty analysis in creating production forecast

Uncertainty range in production forecasting

Using multiple methodologies in production forecasting