oilgas

Shale Completions

Situation

Given the current economic climate, oil price is predicted to remain at low/medium ranges for the foreseeable future.

Complication

Hence, drilling and completing wells economically have become more challenging than ever before.

Question

How can we improve our drilling and completions?

Answer

Our software has been trained on over 14,000 shale wells. It prescribes specific completions recipes, and predicts corresponding production and economics. You can dramatically improve completions performance and avoid costly mistakes in the field.

Field Development

Situation

Given the current economic climate, oil price is predicted to remain at low/medium ranges for the foreseeable future.

Complication

Because of this, managing an entire block or portfolio of wells and developing them effectively can often be the difference between boom or bust.

Question

How can an operator use all of their data to decide which blocks to develop first and how?

Answer

Our software incorporates all kinds of data, in all formats, all the time. Everything from geologic maps to economic type curves is incorporated in this one-of-a-kind analysis which allows you to test new completions recipe strategies across a field, infill drilling patterns, and production operations strategies. Choose to design based on geologic trends or come up with generations of recipes while tracking complex behavior such as frac hits, well bore proximity depletion, and frac order.

Payzone Identification

Situation

Given the current economic climate, oil price is predicted to remain at low/medium ranges for the foreseeable future.

Complication

Exploration is often the costliest part of the oil and gas development chain. Mistakes made while determining where quality reservoirs exist can be extremely detrimental to a company’s economic standing.

Question

How can an operator improve its confidence in predicting locations and volumes of quality reservoir?

Answer

Our software uses seismic and well log data to train artificial intelligence algorithms to identify quality reservoir rock with high confidence. Output exists in the form of a probability map, with emphasis on the facies of choice to drill or avoid (sand, shale, carbonate). These probabilities can be used in conjunction with traditional geophysics analysis and for economic calculations to de-risk and evaluate exploration projects.